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Hustrini NM, Susalit E, Widjaja FF, Khumaedi AI, Dekkers OM, van Diepen M, Rotmans JI. The Etiology of Advanced Chronic Kidney Disease in Southeast Asia: A Meta-analysis. J Epidemiol Glob Health 2024:10.1007/s44197-024-00209-5. [PMID: 38587764 DOI: 10.1007/s44197-024-00209-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 02/14/2024] [Indexed: 04/09/2024] Open
Abstract
INTRODUCTION Chronic kidney disease (CKD) etiology varies greatly between developed and developing countries. In addition, differences in underlying pathogenesis and therapeutic options affect the progression towards advanced-CKD. This meta-analysis aims to identify the etiology of advanced-CKD in Southeast Asia. METHODS A systematic search in four electronic-databases and complementary search on national kidney registries and repository libraries was conducted until July 20, 2023. The risk of bias was assessed using Newcastle-Ottawa Scale for observational studies and Version-2 of Cochrane for intervention studies. A random-effects model was used to estimate pooled prevalence. The protocol is registered in the International Prospective Register of Systematic Reviews PROSPERO; Registration ID:CRD42022300786. RESULTS We analyzed 81 studies involving 32,834 subjects. The pooled prevalence of advanced-CKD etiologies are diabetic kidney disease (DKD) 29.2% (95%CI 23.88-34.78), glomerulonephritis 20.0% (95%CI 16.84-23.38), hypertension 16.8% (95%CI 14.05-19.70), other 8.6% (95%CI 6.97-10.47), unknown 7.5% (95%CI 4.32-11.50), and polycystic kidney disease 0.7% (95%CI 0.40-1.16). We found a significant increase in DKD prevalence from 21% (9.2%, 95%CI 0.00-33.01) to 30% (95%CI 24.59-35.97) before and after the year 2000. Among upper-middle-income and high-income countries, DKD is the most prevalent (26.8%, 95%CI 21.42-32.60 and 38.9%, 95%CI 29.33-48.79, respectively), while glomerulonephritis is common in lower-middle-income countries (33.8%, 95%CI 15.62-54.81). CONCLUSION The leading cause of advanced-CKD in Southeast Asia is DKD, with a substantial proportion of glomerulonephritis. An efficient screening program targeting high-risk populations (diabetes mellitus and glomerulonephritis) is needed, with the aim to delay CKD progression.
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Affiliation(s)
- Ni Made Hustrini
- Division of Nephrology and Hypertension, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia
- Department of Internal Medicine, Leiden University Medical Center, Albinusdreef 2, Leiden, The Netherlands
| | - Endang Susalit
- Division of Nephrology and Hypertension, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia
| | | | - Anandhara Indriani Khumaedi
- Division of Nephrology and Hypertension, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia
| | - Olaf M Dekkers
- Department of Internal Medicine, Leiden University Medical Center, Albinusdreef 2, Leiden, The Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Joris I Rotmans
- Department of Internal Medicine, Leiden University Medical Center, Albinusdreef 2, Leiden, The Netherlands.
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Milders J, Ramspek CL, Janse RJ, Bos WJW, Rotmans JI, Dekker FW, van Diepen M. Prognostic Models in Nephrology: Where Do We Stand and Where Do We Go from Here? Mapping Out the Evidence in a Scoping Review. J Am Soc Nephrol 2024; 35:367-380. [PMID: 38082484 PMCID: PMC10914213 DOI: 10.1681/asn.0000000000000285] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024] Open
Abstract
Prognostic models can strongly support individualized care provision and well-informed shared decision making. There has been an upsurge of prognostic research in the field of nephrology, but the uptake of prognostic models in clinical practice remains limited. Therefore, we map out the research field of prognostic models for kidney patients and provide directions on how to proceed from here. We performed a scoping review of studies developing, validating, or updating a prognostic model for patients with CKD. We searched all published models in PubMed and Embase and report predicted outcomes, methodological quality, and validation and/or updating efforts. We found 602 studies, of which 30.1% concerned CKD populations, 31.6% dialysis populations, and 38.4% kidney transplantation populations. The most frequently predicted outcomes were mortality ( n =129), kidney disease progression ( n =75), and kidney graft survival ( n =54). Most studies provided discrimination measures (80.4%), but much less showed calibration results (43.4%). Of the 415 development studies, 28.0% did not perform any validation and 57.6% performed only internal validation. Moreover, only 111 models (26.7%) were externally validated either in the development study itself or in an independent external validation study. Finally, in 45.8% of development studies no useable version of the model was reported. To conclude, many prognostic models have been developed for patients with CKD, mainly for outcomes related to kidney disease progression and patient/graft survival. To bridge the gap between prediction research and kidney patient care, patient-reported outcomes, methodological rigor, complete reporting of prognostic models, external validation, updating, and impact assessment urgently need more attention.
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Affiliation(s)
- Jet Milders
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Chava L. Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Roemer J. Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Willem Jan W. Bos
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Santeon, Utrecht, The Netherlands
- Department of Internal Medicine, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - Joris I. Rotmans
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W. Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Akerboom B, Janse RJ, Caldinelli A, Lindholm B, Rotmans JI, Evans M, van Diepen M. A tool to predict the risk of lower extremity amputation in patients starting dialysis. Nephrol Dial Transplant 2024:gfae050. [PMID: 38409858 DOI: 10.1093/ndt/gfae050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND AND HYPOTHESIS Non-traumatic lower extremity amputation (LEA) is a severe complication during dialysis. To inform decision-making for physicians, we developed a multivariable prediction model for LEA after starting dialysis. METHODS Data from the Swedish Renal Registry (SNR) between 2010 and 2020 were geographically split into a development and validation cohort. Data from NECOSAD between 1997 and 2009 were used for validation targeted at Dutch patients. Inclusion criteria were no previous LEA and kidney transplant and age ≥ 40 years at baseline. A Fine-Gray model was developed with LEA within 3 years after starting dialysis as outcome of interest. Death and kidney transplant were treated as competing events. One coefficient, ordered by expected relevance, per 20 events was estimated. Performance was assessed with calibration and discrimination. RESULTS SNR was split into an urban development cohort with 4 771 individuals experiencing 201 (4.8%) events and a rural validation cohort with 4.876 individuals experiencing 155 (3.2%) events. NECOSAD contained 1 658 individuals experiencing 61 (3.7%) events. Ten predictors were included: female sex, age, diabetes mellitus, peripheral artery disease, cardiovascular disease, congestive heart failure, obesity, albumin, haemoglobin and diabetic retinopathy. In SNR, calibration intercept and slope were -0.003 and 0.912 respectively. The C-index was estimated as 0.813 (0.783-0.843). In NECOSAD, calibration intercept and slope were 0.001 and 1.142 respectively. The C-index was estimated as 0.760 (0.697-0.824). Calibration plots showed good calibration. CONCLUSION A newly developed model to predict LEA after starting dialysis showed good discriminatory performance and calibration. By identifying high-risk individuals this model could help select patients for preventive measures.
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Affiliation(s)
- Bram Akerboom
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Roemer J Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Aurora Caldinelli
- Department of Clinical Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Bengt Lindholm
- Department of Clinical Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Joris I Rotmans
- Department of Internal Medicine, Division of Nephrology, Leiden University Medical Center, Leiden, the Netherlands
| | - Marie Evans
- Department of Clinical Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
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Luppino F, van Diepen M, den Hollander-Gijsman M, Bartlema K, Dekker F. Level of Overestimation Among Dutch Recreational Skiers: Unskilled Tourists in the Mountains. Clin J Sport Med 2023; 33:e172-e180. [PMID: 37235852 DOI: 10.1097/jsm.0000000000001158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 03/29/2023] [Indexed: 05/28/2023]
Abstract
OBJECTIVE To examine the level of overestimation (LO), associated factors, and identify the group of severe overestimators, among recreational skiers. DESIGN Cross-sectional observational study. SETTING An intermediate difficulty slope in an artificial snow indoor ski hall, and one in the mountains (Flachau, Austria). PARTICIPANTS Dutch recreational skiers. INDEPENDENT VARIABLES Participants were asked to rate themselves (SRSS, self-reported skill score). While skiing downhill they were objectively evaluated by 2 expert assessors (OSS, observed skill score). Potential associated factors and predictors for severe overestimation were assessed by a questionnaire. MAIN OUTCOME MEASURES The LO, calculated by subtracting the OSS from the SRSS, was categorized into "no," "mild," and "severe." Potential differences between these groups were analyzed, and regression analyses were performed to identify the factors associated with severe overestimation. To construct a profile of severe overestimators, the dataset was stratified based on 3 variables. RESULTS Overestimation was largely present (79.8%), and was severe in 32%. The LO decreased toward the more skilled skiers. Severe overestimators were mainly male, skied the least hours per day, were more avoidant, and showed the highest proportions of beginners and slightly advanced skiers. The profile of "severe overestimator" is characterized by physically unprepared males, avoidant for certain weather circumstances. CONCLUSIONS Overestimation among recreational Dutch skiers is largely present, particularly among physically unprepared males, avoidant of certain snow and weather conditions. These features may function as a proxy to identify "severe overestimators" in comparable populations. Preventive strategies should focus to increase awareness particularly among these subjects.
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Affiliation(s)
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Centre, the Netherlands
| | | | - Kornelis Bartlema
- Department of Traumatology, Leiden University Medical Centre, the Netherlands
| | - Friedo Dekker
- Department of Clinical Epidemiology, Leiden University Medical Centre, the Netherlands
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Schutter R, Sanders JSF, Ramspek CL, Crop MJ, Bemelman FJ, Christiaans MH, Hilbrands LB, de Vries AP, van de Wetering J, van Zuilen AD, van Diepen M, Leuvenink HG, Dekker FW, Moers C. Considerable Variability Among Transplant Nephrologists in Judging Deceased Donor Kidney Offers. Kidney Int Rep 2023; 8:2008-2016. [PMID: 37850026 PMCID: PMC10577326 DOI: 10.1016/j.ekir.2023.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/05/2023] [Accepted: 07/17/2023] [Indexed: 10/19/2023] Open
Abstract
Introduction Transplant clinicians may disagree on whether or not to accept a deceased donor kidney offer. We investigated the interobserver variability between transplant nephrologists regarding organ acceptance and whether the use of a prediction model impacted their decisions. Methods We developed an observational online survey with 6 real-life cases of deceased donor kidneys offered to a waitlisted recipient. Per case, nephrologists were asked to estimate the risk of adverse outcome and whether they would accept the offer for this patient, or for a patient of their own choice, and how certain they felt. These questions were repeated after revealing the risk of adverse outcome, calculated by a validated prediction model. Results Sixty Dutch nephrologists completed the survey. The intraclass correlation coefficient of their estimated risk of adverse outcome was poor (0.20, 95% confidence interval [CI] 0.08-0.62). Interobserver agreement of the decision on whether or not to accept the kidney offer was also poor (Fleiss kappa 0.13, 95% CI 0.129-0.130). The acceptance rate before and after providing the outcome of the prediction model was significantly influenced in 2 of 6 cases. Acceptance rates varied considerably among transplant centers. Conclusion In this study, the estimated risk of adverse outcome and subsequent decision to accept a suboptimal donor kidney varied greatly among transplant nephrologists. The use of a prediction model could influence this decision and may enhance nephrologists' certainty about their decision.
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Affiliation(s)
- Rianne Schutter
- Department of Surgery–Organ Donation and Transplantation, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Jan-Stephan F. Sanders
- Department of Internal Medicine, Division of Nephrology, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Chava L. Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, the Netherlands
| | - Meindert J. Crop
- Department of Internal Medicine, Division of Nephrology, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Frederike J. Bemelman
- Department of Internal Medicine, Division of Nephrology, Amsterdam University Medical Center, the Netherlands
| | - Maarten H.L. Christiaans
- Department of Internal Medicine, Division of Nephrology, Maastricht University Medical Center, the Netherlands
| | - Luuk B. Hilbrands
- Department of Nephrology, Radboud University Medical Center, the Netherlands
| | - Aiko P.J. de Vries
- Department of Internal Medicine, Division of Nephrology, and Leiden Transplant Center, Leiden University Medical Center, the Netherlands
| | | | - Arjan D. van Zuilen
- Department of Internal Medicine, Division of Nephrology, University Medical Center Utrecht, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, the Netherlands
| | - Henri G.D. Leuvenink
- Department of Surgery–Organ Donation and Transplantation, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Friedo W. Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, the Netherlands
| | - Cyril Moers
- Department of Surgery–Organ Donation and Transplantation, University Medical Center Groningen, University of Groningen, the Netherlands
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Janse RJ, van Diepen M, Ramspek CL. Predicting Kidney Failure With the Kidney Failure Risk Equation: Time to Rethink Probabilities. Am J Kidney Dis 2023; 82:381-383. [PMID: 37589626 DOI: 10.1053/j.ajkd.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 06/16/2023] [Accepted: 07/03/2023] [Indexed: 08/18/2023]
Affiliation(s)
- Roemer J Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
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Langenhuijsen LFS, Janse RJ, Venema E, Kent DM, van Diepen M, Dekker FW, Steyerberg EW, de Jong Y. Systematic metareview of prediction studies demonstrates stable trends in bias and low PROBAST inter-rater agreement. J Clin Epidemiol 2023; 159:159-173. [PMID: 37142166 DOI: 10.1016/j.jclinepi.2023.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/30/2023] [Accepted: 04/25/2023] [Indexed: 05/06/2023]
Abstract
OBJECTIVES To (1) explore trends of risk of bias (ROB) in prediction research over time following key methodological publications, using the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and (2) assess the inter-rater agreement of the PROBAST. STUDY DESIGN AND SETTING PubMed and Web of Science were searched for reviews with extractable PROBAST scores on domain and signaling question (SQ) level. ROB trends were visually correlated with yearly citations of key publications. Inter-rater agreement was assessed using Cohen's Kappa. RESULTS One hundred and thirty nine systematic reviews were included, of which 85 reviews (containing 2,477 single studies) on domain level and 54 reviews (containing 2,458 single studies) on SQ level. High ROB was prevalent, especially in the Analysis domain, and overall trends of ROB remained relatively stable over time. The inter-rater agreement was low, both on domain (Kappa 0.04-0.26) and SQ level (Kappa -0.14 to 0.49). CONCLUSION Prediction model studies are at high ROB and time trends in ROB as assessed with the PROBAST remain relatively stable. These results might be explained by key publications having no influence on ROB or recency of key publications. Moreover, the trend may suffer from the low inter-rater agreement and ceiling effect of the PROBAST. The inter-rater agreement could potentially be improved by altering the PROBAST or providing training on how to apply the PROBAST.
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Affiliation(s)
| | - Roemer J Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Esmee Venema
- Department of Public Health, Erasmus MC University Medical Center, Rotterdam, The Netherlands; Department of Emergency Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - David M Kent
- Predictive Analytics and Comparative Effectiveness Center, Tufts Medical Center, Boston, MA, USA
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ewout W Steyerberg
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands; Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands.
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Haapio M, van Diepen M, Steenkamp R, Helve J, Dekker FW, Caskey F, Finne P. Predicting mortality after start of long-term dialysis-International validation of one- and two-year prediction models. PLoS One 2023; 18:e0280831. [PMID: 36812268 PMCID: PMC9946236 DOI: 10.1371/journal.pone.0280831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 01/10/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Mortality prediction is critical on long-term kidney replacement therapy (KRT), both for individual treatment decisions and resource planning. Many mortality prediction models already exist, but as a major shortcoming most of them have only been validated internally. This leaves reliability and usefulness of these models in other KRT populations, especially foreign, unknown. Previously two models were constructed for one- and two-year mortality prediction of Finnish patients starting long-term dialysis. These models are here internationally validated in KRT populations of the Dutch NECOSAD Study and the UK Renal Registry (UKRR). METHODS We validated the models externally on 2051 NECOSAD patients and on two UKRR patient cohorts (5328 and 45493 patients). We performed multiple imputation for missing data, used c-statistic (AUC) to assess discrimination, and evaluated calibration by plotting average estimated probability of death against observed risk of death. RESULTS Both prediction models performed well in the NECOSAD population (AUC 0.79 for the one-year model and 0.78 for the two-year model). In the UKRR populations, performance was slightly weaker (AUCs: 0.73 and 0.74). These are to be compared to the earlier external validation in a Finnish cohort (AUCs: 0.77 and 0.74). In all tested populations, our models performed better for PD than HD patients. Level of death risk (i.e., calibration) was well estimated by the one-year model in all cohorts but was somewhat overestimated by the two-year model. CONCLUSIONS Our prediction models showed good performance not only in the Finnish but in foreign KRT populations as well. Compared to the other existing models, the current models have equal or better performance and fewer variables, thus increasing models' usability. The models are easily accessible on the web. These results encourage implementing the models into clinical decision-making widely among European KRT populations.
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Affiliation(s)
- Mikko Haapio
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- * E-mail:
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Jaakko Helve
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Finnish Registry for Kidney Diseases, Helsinki, Finland
| | - Friedo W. Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Fergus Caskey
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Patrik Finne
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Finnish Registry for Kidney Diseases, Helsinki, Finland
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Luppino FS, den Hollander-Gijsman ME, Dekker FW, Bartlema KA, van Diepen M. Estimating skills level in recreational skiing: Development and validation of a practical multidimensional instrument. Scand J Med Sci Sports 2023; 33:55-63. [PMID: 36229351 PMCID: PMC10091691 DOI: 10.1111/sms.14245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 09/13/2022] [Accepted: 10/09/2022] [Indexed: 12/13/2022]
Abstract
Skiing and snowboarding are both popular recreational alpine sports, with substantial injury risk of variable severity. Although skills level has repeatedly been associated with injury risk, a validated measure to accurately estimate the actual skills level without objective assessment is missing. This study aimed to develop a practical validated instrument, to better estimate the actual skills level of recreational skiers, based on the criteria of the Dutch Skiing Federation (DSF), and covering five different skill domains. A sample of Dutch recreational skiers (n = 84) was asked to fill in a questionnaire reflecting seven, a priori chosen predictors by expert opinion, to ski downhill and to be objectively evaluated by expert assessors. The instrument was developed to have a multidimensional character and was validated according to the TRIPOD guideline (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). The sample reported an overall incorrect self-reported estimation of their skills, compared with the observed skill score. The instrument showed good calibration and underwent multiple validation methods. The estimated skills score showed to be closer to the observed scores, than self-reportage. Our study provides a practical, multidimensional, and validated instrument to estimate the actual skills level. It proved to better reflect the actual skills levels compared with self-reportage among recreational skiers.
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Affiliation(s)
| | | | - Friedo Wilhelm Dekker
- Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands
| | | | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands
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Hassan S, Ramspek CL, Ferrari B, van Diepen M, Rossio R, Knevel R, la Mura V, Artoni A, Martinelli I, Bandera A, Nobili A, Gori A, Blasi F, Canetta C, Montano N, Rosendaal FR, Peyvandi F. Corrigendum to 'External validation of risk scores to predict in-hospital mortality in patients hospitalized due to coronavirus disease 2019'. Eur J Intern Med 2022; 106:163. [PMID: 36153183 PMCID: PMC9490513 DOI: 10.1016/j.ejim.2022.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Shermarke Hassan
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Universita ` degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Barbara Ferrari
- U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Raffaella Rossio
- U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Rachel Knevel
- Department of Rheumatology, Leiden University Medical Center, Leiden, the Netherlands
| | - Vincenzo la Mura
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Universita ` degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Andrea Artoni
- Angelo Bianchi Bonomi Hemophilia and Thrombosis Centre, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ida Martinelli
- Angelo Bianchi Bonomi Hemophilia and Thrombosis Centre, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Alessandra Bandera
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Universita ` degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Infectious Disease Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Alessandro Nobili
- Department of Health Policy, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Andrea Gori
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Universita ` degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Infectious Disease Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Francesco Blasi
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Universita ` degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Respiratory Unit and Cystic Fibrosis Adult Center, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ciro Canetta
- Department of Medicine, High Care Internal Medicine Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Nicola Montano
- Medicina Generale Immunologia e Allergologia, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Flora Peyvandi
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Universita ` degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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11
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Janse RJ, Fu EL, Dahlström U, Benson L, Lindholm B, van Diepen M, Dekker FW, Lund LH, Carrero JJ, Savarese G. Use of guideline-recommended medical therapy in patients with heart failure and chronic kidney disease: from physician's prescriptions to patient's dispensations, medication adherence and persistence. Eur J Heart Fail 2022; 24:2185-2195. [PMID: 35851740 PMCID: PMC10087537 DOI: 10.1002/ejhf.2620] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/25/2022] [Accepted: 07/13/2022] [Indexed: 01/18/2023] Open
Abstract
AIM Half of heart failure (HF) patients have chronic kidney disease (CKD) complicating their pharmacological management. We evaluated physicians' and patients' patterns of use of evidence-based medical therapies in HF across CKD stages. METHODS AND RESULTS We studied HF patients with reduced (HFrEF) and mildly reduced (HFmrEF) ejection fraction enrolled in the Swedish Heart Failure Registry in 2009-2018. We investigated the likelihood of physicians to prescribe guideline-recommended therapies to patients with CKD, and of patients to fill the prescriptions within 90 days of incident HF (initiating therapy), to adhere (proportion of days covered ≥80%) and persist (continued use) on these treatments during the first year of therapy. We identified 31 668 patients with HFrEF (median age 74 years, 46% CKD). The proportions receiving a prescription for angiotensin-converting enzyme inhibitors/angiotensin receptor blockers/angiotensin receptor-neprilysin inhibitors (ACEi/ARB/ARNi) were 96%, 92%, 86%, and 68%, for estimated glomerular filtration rate (eGFR) ≥60, 45-59, 30-44, and <30 ml/min/1.73 m2 , respectively; for beta-blockers 94%, 93%, 92%, and 92%, for mineralocorticoid receptor antagonists (MRAs) 45%, 44%, 37%, 24%; and for triple therapy (combination of ACEi/ARB/ARNi + beta-blockers + MRA) 38%, 35%, 28%, and 15%. Patients with CKD were less likely to initiate these medications, and less likely to adhere to and persist on ACEi/ARB/ARNi, MRA, and triple therapy. Among stoppers, CKD patients were less likely to restart these medications. Results were consistent after multivariable adjustment and in patients with HFmrEF (n = 15 114). CONCLUSIONS Patients with HF and CKD are less likely to be prescribed and to fill prescriptions for evidence-based therapies, showing lower adherence and persistence, even at eGFR categories where these therapies are recommended and have shown efficacy in clinical trials.
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Affiliation(s)
- Roemer J Janse
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Edouard L Fu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.,Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ulf Dahlström
- Department of Cardiology and the Department of Health, Medicine and Caring Sciences, Linkoping University, Linkoping, Sweden
| | - Lina Benson
- Division of Cardiology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Bengt Lindholm
- Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Lars H Lund
- Division of Cardiology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden.,Heart, Vascular and Neuro Theme, Karolinska University Hospital, Stockholm, Sweden
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Division of Nephrology, Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Stockholm, Sweden
| | - Gianluigi Savarese
- Division of Cardiology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden.,Heart, Vascular and Neuro Theme, Karolinska University Hospital, Stockholm, Sweden
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12
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Dai L, Massy ZA, Stenvinkel P, Chesnaye NC, Larabi IA, Alvarez JC, Caskey FJ, Torino C, Porto G, Szymczak M, Krajewska M, Drechsler C, Wanner C, Jager KJ, Dekker FW, Evenepoel P, Evans M, Torp A, Iwig B, Perras B, Marx C, Drechsler C, Blaser C, Wanner C, Emde C, Krieter D, Fuchs D, Irmler E, Platen E, Schmidt-Gürtler H, Schlee H, Naujoks H, Schlee I, Cäsar S, Beige J, Röthele J, Mazur J, Hahn K, Blouin K, Neumeier K, Anding-Rost K, Schramm L, Hopf M, Wuttke N, Frischmuth N, Ichtiaris P, Kirste P, Schulz P, Aign S, Biribauer S, Manan S, Röser S, Heidenreich S, Palm S, Schwedler S, Delrieux S, Renker S, Schättel S, Stephan T, Schmiedeke T, Weinreich T, Leimbach T, Stövesand T, Bahner U, Seeger W, Cupisti A, Sagliocca A, Ferraro A, Mele A, Naticchia A, Còsaro A, Ranghino A, Stucchi A, Pignataro A, De Blasio A, Pani A, Tsalouichos A, Antonio B, Iorio BRD, Alessandra B, Abaterusso C, Somma C, D'alessandro C, Torino C, Zullo C, Pozzi C, Bergamo D, Ciurlino D, Motta D, Russo D, Favaro E, Vigotti F, Ansali F, Conte F, Cianciotta F, Giacchino F, Cappellaio F, Pizzarelli F, Greco G, Porto G, Bigatti G, Marinangeli G, Cabiddu G, Fumagalli G, Caloro G, Piccoli G, Capasso G, Gambaro G, Tognarelli G, Bonforte G, Conte G, Toscano G, Del Rosso G, Capizzi I, Baragetti I, Oldrizzi L, Gesualdo L, Biancone L, Magnano M, Ricardi M, Bari MD, Laudato M, Sirico ML, Ferraresi M, Provenzano M, Malaguti M, Palmieri N, Murrone P, Cirillo P, Dattolo P, Acampora P, Nigro R, Boero R, Scarpioni R, Sicoli R, Malandra R, Savoldi S, Bertoli S, Borrelli S, Maxia S, Maffei S, Mangano S, Cicchetti T, Rappa T, Palazzo V, De Simone W, Schrander A, van Dam B, Siegert C, Gaillard C, Beerenhout C, Verburgh C, Janmaat C, Hoogeveen E, Hoorn E, Dekker F, Boots J, Boom H, Eijgenraam JW, Kooman J, Rotmans J, Jager K, Vogt L, Raasveld M, Vervloet M, van Buren M, van Diepen M, Chesnaye N, Leurs P, Voskamp P, van Esch S, Boorsma S, Berger S, Konings C, Aydin Z, Musiała A, Szymczak A, Olczyk E, Augustyniak-Bartosik H, Miśkowiec-Wiśniewska I, Manitius J, Pondel J, Jędrzejak K, Nowańska K, Nowak Ł, Szymczak M, Durlik M, Dorota S, Nieszporek T, Heleniak Z, Jonsson A, Rogland B, Wallquist C, Vargas D, Dimény E, Sundelin F, Uhlin F, Welander G, Hernandez IB, Gröntoft KC, Stendahl M, Svensson ME, Evans M, Heimburger O, Kashioulis P, Melander S, Almquist T, Woodman A, McKeever A, Ullah A, McLaren B, Harron C, Barrett C, O'Toole C, Summersgill C, Geddes C, Glowski D, McGlynn D, Sands D, Caskey F, Roy G, Hirst G, King H, McNally H, Masri-Senghor H, Murtagh H, Rayner H, Turner J, Wilcox J, Berdeprado J, Wong J, Banda J, Jones K, Haydock L, Wilkinson L, Carmody M, Weetman M, Joinson M, Dutton M, Matthews M, Morgan N, Bleakley N, Cockwell P, Roderick P, Mason P, Kalra P, Sajith R, Chapman S, Navjee S, Crosbie S, Brown S, Tickle S, Mathavakkannan S, Kuan Y. The association between TMAO, CMPF, and clinical outcomes in advanced chronic kidney disease: results from the European QUALity (EQUAL) Study. Am J Clin Nutr 2022; 116:1842-1851. [PMID: 36166845 PMCID: PMC9761748 DOI: 10.1093/ajcn/nqac278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 08/18/2022] [Accepted: 09/24/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Trimethylamine N-oxide (TMAO), a metabolite from red meat and fish consumption, plays a role in promoting cardiovascular events. However, data regarding TMAO and its impact on clinical outcomes are inconclusive, possibly due to its undetermined dietary source. OBJECTIVES We hypothesized that circulating TMAO derived from fish intake might cause less harm compared with red meat sources by examining the concomitant level of 3-carboxy-4-methyl-5-propyl-2-furanpropionate (CMPF), a known biomarker of fish intake, and investigated the association between TMAO, CMPF, and outcomes. METHODS Patients were recruited from the European QUALity (EQUAL) Study on treatment in advanced chronic kidney disease among individuals aged ≥65 y whose estimated glomerular filtration rate (eGFR) had dropped for the first time to ≤20 mL/min per 1.73 m2 during the last 6 mo. The association between TMAO, CMPF, and outcomes including all-cause mortality and kidney replacement therapy (KRT) was assessed among 737 patients. Patients were further stratified by median cutoffs of TMAO and CMPF, suggesting high/low red meat and fish intake. RESULTS During a median of 39 mo of follow-up, 232 patients died. Higher TMAO was independently associated with an increased risk of all-cause mortality (multivariable HR: 1.46; 95% CI: 1.17, 1.83). Higher CMPF was associated with a reduced risk of both all-cause mortality (HR: 0.79; 95% CI: 0.71, 0.89) and KRT (HR: 0.80; 95% CI: 0.71, 0.90), independently of TMAO and other clinically relevant confounders. In comparison to patients with low TMAO and CMPF, patients with low TMAO and high CMPF had reduced risk of all-cause mortality (adjusted HR: 0.49; 95% CI: 0.31, 0.73), whereas those with high TMAO and high CMPF showed no association across adjusted models. CONCLUSIONS High CMPF conferred an independent role in health benefits and might even counteract the unfavorable association between TMAO and outcomes. Whether higher circulating CMPF concentrations are due to fish consumption, and/or if CMPF is a protective factor, remains to be verified.
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Affiliation(s)
- Lu Dai
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden,Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Ziad A Massy
- Division of Nephrology, Ambroise Paré University Hospital, Boulogne-Billancourt, France,Centre for Research in Epidemiology and Population Health (CESP), Inserm UMRS 1018, Team 5, University Versailles-Saint Quentin, University Paris-Saclay, Paris, France
| | - Peter Stenvinkel
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas C Chesnaye
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Islam Amine Larabi
- Laboratory of Pharmacology and Toxicology, CHU, Raymond Poincare, Garches, France,INSERM U1173, UFR des Sciences de la Santé Simone Veil, Montigny le Bretonneux, Université de Versailles-Saint-Quentin-en-Yvelines, Versailles, France
| | - Jean Claude Alvarez
- Laboratory of Pharmacology and Toxicology, CHU, Raymond Poincare, Garches, France,INSERM U1173, UFR des Sciences de la Santé Simone Veil, Montigny le Bretonneux, Université de Versailles-Saint-Quentin-en-Yvelines, Versailles, France
| | - Fergus J Caskey
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Claudia Torino
- IFC-CNR, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Gaetana Porto
- G.O.M., Bianchi Melacrino Morelli, Reggio Calabria, Italy
| | - Maciej Szymczak
- Clinical Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Magdalena Krajewska
- Clinical Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | | | - Christoph Wanner
- Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Friedo W Dekker
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Pieter Evenepoel
- Department of Microbiology, Immunology, and Transplantation, Nephrology and Renal Transplantation Research Group, KU Leuven, Leuven, Belgium,Department of Nephrology and Renal Transplantation, University Hospitals Leuven, Leuven, Belgium
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13
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Ramspek CL, Boekee R, Evans M, Heimburger O, Snead CM, Caskey FJ, Torino C, Porto G, Szymczak M, Krajewska M, Drechsler C, Wanner C, Chesnaye NC, Jager KJ, Dekker FW, Snoeijs MG, Rotmans JI, van Diepen M. Predicting Kidney Failure, Cardiovascular Disease and Death in Advanced CKD Patients. Kidney Int Rep 2022; 7:2230-2241. [PMID: 36217520 PMCID: PMC9546766 DOI: 10.1016/j.ekir.2022.07.165] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 07/18/2022] [Indexed: 11/28/2022] Open
Affiliation(s)
- Chava L. Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Correspondence: Chava L. Ramspek, Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Rosemarijn Boekee
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Marie Evans
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Olof Heimburger
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Charlotte M. Snead
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Fergus J. Caskey
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Claudia Torino
- Department of Clinical Epidemiology of Renal Diseases and Hypertension, Consiglio Nazionale della Ricerche-Istituto di Fisiologia Clinica, Reggio Calabria, Italy
| | - Gaetana Porto
- Grande Ospedale Metropolitano, Bianchi Melacrino Morelli, Reggio Calabria, Italy
| | - Maciej Szymczak
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Magdalena Krajewska
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Christiane Drechsler
- Division of Nephrology, Department of Internal Medicine, University Hospital Wurzburg, Wurzburg, Germany
| | - Christoph Wanner
- Division of Nephrology, University Hospital of Wurzburg, Wurzburg, Germany
| | - Nicholas C. Chesnaye
- Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Kitty J. Jager
- Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Friedo W. Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maarten G.J. Snoeijs
- Department of Vascular Surgery, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Joris I. Rotmans
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
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14
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Hassan S, Ramspek CL, Ferrari B, van Diepen M, Rossio R, Knevel R, la Mura V, Artoni A, Martinelli I, Bandera A, Nobili A, Gori A, Blasi F, Canetta C, Montano N, Rosendaal FR, Peyvandi F. External validation of risk scores to predict in-hospital mortality in patients hospitalized due to coronavirus disease 2019. Eur J Intern Med 2022; 102:63-71. [PMID: 35697562 PMCID: PMC9174149 DOI: 10.1016/j.ejim.2022.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/19/2022] [Accepted: 06/06/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist medical staff in treatment and allocating limited resources. AIMS To externally validate two promising previously published risk scores that predict in-hospital mortality among hospitalized COVID-19 patients. METHODS Two prospective cohorts were available; a cohort of 1028 patients admitted to one of nine hospitals in Lombardy, Italy (the Lombardy cohort) and a cohort of 432 patients admitted to a hospital in Leiden, the Netherlands (the Leiden cohort). The endpoint was in-hospital mortality. All patients were adult and tested COVID-19 PCR-positive. Model discrimination and calibration were assessed. RESULTS The C-statistic of the 4C mortality score was good in the Lombardy cohort (0.85, 95CI: 0.82-0.89) and in the Leiden cohort (0.87, 95CI: 0.80-0.94). Model calibration was acceptable in the Lombardy cohort but poor in the Leiden cohort due to the model systematically overpredicting the mortality risk for all patients. The C-statistic of the CURB-65 score was good in the Lombardy cohort (0.80, 95CI: 0.75-0.85) and in the Leiden cohort (0.82, 95CI: 0.76-0.88). The mortality rate in the CURB-65 development cohort was much lower than the mortality rate in the Lombardy cohort. A similar but less pronounced trend was found for patients in the Leiden cohort. CONCLUSION Although performances did not differ greatly, the 4C mortality score showed the best performance. However, because of quickly changing circumstances, model recalibration may be necessary before using the 4C mortality score.
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Affiliation(s)
- Shermarke Hassan
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Barbara Ferrari
- U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Raffaella Rossio
- U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Rachel Knevel
- Department of Rheumatology, Leiden University Medical Center, Leiden, the Netherlands
| | - Vincenzo la Mura
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Andrea Artoni
- Angelo Bianchi Bonomi Hemophilia and Thrombosis Centre, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ida Martinelli
- Angelo Bianchi Bonomi Hemophilia and Thrombosis Centre, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Alessandra Bandera
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Infectious Disease Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Alessandro Nobili
- Department of Health Policy, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Andrea Gori
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Infectious Disease Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Francesco Blasi
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; Respiratory Unit and Cystic Fibrosis Adult Center, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ciro Canetta
- Department of Medicine, High Care Internal Medicine Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Nicola Montano
- Medicina Generale Immunologia e Allergologia, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Flora Peyvandi
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Via Francesco Sforza 35, Milan 20122, Italy; U.O.C. Medicina Generale Emostasi e Trombosi, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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15
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van der Endt VHW, Milders J, Penning de Vries BBL, Trines SA, Groenwold RHH, Dekkers OM, Trevisan M, Carrero JJ, van Diepen M, Dekker FW, de Jong Y. Comprehensive comparison of stroke risk score performance: a systematic review and meta-analysis among 6 267 728 patients with atrial fibrillation. Europace 2022; 24:1739-1753. [PMID: 35894866 PMCID: PMC9681133 DOI: 10.1093/europace/euac096] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 05/24/2022] [Indexed: 12/15/2022] Open
Abstract
AIMS Multiple risk scores to predict ischaemic stroke (IS) in patients with atrial fibrillation (AF) have been developed. This study aims to systematically review these scores, their validations and updates, assess their methodological quality, and calculate pooled estimates of the predictive performance. METHODS AND RESULTS We searched PubMed and Web of Science for studies developing, validating, or updating risk scores for IS in AF patients. Methodological quality was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). To assess discrimination, pooled c-statistics were calculated using random-effects meta-analysis. We identified 19 scores, which were validated and updated once or more in 70 and 40 studies, respectively, including 329 validations and 76 updates-nearly all on the CHA2DS2-VASc and CHADS2. Pooled c-statistics were calculated among 6 267 728 patients and 359 373 events of IS. For the CHA2DS2-VASc and CHADS2, pooled c-statistics were 0.644 [95% confidence interval (CI) 0.635-0.653] and 0.658 (0.644-0.672), respectively. Better discriminatory abilities were found in the newer risk scores, with the modified-CHADS2 demonstrating the best discrimination [c-statistic 0.715 (0.674-0.754)]. Updates were found for the CHA2DS2-VASc and CHADS2 only, showing improved discrimination. Calibration was reasonable but available for only 17 studies. The PROBAST indicated a risk of methodological bias in all studies. CONCLUSION Nineteen risk scores and 76 updates are available to predict IS in patients with AF. The guideline-endorsed CHA2DS2-VASc shows inferior discriminative abilities compared with newer scores. Additional external validations and data on calibration are required before considering the newer scores in clinical practice. CLINICAL TRIAL REGISTRATION ID CRD4202161247 (PROSPERO).
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Affiliation(s)
| | - Jet Milders
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands
| | - Bas B L Penning de Vries
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands
| | - Serge A Trines
- Department of Cardiology, Willem Einthoven Center of Arrhythmia Research and Management, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Rolf H H Groenwold
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands
| | - Olaf M Dekkers
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands
| | - Marco Trevisan
- Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Juan J Carrero
- Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands
| | - Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2333 ZA Leiden, The Netherlands,Department of Internal Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
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Noordzij M, van Diepen M, Caskey FC, Jager KJ. Erratum to: Relative risk versus absolute risk: one cannot be interpreted without the other. Nephrol Dial Transplant 2022; 37:1001. [PMID: 35134977 DOI: 10.1093/ndt/gfab291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Marlies Noordzij
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands
| | | | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
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Janse RJ, Fu EL, Clase CM, Tomlinson L, Lindholm B, van Diepen M, Dekker FW, Carrero JJ. Stopping Versus Continuing Renin-Angiotensin System Inhibitors After Acute Kidney Injury and Adverse Clinical Outcomes; An Observational Study From Routine Care Data. Clin Kidney J 2022; 15:1109-1119. [PMID: 35664269 PMCID: PMC9155253 DOI: 10.1093/ckj/sfac003] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Indexed: 11/18/2022] Open
Abstract
Background The risk–benefit ratio of continuing with renin–angiotensin system inhibitors (RASi)
after an episode of acute kidney injury (AKI) is unclear. While stopping RASi may
prevent recurrent AKI or hyperkalaemia, it may deprive patients of the cardiovascular
benefits of using RASi. Methods We analysed outcomes of long-term RASi users experiencing AKI (stage 2 or 3, or
clinically coded) during hospitalization in Stockholm and Sweden during 2007–18. We
compared stopping RASi within 3 months after discharge with continuing RASi. The primary
study outcome was the composite of all-cause mortality, myocardial infarction (MI) and
stroke. Recurrent AKI was our secondary outcome and we considered hyperkalaemia as a
positive control outcome. Propensity score overlap weighted Cox models were used to
estimate hazard ratios (HRs), balancing 75 confounders. Weighted absolute risk
differences (ARDs) were also determined. Results We included 10 165 individuals, of whom 4429 stopped and 5736 continued RASi, with a
median follow-up of 2.3 years. The median age was 78 years; 45% were women and median
kidney function before the index episode of AKI was 55 mL/min/1.73 m2. After
weighting, those who stopped had an increased risk [HR, 95% confidence interval (CI)] of
the composite of death, MI and stroke [1.13, 1.07–1.19; ARD 3.7, 95% CI 2.6–4.8]
compared with those who continued, a similar risk of recurrent AKI (0.94, 0.84–1.05) and
a decreased risk of hyperkalaemia (0.79, 0.71–0.88). Discussion Stopping RASi use among survivors of moderate-to-severe AKI was associated with a
similar risk of recurrent AKI, but higher risk of the composite of death, MI and
stroke.
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Affiliation(s)
- Roemer J Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Catherine M Clase
- Department of Medicine and Health Research Methods, Evidence and Impact, McMaster University, Ontario, Canada
| | - Laurie Tomlinson
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Bengt Lindholm
- Divisions of Renal Medicine and Baxter Novum, Karolinska Institutet, Stockholm, Sweden
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
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18
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Ramspek CL, Teece L, Snell KIE, Evans M, Riley RD, van Smeden M, van Geloven N, van Diepen M. Lessons learnt when accounting for competing events in the external validation of time-to-event prognostic models. Int J Epidemiol 2021; 51:615-625. [PMID: 34919691 PMCID: PMC9082803 DOI: 10.1093/ije/dyab256] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 11/24/2021] [Indexed: 12/22/2022] Open
Abstract
Background External validation of prognostic models is necessary to assess the accuracy and generalizability of the model to new patients. If models are validated in a setting in which competing events occur, these competing risks should be accounted for when comparing predicted risks to observed outcomes. Methods We discuss existing measures of calibration and discrimination that incorporate competing events for time-to-event models. These methods are illustrated using a clinical-data example concerning the prediction of kidney failure in a population with advanced chronic kidney disease (CKD), using the guideline-recommended Kidney Failure Risk Equation (KFRE). The KFRE was developed using Cox regression in a diverse population of CKD patients and has been proposed for use in patients with advanced CKD in whom death is a frequent competing event. Results When validating the 5-year KFRE with methods that account for competing events, it becomes apparent that the 5-year KFRE considerably overestimates the real-world risk of kidney failure. The absolute overestimation was 10%age points on average and 29%age points in older high-risk patients. Conclusions It is crucial that competing events are accounted for during external validation to provide a more reliable assessment the performance of a model in clinical settings in which competing risks occur.
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Affiliation(s)
- Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Lucy Teece
- Biostatistics Research Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Kym I E Snell
- Centre for Prognosis Research, School of Medicine, Keele University, Keele, UK
| | - Marie Evans
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institutet and Karolinska University hospital, Stockholm, Sweden
| | - Richard D Riley
- Centre for Prognosis Research, School of Medicine, Keele University, Keele, UK
| | - Maarten van Smeden
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Nan van Geloven
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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19
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Eveleens Maarse BC, Chesnaye NC, Schouten R, Michels WM, Bos WJW, Szymczak M, Krajewska M, Evans M, Heimburger O, Caskey FJ, Wanner C, Jager KJ, Dekker FW, Meuleman Y, Schneider A, Torp A, Iwig B, Perras B, Marx C, Drechsler C, Blaser C, Wanner C, Emde C, Krieter D, Fuchs D, Irmler E, Platen E, Schmidt-Gürtler H, Schlee H, Naujoks H, Schlee I, Cäsar S, Beige J, Röthele J, Mazur J, Hahn K, Blouin K, Neumeier K, Anding-Rost K, Schramm L, Hopf M, Wuttke N, Frischmuth N, Ichtiaris P, Kirste P, Schulz P, Aign S, Biribauer S, Manan S, Röser S, Heidenreich S, Palm S, Schwedler S, Delrieux S, Renker S, Schättel S, Stephan T, Schmiedeke T, Weinreich T, Leimbach T, Stövesand T, Bahner U, Seeger W, Cupisti A, Sagliocca A, Ferraro A, Mele A, Naticchia A, Còsaro A, Ranghino A, Stucchi A, Pignataro A, De Blasio A, Pani A, Tsalouichos A, Antonio B, Di Iorio BR, Alessandra B, Abaterusso C, Somma C, D'alessandro C, Torino C, Zullo C, Pozzi C, Bergamo D, Ciurlino D, Motta D, Russo D, Favaro E, Vigotti F, Ansali F, Conte F, Cianciotta F, Giacchino F, Cappellaio F, Pizzarelli F, Greco G, Porto G, Bigatti G, Marinangeli G, Cabiddu G, Fumagalli G, Caloro G, Piccoli G, Capasso G, Gambaro G, Tognarelli G, Bonforte G, Conte G, Toscano G, Del Rosso G, Capizzi I, Baragetti I, Oldrizzi L, Gesualdo L, Biancone L, Magnano M, Ricardi M, Di Bari M, Laudato M, Sirico ML, Ferraresi M, Postorino M, Provenzano M, Malaguti M, Palmieri N, Murrone P, Cirillo P, Dattolo P, Acampora P, Nigro R, Boero R, Scarpioni R, Sicoli R, Malandra R, Savoldi S, Bertoli S, Borrelli S, Maxia S, Maffei S, Mangano S, Cicchetti T, Rappa T, Palazzo V, De Simone W, Schrander A, van Dam B, Siegert C, Gaillard C, Beerenhout C, Verburgh C, Janmaat C, Hoogeveen E, Hoorn E, Dekker F, Boots J, Boom H, Eijgenraam JW, Kooman J, Rotmans J, Jager K, Vogt L, Raasveld M, Vervloet M, van Buren M, van Diepen M, Chesnaye N, Leurs P, Voskamp P, Blankestijn P, van Esch S, Boorsma S, Berger S, Konings C, Aydin Z, Musiała A, Szymczak A, Olczyk E, Augustyniak-Bartosik H, Miśkowiec-Wiśniewska I, Manitius J, Pondel J, Jędrzejak K, Nowańska K, Nowak Ł, Szymczak M, Durlik M, Dorota S, Nieszporek T, Heleniak Z, Jonsson A, Blom AL, Rogland B, Wallquist C, Vargas D, Dimény E, Sundelin F, Uhlin F, Welander G, Hernandez IB, Gröntoft KC, Stendahl M, Svensson M, Evans M, Heimburger O, Kashioulis P, Melander S, Almquist T, Jensen U, Woodman A, McKeever A, Ullah A, McLaren B, Harron C, Barrett C, O'Toole C, Summersgill C, Geddes C, Glowski D, McGlynn D, Sands D, Caskey F, Roy G, Hirst G, King H, McNally H, Masri-Senghor H, Murtagh H, Rayner H, Turner J, Wilcox J, Berdeprado J, Wong J, Banda J, Jones K, Haydock L, Wilkinson L, Carmody M, Weetman M, Joinson M, Dutton M, Matthews M, Morgan N, Bleakley N, Cockwell P, Roderick P, Mason P, Kalra P, Sajith R, Chapman S, Navjee S, Crosbie S, Brown S, Tickle S, Mathavakkannan S, Kuan Y. Associations between depressive symptoms and disease progression in older patients with chronic kidney disease: results of the EQUAL study. Clin Kidney J 2021; 15:786-797. [PMID: 35371440 PMCID: PMC8967670 DOI: 10.1093/ckj/sfab261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Indexed: 11/13/2022] Open
Abstract
Background Depressive symptoms are associated with adverse clinical outcomes in patients with end-stage kidney disease; however, few small studies have examined this association in patients with earlier phases of chronic kidney disease (CKD). We studied associations between baseline depressive symptoms and clinical outcomes in older patients with advanced CKD and examined whether these associations differed depending on sex. Methods CKD patients (≥65 years; estimated glomerular filtration rate ≤20 mL/min/1.73 m2) were included from a European multicentre prospective cohort between 2012 and 2019. Depressive symptoms were measured by the five-item Mental Health Inventory (cut-off ≤70; 0–100 scale). Cox proportional hazard analysis was used to study associations between depressive symptoms and time to dialysis initiation, all-cause mortality and these outcomes combined. A joint model was used to study the association between depressive symptoms and kidney function over time. Analyses were adjusted for potential baseline confounders. Results Overall kidney function decline in 1326 patients was –0.12 mL/min/1.73 m2/month. A total of 515 patients showed depressive symptoms. No significant association was found between depressive symptoms and kidney function over time (P = 0.08). Unlike women, men with depressive symptoms had an increased mortality rate compared with those without symptoms [adjusted hazard ratio 1.41 (95% confidence interval 1.03–1.93)]. Depressive symptoms were not significantly associated with a higher hazard of dialysis initiation, or with the combined outcome (i.e. dialysis initiation and all-cause mortality). Conclusions There was no significant association between depressive symptoms at baseline and decline in kidney function over time in older patients with advanced CKD. Depressive symptoms at baseline were associated with a higher mortality rate in men.
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Affiliation(s)
| | - Nicholas C Chesnaye
- ERA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Robbert Schouten
- Department of Nephrology, OLVG Hospital, Amsterdam, The Netherlands
| | - Wieneke M Michels
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Willem Jan W Bos
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Sint Antonius Hospital, Nieuwegein, The Netherlands
| | - Maciej Szymczak
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Magdalena Krajewska
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Marie Evans
- Department of Clinical Sciences Intervention and Technology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Olof Heimburger
- Department of Clinical Sciences Intervention and Technology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Fergus J Caskey
- Renal Unit, Southmead Hospital, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Christoph Wanner
- Department of Medicine, Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Kitty J Jager
- ERA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Yvette Meuleman
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Massy ZA, Chesnaye NC, Larabi IA, Dekker FW, Evans M, Caskey FJ, Torino C, Porto G, Szymczak M, Drechsler C, Wanner C, Jager KJ, Alvarez JC, Schneider A, Torp A, Iwig B, Perras B, Marx C, Drechsler C, Blaser C, Wanner C, Emde C, Krieter D, Fuchs D, Irmler E, Platen E, Schmidt-Gürtler H, Schlee H, Naujoks H, Schlee I, Cäsar S, Beige J, Röthele J, Mazur J, Hahn K, Blouin K, Neumeier K, Anding-Rost K, Schramm L, Hopf M, Wuttke N, Frischmuth N, Ichtiaris P, Kirste P, Schulz P, Aign S, Biribauer S, Manan S, Röser S, Heidenreich S, Palm S, Schwedler S, Delrieux S, Renker S, Schättel S, Stephan T, Schmiedeke T, Weinreich T, Leimbach T, Stövesand T, Bahner U, Seeger W, Cupisti A, Sagliocca A, Ferraro A, Mele A, Naticchia A, Còsaro A, Ranghino A, Stucchi A, Pignataro A, De Blasio A, Pani A, Tsalouichos A, Bellasi A, Di Iorio BR, Butti A, Abaterusso C, Somma C, D'alessandro C, Torino C, Zullo C, Pozzi C, Bergamo D, Ciurlino D, Motta D, Russo D, Favaro E, Vigotti F, Ansali F, Conte F, Cianciotta F, Giacchino F, Cappellaio F, Pizzarelli F, Greco G, Porto G, Bigatti G, Marinangeli G, Cabiddu G, Fumagalli G, Caloro G, Piccoli G, Capasso G, Gambaro G, Tognarelli G, Bonforte G, Conte G, Toscano G, Del Rosso G, Capizzi I, Baragetti I, Oldrizzi L, Gesualdo L, Biancone L, Magnano M, Ricardi M, Di Bari M, Laudato M, Sirico ML, Ferraresi M, Provenzano M, Malaguti M, Palmieri N, Murrone P, Cirillo P, Dattolo P, Acampora P, Nigro R, Boero R, Scarpioni R, Sicoli R, Malandra R, Savoldi S, Bertoli S, Borrelli S, Maxia S, Maffei S, Mangano S, Cicchetti T, Rappa T, Palazzo V, De Simone W, Schrander A, van Dam B, Siegert C, Gaillard C, Beerenhout C, Verburgh C, Janmaat C, Hoogeveen E, Hoorn E, Dekker F, Boots J, Boom H, Eijgenraam JW, Kooman J, Rotmans J, Jager K, Vogt L, Raasveld M, Vervloet M, van Buren M, van Diepen M, Chesnaye N, Leurs P, Voskamp P, Blankestijn P, van Esch S, Boorsma S, Berger S, Konings C, Aydin Z, Musiała A, Szymczak A, Olczyk E, Augustyniak-Bartosik H, Miśkowiec-Wiśniewska I, Manitius J, Pondel J, Jędrzejak K, Nowańska K, Nowak Ł, Szymczak M, Durlik M, Dorota S, Nieszporek T, Heleniak Z, Jonsson A, Blom AL, Rogland B, Wallquist C, Vargas D, Dimény E, Sundelin F, Uhlin F, Welander G, Hernandez IB, Gröntoft KC, Stendahl M, Svensson M, Evans M, Heimburger O, Kashioulis P, Melander S, Almquist T, Jensen U, Woodman A, McKeever A, Ullah A, McLaren B, Harron C, Barrett C, O'Toole C, Summersgill C, Geddes C, Glowski D, McGlynn D, Sands D, Caskey F, Roy G, Hirst G, King H, McNally H, Masri-Senghor H, Murtagh H, Rayner H, Turner J, Wilcox J, Berdeprado J, Wong J, Banda J, Jones K, Haydock L, Wilkinson L, Carmody M, Weetman M, Joinson M, Dutton M, Matthews M, Morgan N, Bleakley N, Cockwell P, Roderick P, Mason P, Kalra P, Sajith R, Chapman S, Navjee S, Crosbie S, Brown S, Tickle S, Mathavakkannan S, Kuan Y. The relationship between uremic toxins and symptoms in older men and women with advanced chronic kidney disease. Clin Kidney J 2021; 15:798-807. [PMID: 35371454 PMCID: PMC8967681 DOI: 10.1093/ckj/sfab262] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Indexed: 11/30/2022] Open
Abstract
Background Patients with stage 4/5 chronic kidney disease (CKD) suffer from various symptoms. The retention of uremic solutes is thought to be associated with those symptoms. However, there are relatively few rigorous studies on the potential links between uremic toxins and symptoms in patients with CKD. Methods The EQUAL study is an ongoing observational cohort study of non-dialyzed patients with stage 4/5 CKD. EQUAL patients from Germany, Poland, Sweden and the UK were included in the present study (n = 795). Data and symptom self-report questionnaires were collected between April 2012 and September 2020. Baseline uric acid and parathyroid hormone and 10 uremic toxins were quantified. We tested the association between uremic toxins and symptoms and adjusted P-values for multiple testing. Results Symptoms were more frequent in women than in men with stage 4/5 CKD, while levels of various uremic toxins were higher in men. Only trimethylamine N-oxide (TMAO; positive association with fatigue), p-cresyl sulfate (PCS) with constipation and 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid (negative association with shortness of breath) demonstrated moderately strong associations with symptoms in adjusted analyses. The association of phenylacetylglutamine with shortness of breath was consistent in both sexes, although it only reached statistical significance in the full population. In contrast, TMAO (fatigue) and PCS and phenylacetylglutamine (constipation) were only associated with symptoms in men, who presented higher serum levels than women. Conclusion Only a limited number of toxins were associated with symptoms in persons with stage 4/5 CKD. Other uremic toxins, uremia-related factors or psychosocial factors not yet explored might contribute to symptom burden.
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Affiliation(s)
- Ziad A Massy
- Centre for Research in Epidemiology and Population Health (CESP), Inserm UMRS 1018, team5, France
- University Versailles-Saint Quentin, University Paris-Saclay, Villejuif 91190, France
- Department of Nephrology, CHU Ambroise Paré, APHP, 92104 Boulogne Billancourt Cedex, France
| | - Nicholas C Chesnaye
- ERA Registry, Dept of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health research Institute, Amsterdam, The Netherlands
| | - Islam Amine Larabi
- Laboratory of Pharmacology and Toxicology, CHU, Raymond Poincare, Garches, and INSERM U‑1173, UFR des Sciences de la Santé Simone Veil, Montigny le Bretonneux, Université de Versailles-Saint-Quentin-en-Yvelines, Versailles, France
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie Evans
- Renal unit, department of Clinical Intervention and technology (CLINTEC), Karolinska Institutet and Karolinska University hospital, Stockholm, Sweden
| | - Fergus J Caskey
- Population Health Sciences, Bristol Medical School, University of Bristol, UK
| | - Claudia Torino
- IFC-CNR, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Gaetana Porto
- G.O.M., Bianchi Melacrino Morelli, Reggio Calabria, Italy
| | - Maciej Szymczak
- Dept of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | | | - Christoph Wanner
- Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Kitty J Jager
- ERA Registry, Dept of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health research Institute, Amsterdam, The Netherlands
| | - Jean Claude Alvarez
- Laboratory of Pharmacology and Toxicology, CHU, Raymond Poincare, Garches, and INSERM U‑1173, UFR des Sciences de la Santé Simone Veil, Montigny le Bretonneux, Université de Versailles-Saint-Quentin-en-Yvelines, Versailles, France
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Fu EL, Evans M, Carrero JJ, Putter H, Clase CM, Caskey FJ, Szymczak M, Torino C, Chesnaye NC, Jager KJ, Wanner C, Dekker FW, van Diepen M. Timing of dialysis initiation to reduce mortality and cardiovascular events in advanced chronic kidney disease: nationwide cohort study. BMJ 2021; 375:e066306. [PMID: 34844936 PMCID: PMC8628190 DOI: 10.1136/bmj-2021-066306] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/05/2021] [Indexed: 12/02/2022]
Abstract
OBJECTIVE To identify the optimal estimated glomerular filtration rate (eGFR) at which to initiate dialysis in people with advanced chronic kidney disease. DESIGN Nationwide observational cohort study. SETTING National Swedish Renal Registry of patients referred to nephrologists. PARTICIPANTS Patients had a baseline eGFR between 10 and 20 mL/min/1.73 m2 and were included between 1 January 2007 and 31 December 2016, with follow-up until 1 June 2017. MAIN OUTCOME MEASURES The strict design criteria of a clinical trial were mimicked by using the cloning, censoring, and weighting method to eliminate immortal time bias, lead time bias, and survivor bias. A dynamic marginal structural model was used to estimate adjusted hazard ratios and absolute risks for five year all cause mortality and major adverse cardiovascular events (composite of cardiovascular death, non-fatal myocardial infarction, or non-fatal stroke) for 15 dialysis initiation strategies with eGFR values between 4 and 19 mL/min/1.73 m2 in increments of 1 mL/min/1.73 m2. An eGFR between 6 and 7 mL/min/1.73 m2 (eGFR6-7) was taken as the reference. RESULTS Among 10 290 incident patients with advanced chronic kidney disease (median age 73 years; 3739 (36%) women; median eGFR 16.8 mL/min/1.73 m2), 3822 started dialysis, 4160 died, and 2446 had a major adverse cardiovascular event. A parabolic relation was observed for mortality, with the lowest risk for eGFR15-16. Compared with dialysis initiation at eGFR6-7, initiation at eGFR15-16 was associated with a 5.1% (95% confidence interval 2.5% to 6.9%) lower absolute five year mortality risk and 2.9% (0.2% to 5.5%) lower risk of a major adverse cardiovascular event, corresponding to hazard ratios of 0.89 (95% confidence interval 0.87 to 0.92) and 0.94 (0.91 to 0.98), respectively. This 5.1% absolute risk difference corresponded to a mean postponement of death of 1.6 months over five years of follow-up. However, dialysis would need to be started four years earlier. When emulating the intended strategies of the Initiating Dialysis Early and Late (IDEAL) trial (eGFR10-14 v eGFR5-7) and the achieved eGFRs in IDEAL (eGFR7-10 v eGFR5-7), hazard ratios for all cause mortality were 0.96 (0.94 to 0.99) and 0.97 (0.94 to 1.00), respectively, which are congruent with the findings of the randomised IDEAL trial. CONCLUSIONS Very early initiation of dialysis was associated with a modest reduction in mortality and cardiovascular events. For most patients, such a reduction may not outweigh the burden of a substantially longer period spent on dialysis.
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Affiliation(s)
- Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | - Marie Evans
- Department of Clinical Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hein Putter
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Catherine M Clase
- Department of Medicine and Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
| | - Fergus J Caskey
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Maciej Szymczak
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Claudia Torino
- IFC-CNR, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Nicholas C Chesnaye
- ERA-EDTA Registry, Department of Medical Informatics, Academic University Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, Netherlands
| | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Academic University Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, Netherlands
| | - Christoph Wanner
- Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands
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22
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Janse RJ, Hoekstra T, Jager KJ, Zoccali C, Tripepi G, Dekker FW, van Diepen M. Conducting correlation analysis: important limitations and pitfalls. Clin Kidney J 2021; 14:2332-2337. [PMID: 34754428 PMCID: PMC8572982 DOI: 10.1093/ckj/sfab085] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 04/20/2021] [Indexed: 11/22/2022] Open
Abstract
The correlation coefficient is a statistical measure often used in studies to show an association between variables or to look at the agreement between two methods. In this paper, we will discuss not only the basics of the correlation coefficient, such as its assumptions and how it is interpreted, but also important limitations when using the correlation coefficient, such as its assumption of a linear association and its sensitivity to the range of observations. We will also discuss why the coefficient is invalid when used to assess agreement of two methods aiming to measure a certain value, and discuss better alternatives, such as the intraclass coefficient and Bland-Altman's limits of agreement. The concepts discussed in this paper are supported with examples from literature in the field of nephrology.
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Affiliation(s)
- Roemer J Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tiny Hoekstra
- Department of Nephrology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Carmine Zoccali
- CNR-IFC, Center of Clinical Physiology, Clinical Epidemiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Giovanni Tripepi
- CNR-IFC, Center of Clinical Physiology, Clinical Epidemiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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23
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de Jong Y, van der Willik EM, Milders J, Meuleman Y, Morton RL, Dekker FW, van Diepen M. Person centred care provision and care planning in chronic kidney disease: which outcomes matter? A systematic review and thematic synthesis of qualitative studies : Care planning in CKD: which outcomes matter? BMC Nephrol 2021; 22:309. [PMID: 34517825 PMCID: PMC8438879 DOI: 10.1186/s12882-021-02489-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 07/29/2021] [Indexed: 11/23/2022] Open
Abstract
RATIONALE & OBJECTIVE Explore priorities related to outcomes and barriers of adults with chronic kidney disease (CKD) regarding person centred care and care planning. STUDY DESIGN Systematic review of qualitative studies. SEARCH STRATEGY & SOURCES In July 2018 six bibliographic databases, and reference lists of included articles were searched for qualitative studies that included adults with CKD stages 1-5, not on dialysis or conservative management, without a previous kidney transplantation. ANALYTICAL APPROACH Three independent reviewers extracted and inductively coded data using thematic synthesis. Reporting quality was assessed using the COREQ and the review reported according to PRISMA and ENTREQ statements. RESULTS Forty-six studies involving 1493 participants were eligible. The period after diagnosis of CKD is characterized by feelings of uncertainty, social isolation, financial burden, resentment and fear of the unknown. Patients show interest in ways to return to normality and remain in control of their health in order to avoid further deterioration of kidney function. However, necessary information is often unavailable or incomprehensible. Although patients and healthcare professionals share the predominant interest of whether or not dialysis or transplantation is necessary, patients value many more outcomes that are often unrecognized by their healthcare professionals. We identified 4 themes with 6 subthemes that summarize these findings: 'pursuing normality and control' ('pursuing normality'; 'a search for knowledge'); 'prioritizing outcomes' ('reaching kidney failure'; 'experienced health'; 'social life'; 'work and economic productivity'); 'predicting the future'; and 'realising what matters'. Reporting quality was moderate for most included studies. LIMITATIONS Exclusion of non-English articles. CONCLUSIONS The realisation that patients' priorities do not match those of the healthcare professionals, in combination with the prognostic ambiguity, confirms fatalistic perceptions of not being in control when living with CKD. These insights may contribute to greater understanding of patients' perspectives and a more person-centred approach in healthcare prioritization and care planning within CKD care.
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Affiliation(s)
- Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Centre, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands.
- Department of Internal Medicine, Leiden University Medical Centre, Leiden, The Netherlands.
| | - Esmee M van der Willik
- Department of Clinical Epidemiology, Leiden University Medical Centre, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Jet Milders
- Department of Clinical Epidemiology, Leiden University Medical Centre, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Yvette Meuleman
- Department of Clinical Epidemiology, Leiden University Medical Centre, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Rachael L Morton
- NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Centre, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Centre, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
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24
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Ommering BWC, van Blankenstein FM, van Diepen M, Dekker FW. Academic Success Experiences: Promoting Research Motivation andSelf-Efficacy Beliefs among Medical Students. Teach Learn Med 2021; 33:423-433. [PMID: 33632042 DOI: 10.1080/10401334.2021.1877713] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
THEORY Medicine is facing a physician-scientist shortage. Medical training could contribute to developing physician-scientists by stimulating student research involvement, as previous studies showed this is related to research involvement in professional practice. Motivation for research and research self-efficacy beliefs are related to student research involvement. Based on social cognitive theory, success experiences in doing research may enhance research motivation and self-efficacy beliefs. However, the role and type of success experiences in promoting research self-efficacy beliefs and motivation especially early in medical training has not yet been investigated. Therefore, we examined if academic success experiences within an undergraduate course in academic and scientific skills increased research motivation and self-efficacy beliefs among medical students. Furthermore, type of success experience was taken into account by looking at the effects of academic success experiences within standard (i.e., exam) versus authentic (i.e., research report and oral presentation) assessments. HYPOTHESES It was hypothesized that academic success experiences increase intrinsic motivation for research and self-efficacy beliefs. Furthermore, we hypothesized that authentic assessments influence intrinsic motivation for research and self-efficacy beliefs to a larger degree than standard assessments, as the authentic assessments mirror real-world practices of researchers. METHOD First-year undergraduate medicine students followed a course in academic and scientific skills in which they conducted research individually. Their academic success experiences were operationalized as their grades on two authentic research assessments (written report and oral presentation) and one less authentic assessment (written exam). We surveyed students before the course when entering medical school (i.e., baseline measure) and 1 year after the course in their 2nd year (i.e., postmeasure). Both the baseline and postmeasure surveys measured intrinsic motivation for research, extrinsic motivation for research, and research self-efficacy beliefs. Linear regression analyses were used to examine the relationship between academic success experiences and intrinsic motivation for research, extrinsic motivation for research, and research self-efficacy beliefs on the postmeasure. We adjusted for prior research motivation and self-efficacy beliefs at baseline. Therefore, this adjusted effect can be interpreted as an increase or decrease in motivation. In addition, we adjusted for age, gender, and grade point average (GPA) of the first 4 months, as these variables were seen as possible confounders. RESULTS In total, 243 of 275 students participated (88.4%). Academic success experiences in writing and presenting research were related to a significant increase in intrinsic motivation for research. After adjusting for prior GPA, only the effect of presenting remained. Experiencing success in presenting enhanced research self-efficacy beliefs, also after adjusting for prior GPA. Higher grades on the exam did not affect intrinsic motivation for research or research self-efficacy significantly. Also, none of the success experiences influenced extrinsic motivation for research. CONCLUSIONS Academic success experiences on authentic research tasks, especially presenting research, may be a good way to enhance intrinsic motivation for research and research self-efficacy beliefs. In turn, research motivation and self-efficacy beliefs promote research involvement, which is a first step in the physician-scientist pipeline. Furthermore, this study established the applicability of the social cognitive theory in a research context within the medical domain.
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Affiliation(s)
- Belinda W C Ommering
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
| | - Floris M van Blankenstein
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
- Department of Higher Education, Leiden University Graduate School of Teaching, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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25
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de Jong Y, Ramspek CL, Zoccali C, Jager KJ, Dekker FW, van Diepen M. Appraising prediction research: a guide and meta-review on bias and applicability assessment using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Nephrology (Carlton) 2021; 26:939-947. [PMID: 34138495 PMCID: PMC9291738 DOI: 10.1111/nep.13913] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 06/04/2021] [Indexed: 12/23/2022]
Abstract
Over the past few years, a large number of prediction models have been published, often of poor methodological quality. Seemingly objective and straightforward, prediction models provide a risk estimate for the outcome of interest, usually based on readily available clinical information. Yet, using models of substandard methodological rigour, especially without external validation, may result in incorrect risk estimates and consequently misclassification. To assess and combat bias in prediction research the prediction model risk of bias assessment tool (PROBAST) was published in 2019. This risk of bias (ROB) tool includes four domains and 20 signalling questions highlighting methodological flaws, and provides guidance in assessing the applicability of the model. In this paper, the PROBAST will be discussed, along with an in‐depth review of two commonly encountered pitfalls in prediction modelling that may induce bias: overfitting and composite endpoints. We illustrate the prevalence of potential bias in prediction models with a meta‐review of 50 systematic reviews that used the PROBAST to appraise their included studies, thus including 1510 different studies on 2104 prediction models. All domains showed an unclear or high ROB; these results were markedly stable over time, highlighting the urgent need for attention on bias in prediction research. This article aims to do just that by providing (1) the clinician with tools to evaluate the (methodological) quality of a clinical prediction model, (2) the researcher working on a review with methods to appraise the included models, and (3) the researcher developing a model with suggestions to improve model quality. Most published prediction models have limited clinical uptake, are not externally validated and come with methodological issues. The PROBAST (Prediction model Risk Of Bias ASssessment Tool) guides the researcher writing a review, or the clinician interested in a model for risk calculation in a clinical setting. This review examines the aspects of bias in prediction research, and provides information on the prevalence of bias in published models.
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Affiliation(s)
- Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Carmine Zoccali
- Renal Research Institute, New York, USA.,Associazione Ipertensione Nefrologia Trapianto Renale (IPNET) Reggio Cal, Italy
| | - Kitty J Jager
- Department of Medical Informatics, ERA-EDTA Registry, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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26
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de Jong Y, Fu EL, van Diepen M, Trevisan M, Szummer K, Dekker FW, Carrero JJ, Ocak G. Validation of risk scores for ischaemic stroke in atrial fibrillation across the spectrum of kidney function. Eur Heart J 2021; 42:1476-1485. [PMID: 33769473 PMCID: PMC8046502 DOI: 10.1093/eurheartj/ehab059] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/18/2020] [Accepted: 01/22/2021] [Indexed: 12/14/2022] Open
Abstract
Aims The increasing prevalence of ischaemic stroke (IS) can partly be explained by the likewise growing number of patients with chronic kidney disease (CKD). Risk scores have been developed to identify high-risk patients, allowing for personalized anticoagulation therapy. However, predictive performance in CKD is unclear. The aim of this study is to validate six commonly used risk scores for IS in atrial fibrillation (AF) patients across the spectrum of kidney function. Methods and results Overall, 36 004 subjects with newly diagnosed AF from SCREAM (Stockholm CREAtinine Measurements), a healthcare utilization cohort of Stockholm residents, were included. Predictive performance of the AFI, CHADS2, Modified CHADS2, CHA2DS2-VASc, ATRIA, and GARFIELD-AF risk scores was evaluated across three strata of kidney function: normal kidney function [estimated glomerular filtration rate (eGFR) >60 mL/min/1.73 m2], mild CKD (eGFR 30–60 mL/min/1.73 m2), and advanced CKD (eGFR <30 mL/min/1.73 m2). Predictive performance was assessed by discrimination and calibration. During 1.9 years, 3069 (8.5%) patients suffered an IS. Discrimination was dependent on eGFR: the median c-statistic in normal eGFR was 0.75 (range 0.68–0.78), but decreased to 0.68 (0.58–0.73) and 0.68 (0.55–0.74) for mild and advanced CKD, respectively. Calibration was reasonable and largely independent of eGFR. The Modified CHADS2 score showed good performance across kidney function strata, both for discrimination [c-statistic: 0.78 (95% confidence interval 0.77–0.79), 0.73 (0.71–0.74) and 0.74 (0.69–0.79), respectively] and calibration. Conclusion In the most clinically relevant stages of CKD, predictive performance of the majority of risk scores was poor, increasing the risk of misclassification and thus of over- or undertreatment. The Modified CHADS2 score performed good and consistently across all kidney function strata, and should therefore be preferred for risk estimation in AF patients.
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Affiliation(s)
- Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands.,Department of Internal Medicine, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Marco Trevisan
- Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Karolina Szummer
- Department of Cardiology, Karolinska University Hospital, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | - Juan J Carrero
- Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Gurbey Ocak
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands.,Department of Internal Medicine, Sint Antonius Hospital, Koekoekslaan 1, 3435 CM Nieuwegein, the Netherlands
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27
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Ramspek CL, Evans M, Wanner C, Drechsler C, Chesnaye NC, Szymczak M, Krajewska M, Torino C, Porto G, Hayward S, Caskey F, Dekker FW, Jager KJ, van Diepen M. Kidney Failure Prediction Models: A Comprehensive External Validation Study in Patients with Advanced CKD. J Am Soc Nephrol 2021; 32:1174-1186. [PMID: 33685974 PMCID: PMC8259669 DOI: 10.1681/asn.2020071077] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Accepted: 12/26/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Various prediction models have been developed to predict the risk of kidney failure in patients with CKD. However, guideline-recommended models have yet to be compared head to head, their validation in patients with advanced CKD is lacking, and most do not account for competing risks. METHODS To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration. RESULTS The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%-18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts. CONCLUSIONS Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years).
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Affiliation(s)
- Chava L. Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie Evans
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Christoph Wanner
- Division of Nephrology, University Hospital of Wurzburg, Wurzburg, Germany
| | - Christiane Drechsler
- Division of Nephrology, Department of Internal Medicine 1, University Hospital Wurzburg, Wurzburg, Germany
| | - Nicholas C. Chesnaye
- Department of Medical Informatics, European Renal Association–European Dialysis and Transplant Association Registry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Maciej Szymczak
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Magdalena Krajewska
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Claudia Torino
- Department of Clinical Epidemiology of Renal Diseases and Hypertension, Consiglio Nazionale della Ricerche - Istituto di fisiologia clinica, Reggio Calabria, Italy
| | - Gaetana Porto
- Department of Clinical Epidemiology of Renal Diseases and Hypertension, Consiglio Nazionale della Ricerche - Istituto di fisiologia clinica, Reggio Calabria, Italy
| | - Samantha Hayward
- Department of Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom,United Kingdom Renal Registry, Bristol, United Kingdom
| | - Fergus Caskey
- Departmen of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Friedo W. Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Kitty J. Jager
- Department of Medical Informatics, European Renal Association–European Dialysis and Transplant Association Registry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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28
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Fu EL, van Diepen M, Xu Y, Trevisan M, Dekker FW, Zoccali C, Jager K, Carrero JJ. Pharmacoepidemiology for nephrologists (part 2): potential biases and how to overcome them. Clin Kidney J 2021; 14:1317-1326. [PMID: 33959262 PMCID: PMC8087121 DOI: 10.1093/ckj/sfaa242] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 10/02/2020] [Indexed: 12/21/2022] Open
Abstract
Observational pharmacoepidemiological studies using routinely collected healthcare data are increasingly being used in the field of nephrology to answer questions on the effectiveness and safety of medications. This review discusses a number of biases that may arise in such studies and proposes solutions to minimize them during the design or statistical analysis phase. We first describe designs to handle confounding by indication (e.g. active comparator design) and methods to investigate the influence of unmeasured confounding, such as the E-value, the use of negative control outcomes and control cohorts. We next discuss prevalent user and immortal time biases in pharmacoepidemiology research and how these can be prevented by focussing on incident users and applying either landmarking, using a time-varying exposure, or the cloning, censoring and weighting method. Lastly, we briefly discuss the common issues with missing data and misclassification bias. When these biases are properly accounted for, pharmacoepidemiological observational studies can provide valuable information for clinical practice.
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Affiliation(s)
- Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Yang Xu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Marco Trevisan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Carmine Zoccali
- CNR-IFC, Clinical Epidemiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Kitty Jager
- Department of Medical Informatics, ERA-EDTA Registry, Amsterdam University Medical Center, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands
| | - Juan Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
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29
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Janmaat CJ, van Diepen M, Meuleman Y, Chesnaye NC, Drechsler C, Torino C, Wanner C, Postorino M, Szymczak M, Evans M, Caskey FJ, Jager KJ, Dekker FW. Kidney function and symptom development over time in elderly patients with advanced chronic kidney disease: results of the EQUAL cohort study. Nephrol Dial Transplant 2021; 36:862-870. [PMID: 31943084 PMCID: PMC8075370 DOI: 10.1093/ndt/gfz277] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2019] [Accepted: 11/22/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Initiation of renal replacement therapy often results from a combination of kidney function deterioration and symptoms related to chronic kidney disease (CKD) progression. We investigated the association between kidney function decline and symptom development in patients with advanced CKD. METHODS In the European Quality study on treatment in advanced CKD (EQUAL study), a European prospective cohort study, patients with advanced CKD aged ≥65 years and a kidney function that dropped <20 mL/min/1.73 m2 were followed for 1 year. Linear mixed-effects models were used to assess the association between kidney function decline and symptom development. The sum score for symptom number ranged from 0 to 33 and for overall symptom severity from 0 to 165, using the Dialysis Symptom Index. RESULTS At least one kidney function estimate with symptom number or overall symptom severity was available for 1109 and 1019 patients, respectively. The mean (95% confidence interval) annual kidney function decline was 1.70 (1.32; 2.08) mL/min/1.73 m2. The mean overall increase in symptom number and severity was 0.73 (0.28; 1.19) and 2.93 (1.34; 4.52) per year, respectively. A cross-sectional association between the level of kidney function and symptoms was lacking. Furthermore, kidney function at cohort entry was not associated with symptom development. However, each mL/min/1.73 m2 of annual kidney function decline was associated with an extra annual increase of 0.23 (0.07; 0.39) in the number of symptoms and 0.87 (0.35; 1.40) in overall symptom severity. CONCLUSIONS A faster kidney function decline was associated with a steeper increase in both symptom number and severity. Considering the modest association, our results seem to suggest that repeated thorough assessment of symptom development during outpatient clinic visits, in addition to the monitoring of kidney function decline, is important for clinical decision-making.
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Affiliation(s)
- Cynthia J Janmaat
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Yvette Meuleman
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Nicholas C Chesnaye
- Department of Medical Informatics, Academic Medical Center, ERA-EDTA Registry, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Christiane Drechsler
- Department of Medicine, Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Claudia Torino
- CNR-IFC, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Christoph Wanner
- Department of Medicine, Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Maurizio Postorino
- Nephrology Dialysis and Transplant Unit Grande Ospedale Metropolitano, Reggio Calabria, Italy
| | - Maciej Szymczak
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Marie Evans
- Department of Clinical Sciences Intervention and Technology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Fergus J Caskey
- UK Renal Registry, Southmead Hospital, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Kitty J Jager
- Department of Medical Informatics, Academic Medical Center, ERA-EDTA Registry, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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30
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van Eck van der Sluijs A, Abrahams AC, Rookmaaker MB, Verhaar MC, Bos WJW, Blankestijn PJ, Dekker FW, van Diepen M, Ocak G. Bleeding risk of haemodialysis and peritoneal dialysis patients. Nephrol Dial Transplant 2021; 36:170-175. [PMID: 33130878 PMCID: PMC7771974 DOI: 10.1093/ndt/gfaa216] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Dialysis patients have an increased bleeding risk as compared with the general population. However, there is limited information whether bleeding risks are different for patients treated with haemodialysis (HD) or peritoneal dialysis (PD). From a clinical point of view, this information could influence therapy choice. Therefore the aim of this study was to investigate the association between dialysis modality and bleeding risk. METHODS Incident dialysis patients from the Netherlands Cooperative Study on the Adequacy of Dialysis were prospectively followed for major bleeding events over 3 years. Hazard ratios with 95% confidence intervals (CIs) were calculated for HD compared with PD using a time-dependent Cox regression analysis, with updates on dialysis modality. RESULTS In total, 1745 patients started dialysis, of whom 1211 (69.4%) received HD and 534 (30.6%) PD. The bleeding rate was 60.8/1000 person-years for HD patients and 34.6/1000 person-years for PD patients. The time-dependent Cox regression analysis showed that after adjustment for age, sex, primary kidney disease, prior bleeding, cardiovascular disease, antiplatelet drug use, vitamin K antagonist use, erythropoietin use, arterial hypertension, residual glomerular filtratin rate, haemoglobin and albumin levels, bleeding risk for HD patients compared with PD increased 1.5-fold (95% CI 1.0-2.2). CONCLUSIONS In this large prospective cohort of incident dialysis patients, HD patients had an increased bleeding risk compared with PD patients. In particular, HD patients with a history of prior bleeding had an increased bleeding risk.
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Affiliation(s)
| | - Alferso C Abrahams
- Department of Nephrology and Hypertension, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Maarten B Rookmaaker
- Department of Nephrology and Hypertension, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Willem Jan W Bos
- Department of Internal Medicine, Sint Antonius Hospital, Nieuwegein, The Netherlands.,Department of Internal Medicine, Leiden University Medical Centre, Leiden, The Netherlands
| | - Peter J Blankestijn
- Department of Nephrology and Hypertension, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Gurbey Ocak
- Department of Nephrology and Hypertension, University Medical Centre Utrecht, Utrecht, The Netherlands.,Department of Internal Medicine, Sint Antonius Hospital, Nieuwegein, The Netherlands.,Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands
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31
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Ramspek CL, de Jong Y, Dekker FW, van Diepen M. Towards the best kidney failure prediction tool: a systematic review and selection aid. Nephrol Dial Transplant 2021; 35:1527-1538. [PMID: 30830157 PMCID: PMC7473808 DOI: 10.1093/ndt/gfz018] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 01/15/2019] [Indexed: 12/14/2022] Open
Abstract
Background Prediction tools that identify chronic kidney disease (CKD) patients at a high risk of developing kidney failure have the potential for great clinical value, but limited uptake. The aim of the current study is to systematically review all available models predicting kidney failure in CKD patients, organize empirical evidence on their validity and ultimately provide guidance in the interpretation and uptake of these tools. Methods PubMed and EMBASE were searched for relevant articles. Titles, abstracts and full-text articles were sequentially screened for inclusion by two independent researchers. Data on study design, model development and performance were extracted. The risk of bias and clinical usefulness were assessed and combined in order to provide recommendations on which models to use. Results Of 2183 screened studies, a total of 42 studies were included in the current review. Most studies showed high discriminatory capacity and the included predictors had large overlap. Overall, the risk of bias was high. Slightly less than half the studies (48%) presented enough detail for the use of their prediction tool in practice and few models were externally validated. Conclusions The current systematic review may be used as a tool to select the most appropriate and robust prognostic model for various settings. Although some models showed great potential, many lacked clinical relevance due to being developed in a prevalent patient population with a wide range of disease severity. Future research efforts should focus on external validation and impact assessment in clinically relevant patient populations.
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Affiliation(s)
- Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Fu EL, Evans M, Clase CM, Tomlinson LA, van Diepen M, Dekker FW, Carrero JJ. Stopping Renin-Angiotensin System Inhibitors in Patients with Advanced CKD and Risk of Adverse Outcomes: A Nationwide Study. J Am Soc Nephrol 2021; 32:424-435. [PMID: 33372009 PMCID: PMC8054897 DOI: 10.1681/asn.2020050682] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 10/06/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND It is unknown whether stopping renin-angiotensin system (RAS) inhibitor therapy in patients with advanced CKD affects outcomes. METHODS We studied patients referred to nephrologist care, listed on the Swedish Renal Registry during 2007-2017, who developed advanced CKD (eGFR<30 ml/min per 1.73 m2) while on RAS inhibitor therapy. Using target trial emulation techniques on the basis of cloning, censoring, and weighting, we compared the risks of stopping within 6 months and remaining off treatment versus continuing RAS inhibitor therapy. These included risks of subsequent 5-year all-cause mortality, major adverse cardiovascular events, and initiation of kidney replacement therapy (KRT). RESULTS Of 10,254 prevalent RAS inhibitor users (median age 72 years, 36% female) with new-onset eGFR <30 ml/min per 1.73 m2, 1553 (15%) stopped RAS inhibitor therapy within 6 months. Median eGFR was 23 ml/min per 1.73 m2. Compared with continuing RAS inhibition, stopping this therapy was associated with a higher absolute 5-year risk of death (40.9% versus 54.5%) and major adverse cardiovascular events (47.6% versus 59.5%), but with a lower risk of KRT (36.1% versus 27.9%); these corresponded to absolute risk differences of 13.6 events per 100 patients, 11.9 events per 100 patients, and -8.3 events per 100 patients, respectively. Results were consistent whether patients stopped RAS inhibition at higher or lower eGFR, across prespecified subgroups, after adjustment and stratification for albuminuria and potassium, and when modeling RAS inhibition as a time-dependent exposure using a marginal structural model. CONCLUSIONS In this nationwide observational study of people with advanced CKD, stopping RAS inhibition was associated with higher absolute risks of mortality and major adverse cardiovascular events, but also with a lower absolute risk of initiating KRT.
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Affiliation(s)
- Edouard L. Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie Evans
- Department of Clinical Science, Intervention and Technology, Karolinska Institute, Stockholm, Sweden
| | - Catherine M. Clase
- Department of Medicine and Health Research Methods, Evidence and Impact, McMaster University, Ontario, Canada
| | - Laurie A. Tomlinson
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W. Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Juan J. Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
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33
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Terhuerne J, van Diepen M, Kramann R, Erpenbeck J, Dekker F, Marx N, Floege J, Becker M, Schlieper G. Speckle-tracking echocardiography in comparison with ejection fraction for prediction of cardiovascular mortality in patients with end-stage renal disease. Clin Kidney J 2021; 14:1579-1585. [PMID: 34276976 PMCID: PMC8280917 DOI: 10.1093/ckj/sfaa161] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 06/07/2020] [Indexed: 11/13/2022] Open
Abstract
Background Cardiovascular disease is the major cause of death in end-stage renal disease (ESRD). To develop better means to assess cardiovascular risk in these patients, we compared conventional echocardiography-derived left ventricular ejection fraction (EF) with the novel method of 2D speckle-tracking echocardiography to determine cardiac strain. Methods Predictive performances of conventional EF and speckle-tracking echocardiography-derived global longitudinal strain (GLS) were compared using receiver-operator curve (ROC) analyses and calibration by calibration plots. We also took into account other known cardiovascular risk factors through multivariable logistic regression analysis. Results The study comprised 171 ESRD patients (mean age 64 years, 64% male) on maintenance dialysis therapy (93% haemodialysis, 7% peritoneal dialysis) for an average period of 39 months. During 2.1 years of follow-up, 42 patients (25%) died from cardiovascular disease. ROC analysis of GLS resulted in an area under the curve of 0.700 [95% confidence interval (CI) 0.603–0.797] compared with an area under the curve of EF of 0.615 (95% CI 0.514–0.716) (P = 0.059 for difference). The total absolute deviation between predicted and observed outcome frequencies obtained by calibration plots were 13.8% for EF compared with only 6.4% for GLS. Best results of ROC analysis (area under the curve = 0.759; P = 0.06), calibration and goodness-of-fit (χ2 = 28.34, P ≤ 0.0001, R2 = 0.25) were achieved for GLS added to a baseline model consisting of known cardiovascular risk factors in a multivariate regression analysis. Conclusions In summary, in chronic dialysis patients, GLS is a more precise predictor of cardiovascular mortality than conventional echocardiography-derived EF.
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Affiliation(s)
- Janna Terhuerne
- Division of Nephrology and Clinical Immunology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Rafael Kramann
- Division of Nephrology and Clinical Immunology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Johanna Erpenbeck
- Division of Nephrology and Clinical Immunology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Friedo Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Nikolaus Marx
- Department of Cardiology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Jürgen Floege
- Division of Nephrology and Clinical Immunology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Michael Becker
- Department of Cardiology, Medical Faculty RWTH Aachen University, Aachen, Germany
| | - Georg Schlieper
- Division of Nephrology and Clinical Immunology, Medical Faculty RWTH Aachen University, Aachen, Germany.,Center for Nephrology, Hypertension, and Metabolic Diseases, Hannover, Germany
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34
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Fu EL, Clase CM, Evans M, Lindholm B, Rotmans JI, Dekker FW, van Diepen M, Carrero JJ. Comparative Effectiveness of Renin-Angiotensin System Inhibitors and Calcium Channel Blockers in Individuals With Advanced CKD: A Nationwide Observational Cohort Study. Am J Kidney Dis 2020; 77:719-729.e1. [PMID: 33246024 DOI: 10.1053/j.ajkd.2020.10.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 10/15/2020] [Indexed: 01/09/2023]
Abstract
RATIONALE & OBJECTIVE It is unknown whether initiating renin-angiotensin system (RAS) inhibitor therapy in patients with advanced chronic kidney disease (CKD) is superior to alternative antihypertensive agents such as calcium channel blockers (CCBs). We compared the risks for kidney replacement therapy (KRT), mortality, and major adverse cardiovascular events (MACE) in patients with advanced CKD in routine nephrology practice who were initiating either RAS inhibitor or CCB therapy. STUDY DESIGN Observational study in the Swedish Renal Registry, 2007 to 2017. SETTINGS & PARTICIPANTS 2,458 new users of RAS inhibitors and 2,345 CCB users with estimated glomerular filtration rates<30mL/min/1.73m2 (CKD G4-G5 without KRT) who were being followed up by a nephrologist. As a positive control cohort, new users of the same drugs with CKD G3 (estimated glomerular filtration rate, 30-60mL/min/1.73m2) were evaluated. EXPOSURES RAS inhibitor versus CCB therapy initiation. OUTCOME Initiation of KRT (maintenance dialysis or transplantation), all-cause mortality, and MACE (composite of cardiovascular death, myocardial infarction, or stroke). ANALYTICAL APPROACH HRs with 95% CIs were estimated using propensity score-weighted Cox proportional hazards regression adjusting for demographic, clinical, and laboratory covariates. RESULTS Median age was 74 years, 38% were women, and median follow-up was 4.1 years. After propensity score weighting, there was significantly lower risk for KRT after new use of RAS inhibitors compared with new use of CCBs (adjusted HR, 0.79 [95% CI, 0.69-0.89]) but similar risks for mortality (adjusted HR, 0.97 [95% CI, 0.88-1.07]) and MACE (adjusted HR, 1.00 [95% CI, 0.88-1.15]). Results were consistent across subgroups and in as-treated analyses. The positive control cohort of patients with CKD G3 showed similar KRT risk reduction (adjusted HR, 0.67 [95% CI, 0.56-0.80]) with RAS inhibitor therapy compared with CCBs. LIMITATIONS Potential confounding by indication. CONCLUSIONS Our findings provide evidence from real-world clinical practice that initiation of RAS inhibitor therapy compared with CCBs may confer kidney benefits among patients with advanced CKD, with similar cardiovascular protection.
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Affiliation(s)
- Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Catherine M Clase
- Department of Medicine and Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
| | - Marie Evans
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Bengt Lindholm
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Joris I Rotmans
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
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35
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Ramspek CL, Jager KJ, Dekker FW, Zoccali C, van Diepen M. External validation of prognostic models: what, why, how, when and where? Clin Kidney J 2020; 14:49-58. [PMID: 33564405 PMCID: PMC7857818 DOI: 10.1093/ckj/sfaa188] [Citation(s) in RCA: 268] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 07/28/2020] [Indexed: 12/19/2022] Open
Abstract
Prognostic models that aim to improve the prediction of clinical events, individualized treatment and decision-making are increasingly being developed and published. However, relatively few models are externally validated and validation by independent researchers is rare. External validation is necessary to determine a prediction model’s reproducibility and generalizability to new and different patients. Various methodological considerations are important when assessing or designing an external validation study. In this article, an overview is provided of these considerations, starting with what external validation is, what types of external validation can be distinguished and why such studies are a crucial step towards the clinical implementation of accurate prediction models. Statistical analyses and interpretation of external validation results are reviewed in an intuitive manner and considerations for selecting an appropriate existing prediction model and external validation population are discussed. This study enables clinicians and researchers to gain a deeper understanding of how to interpret model validation results and how to translate these results to their own patient population.
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Affiliation(s)
- Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Kitty J Jager
- Department of Medical Informatics, Amsterdam Public Health Institute, ERA-EDTA Registry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Carmine Zoccali
- CNR-IFC, Clinical Epidemiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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36
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Fu EL, van Diepen M. Comment on Kwon et al. The Long-term Effects of Metformin on Patients With Type 2 Diabetic Kidney Disease. Diabetes Care 2020;43:948-955. Diabetes Care 2020; 43:e190. [PMID: 33082247 DOI: 10.2337/dc20-1591] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, the Netherlands
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Ommering BWC, van Diepen M, van Blankenstein FM, de Jong PGM, Dekker FW. Twelve tips to offer a short authentic and experiential individual research opportunity to a large group of undergraduate students. Med Teach 2020; 42:1128-1133. [PMID: 33073658 DOI: 10.1080/0142159x.2019.1695766] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Engaging students in research during medical school could contribute to creating an academic attitude among students, which underlies practicing evidence-based medicine in future professional practice. However, attempts to involve undergraduate students in research during medical training remain inadequate. Most medical schools educate large numbers of students at the same time, especially in early phases of medical training. Large scale education on the one hand and individually providing students with authentic research experiences on the other hand is considered not that easy to achieve. Drawing on our own experiences, existing literature and theories we propose twelve tips to design and implement a course in which authentic individual research experiences can be provided to a large group of undergraduate students.
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Affiliation(s)
- Belinda W C Ommering
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Floris M van Blankenstein
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
- Department of Higher Education, Leiden University Graduate School of Teaching, Leiden, The Netherlands
| | - Peter G M de Jong
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Center for Innovation in Medical Education, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Zamanipoor Najafabadi AH, Ramspek CL, Dekker FW, Heus P, Hooft L, Moons KGM, Peul WC, Collins GS, Steyerberg EW, van Diepen M. TRIPOD statement: a preliminary pre-post analysis of reporting and methods of prediction models. BMJ Open 2020; 10:e041537. [PMID: 32948578 PMCID: PMC7511612 DOI: 10.1136/bmjopen-2020-041537] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 07/21/2020] [Accepted: 07/23/2020] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVES To assess the difference in completeness of reporting and methodological conduct of published prediction models before and after publication of the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. METHODS In the seven general medicine journals with the highest impact factor, we compared the completeness of the reporting and the quality of the methodology of prediction model studies published between 2012 and 2014 (pre-TRIPOD) with studies published between 2016 and 2017 (post-TRIPOD). For articles published in the post-TRIPOD period, we examined whether there was improved reporting for articles (1) citing the TRIPOD statement, and (2) published in journals that published the TRIPOD statement. RESULTS A total of 70 articles was included (pre-TRIPOD: 32, post-TRIPOD: 38). No improvement was seen for the overall percentage of reported items after the publication of the TRIPOD statement (pre-TRIPOD 74%, post-TRIPOD 76%, 95% CI of absolute difference: -4% to 7%). For the individual TRIPOD items, an improvement was seen for 16 (44%) items, while 3 (8%) items showed no improvement and 17 (47%) items showed a deterioration. Post-TRIPOD, there was no improved reporting for articles citing the TRIPOD statement, nor for articles published in journals that published the TRIPOD statement. The methodological quality improved in the post-TRIPOD period. More models were externally validated in the same article (absolute difference 8%, post-TRIPOD: 39%), used measures of calibration (21%, post-TRIPOD: 87%) and discrimination (9%, post-TRIPOD: 100%), and used multiple imputation for handling missing data (12%, post-TRIPOD: 50%). CONCLUSIONS Since the publication of the TRIPOD statement, some reporting and methodological aspects have improved. Prediction models are still often poorly developed and validated and many aspects remain poorly reported, hindering optimal clinical application of these models. Long-term effects of the TRIPOD statement publication should be evaluated in future studies.
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Affiliation(s)
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pauline Heus
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center (UMC) Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Lotty Hooft
- Dutch Cochrane Centre (DCC), Julius Center for Health Sciences and Primary Care, University Medical Centre (UMC) Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Karel G M Moons
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands
| | - Wilco C Peul
- Department of Neurosurgery, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurosurgery, The Hague Medical Center, The Hague, The Netherlands
| | | | - Ewout W Steyerberg
- Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Steenbeek ED, Ramspek CL, van Diepen M, Dekker FW, Achterberg WP. The Association Between Pain Perception and Care Dependency in Older Nursing Home Residents: A Prospective Cohort Study. J Am Med Dir Assoc 2020; 22:676-681. [PMID: 32868249 DOI: 10.1016/j.jamda.2020.07.022] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 07/05/2020] [Accepted: 07/16/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES Maintenance of independence is a challenge for nursing home residents whose pain is often substantial. The objective of this study was to explore the relationship between pain perception and care dependency in a population of Dutch nursing home residents. DESIGN Prospective cohort study. SETTING AND PARTICIPANTS Dutch nursing home residents aged 65 or older, excluding residents with a severe cognitive impairment. METHODS The Numeric Rating Scale (NRS) was used to rate pain perception from 0 to 10 in half-point increments and the Care Dependency Scale (CDS) to measure care dependency, with scores ranging from 15 (completely care dependent) to 75 (fully independent). Both measurements were repeated after a 2-month follow-up. Multiple linear regression analysis was used to adjust for potential confounders. Missing data were dealt with by performing tenfold multiple imputation. RESULTS A total of 1256 residents (65% women, mean age 83 years) were included. At baseline, the median NRS pain score was 3.0 (interquartile range 0.0-6.0) and the mean CDS score was 55.9 (SD 11.5). Cross-sectionally, for 1-point increase in pain score, care dependency increased 0.65 points [95% confidence interval (CI) 0.46-0.83]. More pain at baseline was associated with slightly lower care dependency after 2 months (beta 0.20, 95% CI 0.01-0.39). Compared with residents whose pain decreased over 2 months, residents with stable pain or increased pain had a 2.27-point (95% CI 0.83-3.70) and 2.39-point (95% CI 0.87-3.90) greater increase in care dependency, respectively. CONCLUSIONS AND IMPLICATIONS Pain perception and care dependency are associated in a population of older nursing home residents, and stable or increased pain is associated with increased care dependency progression. The findings of this study emphasize that pain and care dependency should not be assessed nor treated independently.
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Affiliation(s)
- Esli D Steenbeek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Wilco P Achterberg
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
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40
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Fu EL, Janse RJ, de Jong Y, van der Endt VHW, Milders J, van der Willik EM, de Rooij ENM, Dekkers OM, Rotmans JI, van Diepen M. Acute kidney injury and kidney replacement therapy in COVID-19: a systematic review and meta-analysis. Clin Kidney J 2020; 13:550-563. [PMID: 32897278 PMCID: PMC7467593 DOI: 10.1093/ckj/sfaa160] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Acute kidney injury (AKI) can affect hospitalized patients with coronavirus disease 2019 (COVID-19), with estimates ranging between 0.5% and 40%. We performed a systematic review and meta-analysis of studies reporting incidence, mortality and risk factors for AKI in hospitalized COVID-19 patients. METHODS We systematically searched 11 electronic databases until 29 May 2020 for studies in English reporting original data on AKI and kidney replacement therapy (KRT) in hospitalized COVID-19 patients. Incidences of AKI and KRT and risk ratios for mortality associated with AKI were pooled using generalized linear mixed and random-effects models. Potential risk factors for AKI were assessed using meta-regression. Incidences were stratified by geographic location and disease severity. RESULTS A total of 3042 articles were identified, of which 142 studies were included, with 49 048 hospitalized COVID-19 patients including 5152 AKI events. The risk of bias of included studies was generally low. The pooled incidence of AKI was 28.6% [95% confidence interval (CI) 19.8-39.5] among hospitalized COVID-19 patients from the USA and Europe (20 studies) and 5.5% (95% CI 4.1-7.4) among patients from China (62 studies), whereas the pooled incidence of KRT was 7.7% (95% CI 5.1-11.4; 18 studies) and 2.2% (95% CI 1.5-3.3; 52 studies), respectively. Among patients admitted to the intensive care unit, the incidence of KRT was 20.6% (95% CI 15.7-26.7; 38 studies). Meta-regression analyses showed that age, male sex, cardiovascular disease, diabetes mellitus, hypertension and chronic kidney disease were associated with the occurrence of AKI; in itself, AKI was associated with an increased risk of mortality, with a pooled risk ratio of 4.6 (95% CI 3.3-6.5). CONCLUSIONS AKI and KRT are common events in hospitalized COVID-19 patients, with estimates varying across geographic locations. Additional studies are needed to better understand the underlying mechanisms and optimal treatment of AKI in these patients.
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Affiliation(s)
- Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Roemer J Janse
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Vera H W van der Endt
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jet Milders
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Esmee M van der Willik
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Esther N M de Rooij
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Olaf M Dekkers
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Joris I Rotmans
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Bidulka P, Fu EL, Leyrat C, Kalogirou F, McAllister KSL, Kingdon EJ, Mansfield KE, Iwagami M, Smeeth L, Clase CM, Bhaskaran K, van Diepen M, Carrero JJ, Nitsch D, Tomlinson LA. Stopping renin-angiotensin system blockers after acute kidney injury and risk of adverse outcomes: parallel population-based cohort studies in English and Swedish routine care. BMC Med 2020; 18:195. [PMID: 32723383 PMCID: PMC7389346 DOI: 10.1186/s12916-020-01659-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 06/08/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The safety of restarting angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) after acute kidney injury (AKI) is unclear. There is concern that previous users do not restart ACEI/ARB despite ongoing indications. We sought to determine the risk of adverse events after an episode of AKI, comparing prior ACEI/ARB users who stop treatment to those who continue. METHODS We conducted two parallel cohort studies in English and Swedish primary and secondary care, 2006-2016. We used multivariable Cox regression to estimate hazard ratios (HR) for hospital admission with heart failure (primary analysis), AKI, stroke, or death within 2 years after hospital discharge following a first AKI episode. We compared risks of admission between people who stopped ACEI/ARB treatment to those who were prescribed ACEI/ARB within 30 days of AKI discharge. We undertook sensitivity analyses, including propensity score-matched samples, to explore the robustness of our results. RESULTS In England, we included 7303 people with AKI hospitalisation following recent ACEI/ARB therapy for the primary analysis. Four thousand three (55%) were classified as stopping ACEI/ARB based on no prescription within 30 days of discharge. In Sweden, we included 1790 people, of whom 1235 (69%) stopped treatment. In England, no differences were seen in subsequent risk of heart failure (HR 1.10; 95% confidence intervals (CI) 0.93-1.30), AKI (HR 0.90; 95% CI 0.77-1.05), or stroke (HR 0.99; 95% CI 0.71-1.38), but there was an increased risk of death (HR 1.27; 95% CI 1.15-1.41) in those who stopped ACEI/ARB compared to those who continued. Results were similar in Sweden: no differences were seen in risk of heart failure (HR 0.91; 95% CI 0.73-1.13) or AKI (HR 0.81; 95% CI 0.54-1.21). However, no increased risk of death was seen (HR 0.94; 95% CI 0.78-1.13) and stroke was less common in people who stopped ACEI/ARB (HR 0.56; 95% CI 0.34-0.93). Results were similar across all sensitivity analyses. CONCLUSIONS Previous ACEI/ARB users who continued treatment after an episode of AKI did not have an increased risk of heart failure or subsequent AKI compared to those who stopped the drugs.
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Affiliation(s)
- Patrick Bidulka
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
| | - Edouard L Fu
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef, Leiden, 2333ZA, The Netherlands
| | - Clémence Leyrat
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Fotini Kalogirou
- Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Katherine S L McAllister
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Edward J Kingdon
- Sussex Kidney Unit, Royal Sussex County Hospital, Brighton, BN2 5BE, UK
| | - Kathryn E Mansfield
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Masao Iwagami
- Department of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Liam Smeeth
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Catherine M Clase
- Department of Medicine, Department of Health Research, Evidence and Impact, McMaster University, Hamilton, ON, Canada
| | - Krishnan Bhaskaran
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Albinusdreef, Leiden, 2333ZA, The Netherlands
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12, Stockholm, Sweden
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Laurie A Tomlinson
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
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Bosdriesz JR, Stel VS, van Diepen M, Meuleman Y, Dekker FW, Zoccali C, Jager KJ. Evidence-based medicine-When observational studies are better than randomized controlled trials. Nephrology (Carlton) 2020; 25:737-743. [PMID: 32542836 PMCID: PMC7540602 DOI: 10.1111/nep.13742] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 06/02/2020] [Accepted: 06/06/2020] [Indexed: 01/06/2023]
Abstract
In evidence-based medicine, clinical research questions may be addressed by different study designs. This article describes when randomized controlled trials (RCT) are needed and when observational studies are more suitable. According to the Centre for Evidence-Based Medicine, study designs can be divided into analytic and non-analytic (descriptive) study designs. Analytic studies aim to quantify the association of an intervention (eg, treatment) or a naturally occurring exposure with an outcome. They can be subdivided into experimental (ie, RCT) and observational studies. The RCT is the best study design to evaluate the intended effect of an intervention, because the randomization procedure breaks the link between the allocation of the intervention and patient prognosis. If the randomization of the intervention or exposure is not possible, one needs to depend on observational analytic studies, but these studies usually suffer from bias and confounding. If the study focuses on unintended effects of interventions (ie, effects of an intervention that are not intended or foreseen), observational analytic studies are the most suitable study designs, provided that there is no link between the allocation of the intervention and the unintended effect. Furthermore, non-analytic studies (ie, descriptive studies) also rely on observational study designs. In summary, RCTs and observational study designs are inherently different, and depending on the study aim, they each have their own strengths and weaknesses.
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Affiliation(s)
- Jizzo R Bosdriesz
- ERA-EDTA Registry, Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC-location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Vianda S Stel
- ERA-EDTA Registry, Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC-location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Yvette Meuleman
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Carmine Zoccali
- CNR-IFC, Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
| | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC-location AMC, University of Amsterdam, Amsterdam, The Netherlands
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van Geloven N, Swanson SA, Ramspek CL, Luijken K, van Diepen M, Morris TP, Groenwold RHH, van Houwelingen HC, Putter H, le Cessie S. Prediction meets causal inference: the role of treatment in clinical prediction models. Eur J Epidemiol 2020; 35:619-630. [PMID: 32445007 PMCID: PMC7387325 DOI: 10.1007/s10654-020-00636-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 04/18/2020] [Indexed: 11/29/2022]
Abstract
In this paper we study approaches for dealing with treatment when developing a clinical prediction model. Analogous to the estimand framework recently proposed by the European Medicines Agency for clinical trials, we propose a 'predictimand' framework of different questions that may be of interest when predicting risk in relation to treatment started after baseline. We provide a formal definition of the estimands matching these questions, give examples of settings in which each is useful and discuss appropriate estimators including their assumptions. We illustrate the impact of the predictimand choice in a dataset of patients with end-stage kidney disease. We argue that clearly defining the estimand is equally important in prediction research as in causal inference.
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Affiliation(s)
- Nan van Geloven
- Department of Biomedical Data Sciences, Leiden University Medical Center, Zone S5-P, PO Box 9600, 2300 RC, Leiden, The Netherlands.
| | - Sonja A Swanson
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, USA
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Kim Luijken
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tim P Morris
- MRC Clinical Trials Unit, UCL London, London, UK
| | - Rolf H H Groenwold
- Department of Biomedical Data Sciences, Leiden University Medical Center, Zone S5-P, PO Box 9600, 2300 RC, Leiden, The Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Hans C van Houwelingen
- Department of Biomedical Data Sciences, Leiden University Medical Center, Zone S5-P, PO Box 9600, 2300 RC, Leiden, The Netherlands
| | - Hein Putter
- Department of Biomedical Data Sciences, Leiden University Medical Center, Zone S5-P, PO Box 9600, 2300 RC, Leiden, The Netherlands
| | - Saskia le Cessie
- Department of Biomedical Data Sciences, Leiden University Medical Center, Zone S5-P, PO Box 9600, 2300 RC, Leiden, The Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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44
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de Jong Y, Ramspek CL, van der Endt VHW, Rookmaaker MB, Blankestijn PJ, Vernooij RWM, Verhaar MC, Bos WJW, Dekker FW, Ocak G, van Diepen M. A systematic review and external validation of stroke prediction models demonstrates poor performance in dialysis patients. J Clin Epidemiol 2020; 123:69-79. [PMID: 32240769 DOI: 10.1016/j.jclinepi.2020.03.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 02/20/2020] [Accepted: 03/19/2020] [Indexed: 12/31/2022]
Abstract
OBJECTIVES The objective of this study was to systematically review and externally assess the predictive performance of models for ischemic stroke in incident dialysis patients. STUDY DESIGN AND SETTING Two reviewers systematically searched and selected ischemic stroke models. Risk of bias was assessed with the PROBAST. Predictive performance was evaluated within The Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD), a large prospective multicenter cohort of incident dialysis patients. For discrimination, c-statistics were calculated; calibration was assessed by plotting predicted and observed probabilities for stroke, and calibration-in-the-large. RESULTS Seventy-seven prediction models for stroke were identified, of which 15 were validated. Risk of bias was high, with all of these models scoring high risk in one or more domains. In NECOSAD, of the 1,955 patients, 127 (6.5%) suffered an ischemic stroke during the follow-up of 2.5 years. Compared with the original studies, most models performed worse with all models showing poor calibration and discriminative abilities (c-statistics ranging from 0.49 to 0.66). The Framingham showed reasonable calibration; however, with a c-statistic of 0.57 (95% CI 0.50-0.63), the discrimination was poor. CONCLUSION This external validation demonstrates the weak predictive performance of ischemic stroke models in incident dialysis patients. Instead of using these models in this fragile population, either existing models should be updated, or novel models should be developed and validated.
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Affiliation(s)
- Ype de Jong
- Department of Clinical Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands; Department of Internal Medicine, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Vera H W van der Endt
- Department of Clinical Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Maarten B Rookmaaker
- Department of Nephrology and Hypertension, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Peter J Blankestijn
- Department of Nephrology and Hypertension, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Robin W M Vernooij
- Department of Nephrology and Hypertension, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Willem Jan W Bos
- Department of Internal Medicine, Leiden University Medical Center (LUMC), Leiden, The Netherlands; Department of Internal Medicine, Sint Antonius Hospital, Nieuwegein, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Gurbey Ocak
- Department of Nephrology and Hypertension, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
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Voskamp PWM, van Diepen M, Evans M, Caskey FJ, Torino C, Postorino M, Szymczak M, Klinger M, Wallquist C, van de Luijtgaarden MWM, Chesnaye NC, Wanner C, Jager KJ, Dekker FW. The impact of symptoms on health-related quality of life in elderly pre-dialysis patients: effect and importance in the EQUAL study. Nephrol Dial Transplant 2020; 34:1707-1715. [PMID: 29939304 DOI: 10.1093/ndt/gfy167] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 05/03/2018] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Quality of life (QoL) is an important outcome in chronic kidney disease (CKD). Patients feel that symptoms are an important determinant of QoL. However, this relation is unknown. The aims of this study were to investigate the impact of the number and severity of symptoms on QoL in elderly pre-dialysis patients, assessed by both the effect of symptoms and their importance relative to kidney function, and other clinical variables on QoL. METHODS The European Quality study (EQUAL study) is an ongoing European prospective follow-up study in late Stage 4/5 CKD patients aged ≥65 years. We used patients included between March 2012 and December 2015. Patients scored their symptoms with the Dialysis Symptom Index, and QoL with the research and development-36 (RAND-36) item Health Survey (RAND-36). The RAND-36 results in a physical component summary (PCS) and a mental component summary (MCS). We used linear regression to estimate the relation between symptoms and QoL at baseline and after 6 months, and to calculate the variance in QoL explained by symptoms. RESULTS The baseline questionnaire was filled in by 1079 (73%) patients (median age 75 years, 66% male, 98% Caucasian), and the follow up questionnaire by 627 (42%) patients. At baseline, every additional symptom changed MCS with -0.81 [95% confidence interval (CI): -0.91 to -0.71] and PCS with -0.50 (95% CI: -0.62 to -0.39). In univariable analyses, number of symptoms explained 22% of MCS variance and 11% of PCS variance, whereas estimated glomerular filtration rate only explained 1%. CONCLUSIONS In elderly CKD Stage 4/5 patients, symptoms have a substantial impact on QoL. This indicates symptoms should have a more prominent role in clinical decision-making.
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Affiliation(s)
- Pauline W M Voskamp
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie Evans
- Department of Clinical Sciences Intervention and Technology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | | | - Claudia Torino
- Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Azienda Ospedaliera Bianchi Melacrino Morelli, Reggio Calabria, Italy
| | - Maurizio Postorino
- Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Azienda Ospedaliera Bianchi Melacrino Morelli, Reggio Calabria, Italy
| | - Maciej Szymczak
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Marian Klinger
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Carin Wallquist
- Department of Nephrology, Skåne University Hospital, Malmö, Sweden
| | - Moniek W M van de Luijtgaarden
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Nicolas C Chesnaye
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Christoph Wanner
- Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
| | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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46
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Ramspek CL, Verberne WR, van Buren M, Dekker FW, Bos WJW, van Diepen M. Predicting mortality risk on dialysis and conservative care: development and internal validation of a prediction tool for older patients with advanced chronic kidney disease. Clin Kidney J 2020; 14:189-196. [PMID: 33564418 PMCID: PMC7857791 DOI: 10.1093/ckj/sfaa021] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 01/24/2020] [Indexed: 02/07/2023] Open
Abstract
Background Conservative care (CC) may be a valid alternative to dialysis for certain older patients with advanced chronic kidney disease (CKD). A model that predicts patient prognosis on both treatment pathways could be of value in shared decision-making. Therefore, the aim is to develop a prediction tool that predicts the mortality risk for the same patient for both dialysis and CC from the time of treatment decision. Methods CKD Stage 4/5 patients aged ≥70 years, treated at a single centre in the Netherlands, were included between 2004 and 2016. Predictors were collected at treatment decision and selected based on literature and an expert panel. Outcome was 2-year mortality. Basic and extended logistic regression models were developed for both the dialysis and CC groups. These models were internally validated with bootstrapping. Model performance was assessed with discrimination and calibration. Results In total, 366 patients were included, of which 126 chose CC. Pre-selected predictors for the basic model were age, estimated glomerular filtration rate, malignancy and cardiovascular disease. Discrimination was moderate, with optimism-corrected C-statistics ranging from 0.675 to 0.750. Calibration plots showed good calibration. Conclusions A prediction tool that predicts 2-year mortality was developed to provide older advanced CKD patients with individualized prognosis estimates for both dialysis and CC. Future studies are needed to test whether our findings hold in other CKD populations. Following external validation, this prediction tool could be used to compare a patient’s prognosis on both dialysis and CC, and help to inform treatment decision-making.
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Affiliation(s)
- Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Wouter R Verberne
- Department of Internal Medicine, St Antonius Hospital, Nieuwegein, The Netherlands.,Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Marjolijn van Buren
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands.,Department of Internal Medicine, Haga Hospital, The Hague, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Willem Jan W Bos
- Department of Internal Medicine, St Antonius Hospital, Nieuwegein, The Netherlands.,Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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47
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Ocak G, Ramspek C, Rookmaaker MB, Blankestijn PJ, Verhaar MC, Bos WJW, Dekker FW, van Diepen M. Performance of bleeding risk scores in dialysis patients. Nephrol Dial Transplant 2020; 34:1223-1231. [PMID: 30608543 DOI: 10.1093/ndt/gfy387] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Bleeding risk scores have been created to identify patients with an increased bleeding risk, which could also be useful in dialysis patients. However, the predictive performances of these bleeding risk scores in dialysis patients are unknown. Therefore, the aim of this study was to validate existing bleeding risk scores in dialysis patients. METHODS A cohort of 1745 incident dialysis patients was prospectively followed for 3 years during which bleeding events were registered. We evaluated the discriminative performance of the Hypertension, Abnormal kidney and liver function, Stroke, Bleeding, Labile INR, Elderly and Drugs or alcohol (HASBLED), the AnTicoagulation and Risk factors In Atrial fibrillation (ATRIA), the Hepatic or kidney disease, Ethanol abuse, Malignancy, Older age, Reduced platelet count or Reduced platelet function, Hypertension, Anaemia, Genetic factors, Excessive fall risk and Stroke (HEMORR2HAGES) and the Outcomes Registry for Better Informed Treatment (ORBIT) bleeding risk scores by calculating C-statistics with 95% confidence intervals (CI). In addition, calibration was evaluated by comparing predicted and observed risks. RESULTS Of the 1745 dialysis patients, 183 patients had a bleeding event, corresponding to an incidence rate of 5.23/100 person-years. The HASBLED [C-statistic of 0.58 (95% CI 0.54-0.62)], ATRIA [C-statistic of 0.55 (95% CI 0.51-0.60)], HEMORR2HAGES [C-statistic of 0.56 (95% CI 0.52-0.61)] and ORBIT [C-statistic of 0.56 (95% CI 0.52-0.61)] risk scores had poor discriminative performances in dialysis patients. Furthermore, the calibration analyses showed that patients with a low risk of bleeding according to the HASBLED, ATRIA, HEMORR2HAGES and ORBIT bleeding risk scores had higher incidence rates for bleeding in our cohort than predicted. CONCLUSIONS The HASBLED, ATRIA, HEMORR2HAGES and ORBIT bleeding risk scores had poor predictive abilities in dialysis patients. Therefore, these bleeding risk scores may not be useful in this population.
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Affiliation(s)
- Gurbey Ocak
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Chava Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Maarten B Rookmaaker
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Peter J Blankestijn
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Willem Jan W Bos
- Department of Internal Medicine, Sint Antonius Hospital, Nieuwegein, The Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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48
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Janmaat CJ, van Diepen M, Tsonaka R, Jager KJ, Zoccali C, Dekker FW. Pitfalls of linear regression for estimating slopes over time and how to avoid them by using linear mixed-effects models. Nephrol Dial Transplant 2020; 34:561-566. [PMID: 29796633 DOI: 10.1093/ndt/gfy128] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Indexed: 11/13/2022] Open
Abstract
Clinical epidemiological studies often focus on investigating the underlying causes of disease. For instance, a nephrologist may be interested in the association between blood pressure and the development of chronic kidney disease (CKD). However, instead of focusing on the mere occurrence of CKD, the decline of kidney function over time might be the outcome of interest. For examining this kidney function trajectory, patients are typically followed over time with their kidney function estimated at several time points. During follow-up, some patients may drop out earlier than others and for different reasons. Furthermore, some patients may have greater kidney function at study entry or faster kidney function decline than others. Also, a substantial heterogeneity may exist in the number of kidney function estimates available for each patient. This heterogeneity with respect to kidney function, dropout and number of kidney function estimates is important to take into account when estimating kidney function trajectories. In general, two methods are used in the literature to estimate kidney function trajectories over time: linear regression to estimate individual slopes and the linear mixed-effects model (LMM), i.e. repeated measures analysis. Importantly, the linear regression method does not properly take into account the above-mentioned heterogeneity, whereas the LMM is able to retain all information and variability in the data. However, the underlying concepts, use and interpretation of LMMs are not always straightforward. Therefore we illustrate this using a clinical example and offer a framework of how to model and interpret the LMM.
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Affiliation(s)
- Cynthia J Janmaat
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Roula Tsonaka
- Department of Biomedical Data Sciences, Section Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Kitty J Jager
- ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands and
| | - Carmine Zoccali
- Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, National Council of Research, Institute of Clinical Physiology, Reggio Calabria, Italy
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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49
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Meuwese CL, van Diepen M, Cappola AR, Sarnak MJ, Shlipak MG, Bauer DC, Fried LP, Iacoviello M, Vaes B, Degryse J, Khaw KT, Luben RN, Åsvold BO, Bjøro T, Vatten LJ, de Craen AJM, Trompet S, Iervasi G, Molinaro S, Ceresini G, Ferrucci L, Dullaart RPF, Bakker SJL, Jukema JW, Kearney PM, Stott DJ, Peeters RP, Franco OH, Völzke H, Walsh JP, Bremner A, Sgarbi JA, Maciel RMB, Imaizumi M, Ohishi W, Dekker FW, Rodondi N, Gussekloo J, den Elzen WPJ. Low thyroid function is not associated with an accelerated deterioration in renal function. Nephrol Dial Transplant 2020; 34:650-659. [PMID: 29684213 DOI: 10.1093/ndt/gfy071] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is frequently accompanied by thyroid hormone dysfunction. It is currently unclear whether these alterations are the cause or consequence of CKD. This study aimed at studying the effect of thyroid hormone alterations on renal function in cross-sectional and longitudinal analyses in individuals from all adult age groups. METHODS Individual participant data (IPD) from 16 independent cohorts having measured thyroid stimulating hormone, free thyroxine levels and creatinine levels were included. Thyroid hormone status was defined using clinical cut-off values. Estimated glomerular filtration rates (eGFR) were calculated by means of the four-variable Modification of Diet in Renal Disease (MDRD) formula. For this IPD meta-analysis, eGFR at baseline and eGFR change during follow-up were computed by fitting linear regression models and linear mixed models in each cohort separately. Effect estimates were pooled using random effects models. RESULTS A total of 72 856 individuals from 16 different cohorts were included. At baseline, individuals with overt hypothyroidism (n = 704) and subclinical hypothyroidism (n = 3356) had a average (95% confidence interval) -4.07 (-6.37 to -1.78) and -2.40 (-3.78 to -1.02) mL/min/1.73 m2 lower eGFR as compared with euthyroid subjects (n = 66 542). In (subclinical) hyperthyroid subjects (n = 2254), average eGFR was 3.01 (1.50-4.52) mL/min/1.73 m2 higher. During 329 713 patient years of follow-up, eGFR did not decline more rapidly in individuals with low thyroid function compared with individuals with normal thyroid function. CONCLUSIONS Low thyroid function is not associated with a deterioration of renal function. The cross-sectional association may be explained by renal dysfunction causing thyroid hormone alterations.
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Affiliation(s)
- Christiaan L Meuwese
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anne R Cappola
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Mark J Sarnak
- Department of Medicine, Division of Nephrology, Tufts Medical Center, Boston, MA, USA
| | - Michael G Shlipak
- Department of Medicine, UCSF School of Medicine, San Francisco, CA, USA
| | - Douglas C Bauer
- Department of Medicine, University of California, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of San Francisco, CA, USA
| | - Linda P Fried
- Mailman School of Public Health and Columbia University Medical Center, New York, NY, USA
| | - Massimo Iacoviello
- University Cardiology Unit, Cardiothoracic Department, University Policlinic Hospital, Bari, Italy
| | - Bert Vaes
- Institute of Health and Society, Université catholique de Louvain (UCL), Brussels, Belgium.,Department of Public Health and Primary Care, Katholieke Universiteit Leuven (KUL), Leuven, Belgium
| | - Jean Degryse
- Institute of Health and Society, Université catholique de Louvain (UCL), Brussels, Belgium.,Department of Public Health and Primary Care, Katholieke Universiteit Leuven (KUL), Leuven, Belgium
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Robert N Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Bjørn O Åsvold
- Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Endocrinology, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Trine Bjøro
- Department of Medical Biochemistry, Oslo University Hospital, and Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Lars J Vatten
- Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anton J M de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Stella Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.,Department of Cardiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Giorgio Iervasi
- National Council Research Institute of Clinical Physiology, Tuscany Region G. Monasterio Foundation, Pisa, Italy
| | - Sabrina Molinaro
- National Council Research Institute of Clinical Physiology, Pisa, Italy
| | - Graziano Ceresini
- Department of Clinical and Experimental Medicine, Geriatric Endocrine Unit, University Hospital of Parma, Parma, Italy
| | | | - Robin P F Dullaart
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Stephan J L Bakker
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Centre, Leiden, The Netherlands
| | | | - David J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Robin P Peeters
- Department of Internal Medicine, Rotterdam Thyroid Center, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Oscar H Franco
- Department of Internal Medicine, Rotterdam Thyroid Center, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, SHIP/Clinical-Epidemiological Research & German Centre of Cardiovascular Research, University of Greifswald, Greifswald, Germany
| | - John P Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia.,Medical School, The University of Western Australia, Crawley, Western Australia
| | - Alexandra Bremner
- School of Population Health, The University of Western Australia, Crawley, Western Australia
| | - José A Sgarbi
- Division of Endocrinology, Faculdade de Medicina de Marília, Marília, Brazil
| | - Rui M B Maciel
- Division of Endocrinology, Department of Medicine, Federal University of São Paulo, São Paulo, Brazil
| | - Misa Imaizumi
- Department of Clinical Studies, Radiation Effects Research Foundation, Hiroshima and Nagasaki, Japan
| | - Waka Ohishi
- Department of Clinical Studies, Radiation Effects Research Foundation, Hiroshima and Nagasaki, Japan
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Nicolas Rodondi
- Department of General Internal Medicine, Inselspital, University of Bern, Bern, Switzerland.,Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
| | - Jacobijn Gussekloo
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Wendy P J den Elzen
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Center, Leiden, The Netherlands
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50
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Schroijen MA, van Diepen M, Hamming JF, Dekker FW, Dekkers OM. Mortality after amputation in dialysis patients is high but not modified by diabetes status. Clin Kidney J 2019; 13:1077-1082. [PMID: 33391752 PMCID: PMC7769538 DOI: 10.1093/ckj/sfz116] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 08/07/2019] [Indexed: 01/22/2023] Open
Abstract
Background Survival among dialysis patients with diabetes mellitus (DM) is inferior to survival of non-diabetic dialysis patients, probably due to the higher prevalence of diabetes-related comorbid conditions. One could hypothesize that these comorbid conditions also contribute to a decreased survival after amputation in diabetic patients compared with non-diabetic patients on dialysis. Methods Data were collected from the Netherlands Cooperative Study on the Adequacy of Dialysis, a multicentre, prospective cohort study in which new patients with end-stage renal disease were monitored until transplantation or death. Amputation rates (incident cases) were calculated in patients with and without DM. The primary endpoint was all-cause survival after first amputation during dialysis therapy in diabetic patients compared with non-diabetic dialysis patients with an amputation. This was formally assessed using interaction analysis (Poisson regression). Results During follow-up (mean duration 2.9 years), 50 of the 413 diabetic patients had a new amputation (12.1%), compared with 20 of 1553 non-diabetic patients (1.2%). Amputation rates/1000 person-years were 47.9 [95% confidence interval (CI) 36.3–63.2] and 4.1 (95% CI 2.7–6.4), respectively, for diabetic patients and non-diabetic patients. Amputation increased mortality risk more than 4-fold in patients without diabetes [hazard ratio (HR) 4.6 (95% CI 2.8–7.6)] as well as in patients with diabetes [HR 4.6 (95% CI 3.3–6.4)]. No formal interaction between diabetes and amputation was found (P = 0.12). Conclusions Amputation in dialysis patients is associated with a 4-fold increased mortality risk; this mortality risk was similar for diabetes and non-diabetes patients. Importantly, the risk for amputation is 10-fold higher in DM compared with non-diabetic dialysis patients.
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Affiliation(s)
- Marielle A Schroijen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.,Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
| | - Merel van Diepen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jaap F Hamming
- Department of Vascular Surgery, Leiden University Medical Center, Leiden, the Netherlands
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Olaf M Dekkers
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.,Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
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