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Phillips K, Hazlehurst JM, Sheppard C, Bellary S, Hanif W, Karamat MA, Crowe FL, Stone A, Thomas GN, Peracha J, Fenton A, Sainsbury C, Nirantharakumar K, Dasgupta I. Inequalities in the management of diabetic kidney disease in UK primary care: A cross-sectional analysis of a large primary care database. Diabet Med 2024; 41:e15153. [PMID: 37223892 DOI: 10.1111/dme.15153] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 05/18/2023] [Accepted: 05/21/2023] [Indexed: 05/25/2023]
Abstract
AIMS To determine differences in the management of diabetic kidney disease (DKD) relevant to patient sex, ethnicity and socio-economic group in UK primary care. METHODS A cross-sectional analysis as of January 1, 2019 was undertaken using the IQVIA Medical Research Data dataset, to determine the proportion of people with DKD managed in accordance with national guidelines, stratified by demographics. Robust Poisson regression models were used to calculate adjusted risk ratios (aRR) adjusting for age, sex, ethnicity and social deprivation. RESULTS Of the 2.3 million participants, 161,278 had type 1 or 2 diabetes, of which 32,905 had DKD. Of people with DKD, 60% had albumin creatinine ratio (ACR) measured, 64% achieved blood pressure (BP, <140/90 mmHg) target, 58% achieved glycosylated haemoglobin (HbA1c, <58 mmol/mol) target, 68% prescribed renin-angiotensin-aldosterone system (RAAS) inhibitor in the previous year. Compared to men, women were less likely to have creatinine: aRR 0.99 (95% CI 0.98-0.99), ACR: aRR 0.94 (0.92-0.96), BP: aRR 0.98 (0.97-0.99), HbA1c : aRR 0.99 (0.98-0.99) and serum cholesterol: aRR 0.97 (0.96-0.98) measured; achieve BP: aRR 0.95 (0.94-0.98) or total cholesterol (<5 mmol/L) targets: aRR 0.86 (0.84-0.87); or be prescribed RAAS inhibitors: aRR 0.92 (0.90-0.94) or statins: aRR 0.94 (0.92-0.95). Compared to the least deprived areas, people from the most deprived areas were less likely to have BP measurements: aRR 0.98 (0.96-0.99); achieve BP: aRR 0.91 (0.8-0.95) or HbA1c : aRR 0.88 (0.85-0.92) targets, or be prescribed RAAS inhibitors: aRR 0.91 (0.87-0.95). Compared to people of white ethnicity; those of black ethnicity were less likely to be prescribed statins aRR 0.91 (0.85-0.97). CONCLUSIONS There are unmet needs and inequalities in the management of DKD in the UK. Addressing these could reduce the increasing human and societal cost of managing DKD.
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Affiliation(s)
- Katherine Phillips
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Jonathan M Hazlehurst
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
- Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK
- Department of Diabetes and Endocrinology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | | | - Srikanth Bellary
- Department of Diabetes and Endocrinology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- School of Health and Life Sciences, Aston University, Birmingham, UK
| | - Wasim Hanif
- Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK
- Department of Diabetes and Endocrinology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Muhammad Ali Karamat
- Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK
- Department of Diabetes and Endocrinology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Francesca L Crowe
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Anna Stone
- Royal Wolverhampton NHS Trust, Wolverhampton, UK
| | - G Neil Thomas
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Javeria Peracha
- Renal Unit, Royal Wolverhampton NHS Trust, Wolverhampton, UK
| | - Anthony Fenton
- Department of Renal Medicine, Royal Stoke University Hospital, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK
| | - Christopher Sainsbury
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
- Department of Diabetes, Gartnavel General Hospital, Glasgow, UK
| | - Krishnarajah Nirantharakumar
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
- Midlands Health Data Research UK, University of Birmingham, Birmingham, UK
| | - Indranil Dasgupta
- Department of Renal Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Warwick Medical School, University of Warwick, Coventry, UK
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Chen S, Marshall T, Jackson C, Cooper J, Crowe F, Nirantharakumar K, Saunders CL, Kirk P, Richardson S, Edwards D, Griffin S, Yau C, Barrett JK. Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England. PLoS Med 2023; 20:e1004310. [PMID: 37922316 PMCID: PMC10655992 DOI: 10.1371/journal.pmed.1004310] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 11/17/2023] [Accepted: 10/09/2023] [Indexed: 11/05/2023] Open
Abstract
BACKGROUND Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions. METHODS AND FINDINGS We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results. CONCLUSIONS Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.
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Affiliation(s)
- Sida Chen
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Tom Marshall
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | | | - Jennifer Cooper
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Francesca Crowe
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Krish Nirantharakumar
- Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Catherine L. Saunders
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Paul Kirk
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Sylvia Richardson
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Duncan Edwards
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Simon Griffin
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Christopher Yau
- Nuffield Department for Women’s & Reproductive Health, University of Oxford, Oxford, United Kingdom
- Health Data Research, Oxford, United Kingdom
| | - Jessica K. Barrett
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
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Aronson JK. When I use a word . . . . Too much healthcare-Monitoring. BMJ 2022; 379:o2605. [PMID: 36316030 DOI: 10.1136/bmj.o2605] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Affiliation(s)
- Jeffrey K Aronson
- Centre for Evidence Based Medicine, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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4
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James G, Garcia Sanchez JJ, Carrero JJ, Kumar S, Pecoits-Filho R, Heerspink HJ, Nolan S, Lam CS, Chen H, Kanda E, Kashihara N, Arnold M, Kosiborod MN, Lainscak M, Pollock C, Wheeler DC. Low Adherence to Kidney Disease: Improving Global Outcomes 2012 CKD Clinical Practice Guidelines Despite Clear Evidence of Utility. Kidney Int Rep 2022; 7:2059-2070. [PMID: 36090504 PMCID: PMC9458998 DOI: 10.1016/j.ekir.2022.05.033] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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: 11/29/2021] [Revised: 05/23/2022] [Accepted: 05/30/2022] [Indexed: 11/27/2022] Open
Affiliation(s)
- Glen James
- Global Medical Affairs, BioPharmaceuticals Medical, AstraZeneca, Cambridge, UK
| | | | - Juan Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Supriya Kumar
- Real World Data Science, BioPharmaceuticals Medical, AstraZeneca, Gaithersburg, Maryland, USA
| | - Roberto Pecoits-Filho
- School of Medicine, Pontifical Catholic University of Parana, Curitiba, Brazil
- Arbor Research Collaborative for Health, Ann Arbor, Michigan, USA
| | - Hiddo J.L. Heerspink
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, Groningen, Netherlands
| | - Stephen Nolan
- Global Medical Affairs, BioPharmaceuticals Medical, AstraZeneca, Cambridge, UK
| | - Carolyn S.P. Lam
- Department of Cardiology, National Heart Center, Singapore
- Duke-NUS Medical School, Singapore
| | - Hungta Chen
- Medical and Payer Evidence Statistics, BioPharmaceuticals Medical, AstraZeneca, Gaithersburg, Maryland, USA
| | | | | | - Matthew Arnold
- Real World Data Science, BioPharmaceuticals Medical, AstraZeneca, Cambridge, UK
| | - Mikhail N. Kosiborod
- Saint Luke’s Mid America Heart Institute, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - Mitja Lainscak
- Division of Cardiology, General Hospital Murska Sobota, Murska Sobota, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Carol Pollock
- Kolling Institute, Royal North Shore Hospital, University of Sydney, Sydney, New South Wales, Australia
| | - David C. Wheeler
- Department of Renal Medicine, University College London, London, UK
- Correspondence: David C. Wheeler, Department of Renal Medicine, University College London, Rowland Hill Street, London NW3 2PF, UK.
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Abstract
Chronic kidney disease affects approximately 10% of the population or 800 million people globally, with diabetes being the leading cause. The presence of chronic kidney disease with impaired kidney function or with albuminuria is associated with an increased risk of a progressive loss of renal function and increased risk of cardiovascular disease and excess mortality. Screening for chronic kidney disease is critically important because during the initial stages patients often have no symptoms and because we now have available recently approved multiple interventions that can reduce the high risks dramatically. Screening should be performed with regular measurement of albumin in the urine and creatinine or cystatin C in blood for estimation of kidney function. Regretfully recent data indicates that screening for albuminuria is conducted in only 20%-50% of people at risk depending on the setting. Clinicians need to perform regular screening and concomitant management of risk factors. Recent therapeutic options must be implemented to improve outcomes. Finally, a reduction in albuminuria after initiation of intervention constitutes a treatment target because it indicates improved prognosis.
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Affiliation(s)
- Peter Rossing
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Head of Complications Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Murray Epstein
- Division of Nephrology and Hypertension, University of Miami Miller School of Medicine, Miami, Fla.
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6
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Sullivan MK, Jani BD, Lees JS, Welsh CE, McConnachie A, Stanley B, Welsh P, Nicholl BI, Lyall DM, Carrero JJ, Nitsch D, Sattar N, Mair FS, Mark PB. Multimorbidity and the risk of major adverse kidney events: findings from the UK Biobank cohort. Clin Kidney J 2021; 14:2409-2419. [PMID: 34754437 PMCID: PMC8573008 DOI: 10.1093/ckj/sfab079] [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: 12/22/2020] [Indexed: 01/28/2023] Open
Abstract
Background Multimorbidity [the presence of two or more long-term conditions (LTCs)] is associated with a heightened risk of mortality, but little is known about its relationship with the risk of kidney events. Methods Associations between multimorbidity and major adverse kidney events [MAKE: the need for long-term kidney replacement therapy, doubling of serum creatinine, fall of estimated glomerular filtration rate (eGFR) to <15 mL/min/1.73 m2 or 30% decline in eGFR] were studied in 68 505 participants from the UK Biobank cohort. Participants were enrolled in the study between 2006 and 2010. Associations between LTC counts and MAKE were tested using survival analyses accounting for the competing risk of death. Results Over a median follow-up period of 12.0 years, 2963 participants had MAKE. There were associations between LTC count categories and the risk of MAKE [one LTC adjusted subhazard ratio (sHR) = 1.29, 95% confidence interval (CI) 1.15–1.45; two LTCs sHR = 1.74 (95% CI 1.55–1.96); and three or more LTCs sHR = 2.41 (95% CI 2.14–2.71)]. This finding was more pronounced when only cardiometabolic LTCs were considered [one LTC sHR = 1.58 (95% CI 1.45–1.73); two LTCs sHR = 3.17 (95% CI 2.80–3.59); and three or more LTCs sHR = 5.24 (95% CI 4.34–6.33)]. Combinations of LTCs associated with MAKE were identified. Diabetes, hypertension and coronary heart disease featured most commonly in high-risk combinations. Conclusions Multimorbidity, and in particular cardiometabolic multimorbidity, is a risk factor for MAKE. Future research should study groups of patients who are at high risk of progressive kidney disease based on the number and type of LTCs.
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Affiliation(s)
- Michael K Sullivan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Bhautesh Dinesh Jani
- General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Jennifer S Lees
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Claire E Welsh
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Alex McConnachie
- Robertson Centre for Biostatistics, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Bethany Stanley
- Robertson Centre for Biostatistics, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Paul Welsh
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Barbara I Nicholl
- General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Donald M Lyall
- Public Health, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Swedenand
| | - Dorothea Nitsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Frances S Mair
- General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Patrick B Mark
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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7
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Perera R, Stevens R, Aronson JK, Banerjee A, Evans J, Feakins BG, Fleming S, Glasziou P, Heneghan C, Hobbs FDR, Jones L, Kurtinecz M, Lasserson DS, Locock L, McLellan J, Mihaylova B, O’Callaghan CA, Oke JL, Pidduck N, Plüddemann A, Roberts N, Schlackow I, Shine B, Simons CL, Taylor CJ, Taylor KS, Verbakel JY, Bankhead C. Long-term monitoring in primary care for chronic kidney disease and chronic heart failure: a multi-method research programme. Programme Grants Appl Res 2021. [DOI: 10.3310/pgfar09100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background
Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: chronic kidney disease and chronic heart failure.
Objectives
The research questions were as follows: does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage individuals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers?
Design
Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation.
Setting
This study was set in UK primary care.
Data sources
Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature.
Participants
The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals.
Interventions
The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure).
Main outcome measures
The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring.
Results
Chronic kidney disease: serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are ≈ 2% for people with normal urine albumin, 3–5% for people with microalbuminuria (3–30 mg/mmol) and 3–12% for people with macroalbuminuria (> 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12–15% of tests in primary care. Glycaemic-control and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as ‘kidney damage’ or ‘kidney failure’ as frightening, and the term ‘chronic’ was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use ‘chronic kidney disease’ when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for individuals with an estimated glomerular filtration rate of 60–90 ml/minute/1.73 m2, aged < 70 years and without cardiovascular disease, where monitoring every 3–4 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99; specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95; specificity, 0.57). Within-person variation estimates for B-type natriuretic peptide and weight were as follows: coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For individuals, monitoring provided reassurance; future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings.
Limitations
No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear.
Conclusions
It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome.
Future work
The following future work is recommended: improve general practitioner–patient communication of early-stage renal function decline, and identify strategies to reduce the variability of natriuretic peptide.
Study registration
This study is registered as PROSPERO CRD42015017501, CRD42019134922 and CRD42016046902.
Funding
This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 9, No. 10. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Rafael Perera
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Richard Stevens
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Jeffrey K Aronson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
| | - Julie Evans
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Benjamin G Feakins
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Susannah Fleming
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Paul Glasziou
- Institute for Evidence-Based Healthcare, Faculty of Health Sciences & Medicine, Bond University, Gold Coast, QLD, Australia
| | - Carl Heneghan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - FD Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Louise Jones
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Milena Kurtinecz
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Daniel S Lasserson
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Louise Locock
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Julie McLellan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Borislava Mihaylova
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Institute of Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Jason L Oke
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Nicola Pidduck
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Annette Plüddemann
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Nia Roberts
- Bodleian Health Care Libraries, Knowledge Centre, University of Oxford, Oxford, UK
| | - Iryna Schlackow
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Brian Shine
- Department of Clinical Biochemistry, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Claire L Simons
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Clare J Taylor
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Kathryn S Taylor
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Jan Y Verbakel
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
- National Institute for Health Research (NIHR) Community Healthcare MedTech and In Vitro Diagnostics Co-operative (MIC), Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Clare Bankhead
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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Tangri N, Major RW. Risk-Based Triage for Nephrology Referrals: The Time is Now. Kidney Int Rep 2021; 6:2028-2030. [PMID: 34386651 PMCID: PMC8344117 DOI: 10.1016/j.ekir.2021.06.020] [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] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Navdeep Tangri
- Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Rupert W. Major
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- John Walls Renal Unit, University Hospitals of Leicester, Leicester, United Kingdom
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9
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Cleary F, Prieto-Merino D, Hull S, Caplin B, Nitsch D. Feasibility of evaluation of the natural history of kidney disease in the general population using electronic healthcare records. Clin Kidney J 2020; 14:1603-1609. [PMID: 34084456 PMCID: PMC8162846 DOI: 10.1093/ckj/sfaa175] [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: 04/03/2020] [Accepted: 07/06/2020] [Indexed: 11/27/2022] Open
Abstract
Background Knowledge about the nature of long-term changes in kidney function in the general population is sparse. We aim to identify whether primary care electronic healthcare records capture sufficient information to study the natural history of kidney disease. Methods The National Chronic Kidney Disease Audit database covers ∼14% of the population of England and Wales. Availability of repeat serum creatinine tests was evaluated by risk factors for chronic kidney disease (CKD) and individual changes over time in estimated glomerular filtration rate (eGFR) were estimated using linear regression. Sensitivity of estimation to method of evaluation of eGFR compared laboratory-reported eGFR and recalculated eGFR (using laboratory-reported creatinine), to uncover any impact of historical creatinine calibration issues on slope estimation. Results Twenty-five per cent of all adults, 92% of diabetics and 96% of those with confirmed CKD had at least three creatinine tests, spanning a median of 5.7 years, 6.2 years and 6.1 years, respectively. Median changes in laboratory-reported eGFR (mL/min/1.73 m2/year) were −1.32 (CKD) and −0.60 (diabetes). Median changes in recalculated eGFR were −0.98 (CKD) and −0.11 (diabetes), underestimating decline. Magnitude of underestimation (and between-patient variation in magnitude) decreased with deteriorating eGFR. For CKD Stages 3, 4 and 5 (at latest eGFR), median slopes were −1.27, −2.49 and -3.87 for laboratory-reported eGFR and −0.89, −2.26 and −3.75 for recalculated eGFR. Conclusions Evaluation of long-term changes in renal function will be possible in those at greatest risk if methods are identified to overcome creatinine calibration problems. Bias will be reduced by focussing on patients with confirmed CKD.
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Affiliation(s)
- Faye Cleary
- Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Heath, London School of Hygiene and Tropical Medicine, London, UK
| | - David Prieto-Merino
- Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Heath, London School of Hygiene and Tropical Medicine, London, UK
| | - Sally Hull
- Clinical Effectiveness Group, Centre for Primary Care and Public Health, Queen Mary University of London, London, UK
| | - Ben Caplin
- Department of Renal Medicine, University College London Medical School, London, UK
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Heath, London School of Hygiene and Tropical Medicine, London, UK
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Abstract
Chronic kidney disease (CKD) is an important public health concern in developed countries because of both the number of people affected and the high cost of care when prevention strategies are not effectively implemented. Prevention should start at the governance level with the institution of multisectoral polices supporting sustainable development goals and ensuring safe and healthy environments. Primordial prevention of CKD can be achieved through implementation of measures to ensure healthy fetal (kidney) development. Public health strategies to prevent diabetes, hypertension, and obesity as risk factors for CKD are important. These approaches are cost-effective and reduce the overall noncommunicable disease burden. Strategies to prevent nontraditional CKD risk factors, including nephrotoxin exposure, kidney stones, infections, environmental exposures, and acute kidney injury (AKI), need to be tailored to local needs and epidemiology. Early diagnosis and treatment of CKD risk factors such as diabetes, obesity, and hypertension are key for primary prevention of CKD. CKD tends to occur more frequently and to progress more rapidly among indigenous, minority, and socioeconomically disadvantaged populations. Special attention is required to meet the CKD prevention needs of these populations. Effective secondary prevention of CKD relies on screening of individuals at risk to detect and treat CKD early, using established and emerging strategies. Within high-income countries, barriers to accessing effective CKD therapies must be recognized, and public health strategies must be developed to overcome these obstacles, including training and support at the primary care level to identify individuals at risk of CKD, and appropriately implement clinical practice guidelines.
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Affiliation(s)
- Valerie A. Luyckx
- Institute of Biomedical Ethics and the History of Medicine, University of Zurich, Zurich, Switzerland
- Renal Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
- Nephrology, Cantonal Hospital Graubunden, Chur, Switzerland
| | - David Z.I. Cherney
- Division of Nephrology, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Aminu K. Bello
- Division of Nephrology and Immunology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
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