Development and validation of an electronic health record-based chronic kidney disease registry

Development and validation of a self-updating gout register from electronic health records data

OBJECTIVE

To develop an automatic gout register from electronic health records (EHRs) data.

METHODS

We analysed the EHR of all patients >18 years old from a tertiary academic hospital (2013-2022) based on six criteria: International Classification of Diseases 10 gout diagnosis, urate-lowering therapy prescription, monosodium urate crystals in joint aspiration and gout-related terms in problem lists, clinical or imaging reports. We assessed the positive and negative predictive value (PPV and NPV) of the query by chart reviews.

RESULTS

Of 2 110 902 outpatients and inpatients, 10 289 had at least one criterion for gout. The combination of joint aspiration OR diagnostic in the problem list OR≥2 other criteria created a register of 5138 patients, with a PPV of 92.4% (95% CI 88.5% to 95.0%) and an NPV of 94.3% (95% CI 91.9% to 96.0%). PPV and NPV were similar among outpatients and inpatients. Incidence was 2.9 per 1000 person-year and dropped by 30% from the COVID-19 pandemic onward. Patients with gout were on average 71.2 years old (SD 14.9), mainly male (76.5%), overweight (69.5%) and polymorbid (mean number of comorbidities of 3, IQR 1-5). More than half (57.4%) had received a urate-lowering treatment, 6.7% had a gout that led to a hospitalisation or ≥2 flares within a year and 32.9% received a rheumatology consultation.

CONCLUSION

An automatic EHR-based gout register is feasible, valid and could be used to evaluate and improve gout management. Interestingly, the register uncovered a marked underdiagnosis or under-reporting of gout since the COVID-19 pandemic.

Clinical effectiveness of oral antiviral agents for treating non-hospitalized COVID-19 patients with chronic kidney disease

OBJECTIVES

This study examined the effectiveness of nirmatrelvir plus ritonavir (NMV-r) and molnupiravir (MOV) in treating COVID-19 among chronic kidney disease (CKD) patients.

METHODS

This retrospective cohort study, using the TriNetX research network, identified stage 3-5 CKD and end-stage kidney disease (ESKD) patients with non-hospitalized COVID-19 between 1 January 2022, and 31 May 2023. Propensity score matching (PSM) was used to compare patients on NMV-r or MOV (antiviral group) against those not receiving these treatments (control group). The primary composite outcome was the cumulative hazard ratio (HR) for all-cause hospitalization or death within the 30-day follow-up.

RESULTS

After PSM, two balanced cohorts of 6,275 patients each were established. The antiviral group exhibited a lower incidence of all-cause hospitalization or mortality (5.93% vs. 9.53%; HR: 0.626; 95% CI: 0.550-0.713) than controls. Additionally, antiviral recipients were associated with a lower risk of all-cause hospitalization (HR: 0.679; 95% CI: 0.594-0.777) and mortality (HR: 0.338; 95% CI: 0.227-0.504). The beneficial effects of antiviral agents were consistent across sex, age, vaccination status, antiviral type, and CKD stage.

CONCLUSION

Oral antiviral agents could be associated with lower rates of all-cause hospitalization or death among non-hospitalized COVID-19 patients with CKD.

The ICD-9 to ICD-10 transition has not improved identification of rapidly progressing stage 3 and stage 4 chronic kidney disease patients: a diagnostic test study

BACKGROUND

The International Classification of Diseases (ICD) coding system is the industry standard tool for billing, disease classification, and epidemiology purposes. Prior research has demonstrated ICD codes to have poor accuracy, particularly in relation to rapidly progressing chronic kidney disease (CKD) patients. In 2016, the ICD system moved to revision 10. This study examines subjects in a large insurer database to determine the accuracy of ICD-10 CKD-staging codes to diagnose patients rapidly progressing towards end-stage kidney disease (ESKD).

PATIENTS AND METHODS

Serial observations of outpatient serum creatinine measurements from 2016 to 2021 of 315,903 patients were transformed to estimated glomerular filtration rate (eGFR) to identify CKD stage-3 and advanced patients diagnosed clinically (eGFR-CKD). CKD-staging codes from the same time period of 59,386 patients and used to identify stage-3 and advanced patients diagnosed by ICD-code (ICD-CKD). eGFR-CKD and ICD-CKD diagnostic accuracy was compared between a total of 334,610 patients.

RESULTS

5,618 patients qualified for the progression analysis; 72 were identified as eGFR rapid progressors; 718 had multiple codes to qualify as ICD rapid progressors. Sensitivity was 5.56%, with positive predictive value (PPV) 5.6%. 34,858 patients were diagnosed as eGFR-CKD stage-3 patients; 17,549 were also diagnosed as ICD-CKD stage-3 patients, for a sensitivity of 50.34%, with PPV of 58.71%. 4,069 patients reached eGFR-CKD stage-4 with 2,750 ICD-CKD stage-4 patients, giving a sensitivity of 67.58%, PPV of 42.43%. 959 patients reached eGFR-CKD stage-5 with 566 ICD-CKD stage-5 patients, giving a sensitivity of 59.02%, PPV of 35.85%.

CONCLUSION

This research shows that recent ICD revisions have not improved identification of rapid progressors in diagnostic accuracy, although marked increases in sensitivity for stage-3 (50.34% vs. 24.68%), and PPV in stage-3 (58.71% vs. 40.08%), stage-4 (42.43% vs. 18.52%), and stage-5 (35.85% vs. 4.51%) were observed. However, sensitivity in stage-5 compares poorly (59.02% vs. 91.05%).

Defining measures of kidney function in observational studies using routine health care data: methodological and reporting considerations

The availability of electronic health records and access to a large number of routine measurements of serum creatinine and urinary albumin enhance the possibilities for epidemiologic research in kidney disease. However, the frequency of health care use and laboratory testing is determined by health status and indication, imposing certain challenges when identifying patients with kidney injury or disease, when using markers of kidney function as covariates, or when evaluating kidney outcomes. Depending on the specific research question, this may influence the interpretation, generalizability, and/or validity of study results. This review illustrates the heterogeneity of working definitions of kidney disease in the scientific literature and discusses advantages and limitations of the most commonly used approaches using 3 examples. We summarize ways to identify and overcome possible biases and conclude by proposing a framework for reporting definitions of exposures and outcomes in studies of kidney disease using routinely collected health care data.

Association Between Kidney Dysfunction Types and Mortality Among Hospitalized Patients with Cirrhosis

BACKGROUND AND AIMS

Kidney dysfunction is associated with increased mortality among patients with cirrhosis. We investigated whether kidney dysfunction types [e.g., acute kidney injury (AKI), chronic kidney disease (CKD), and AKI on CKD] were differentially associated with inpatient mortality.

METHODS

We utilized the nationwide inpatient sample, a nationally representative database, from 2007 to 2014. We included all hospitalizations with previously validated codes for cirrhosis or associated decompensated cirrhosis diagnoses. We defined kidney dysfunction types also from previously validated codes, and we grouped hospitalizations into the following diagnoses: normal, AKI, CKD, and AKI on CKD. Our primary outcome was inpatient mortality.

RESULTS

There were 1,293,779 hospitalizations with cirrhosis sampled in this study. Of these hospitalizations, 849,193 (66%) had normal kidney function, 176,418 (14%) had AKI, 157,600 (12%) had CKD, and 110,568 (9%) had AKI on CKD. We found that the proportion of hospitalizations with AKI, CKD, and AKI on CKD increased significantly throughout the study period (p < 0.001, test for trend for all). Kidney dysfunction type was differentially associated with inpatient mortality, even after adjustment: as compared to those with CKD, normal kidney function: OR 0.75 [95 CI 0.73-0.78], AKI: OR 2.40 [95 CI 2.32-2.48], and AKI on CKD: OR 1.66 [95 CI 1.60-1.72].

DISCUSSION

Using a nationally representative cohort of all hospitalizations with cirrhosis, our study highlights that the burden of kidney dysfunction, especially AKI, among hospitalizations with cirrhosis is rising, and the inclusion of kidney dysfunction type may be an opportunity to improve prognostication.

The Influence of Diabetes Mellitus on the Risks of End-Stage Kidney Disease and Mortality After Liver Transplantation

This retrospective study aimed to investigate the effect of diabetes mellitus (DM) on the risks of end-stage kidney disease (ESKD) and post-liver transplantation (post-LT) mortality. Using data from the National Health Insurance Research Database, Taiwan, 3,489 patients who received a LT between 1 January 2005, and 31 December 2015, were enrolled in this study and divided into the pre-existing DM, post-LT DM (PLTDM), and without DM groups. All subjects were followed up from 1 year after LT to the index date for ESKD, and the occurrence of death, or until 31 December 2016. Of the 3,489 patients with LT, 1,016 had pre-existing DM, 215 had PLTDM, and 2,258 had no DM pre- or post-LT. The adjusted HRs of ESKD were 1.77 (95% Confidence Interval [CI], .78–3.99) and 2.61 (95% CI, 1.63–4.18) for PLTDM group and pre-existing DM group compared to without DM group, respectively. For the risk of death, the adjusted HRs were 1.05 (95% CI, .72–1.55) and 1.28 (95% CI, 1.04–1.59) for PLTDM group and pre-existing DM group compared to those without DM group, respectively. The sensitivity analysis for the risk of ESKD and death also revealed the consistent result. Pre-existing DM has significant increase the risk of post-LT ESKD and mortality. The role of PLTDM should be explored to explain postoperative morbidity and mortality.

[AKTIN - The German Emergency Department Data Registry - real-time data from emergency medicine : Implementation and first results from 15 emergency departments with focus on Federal Joint Committee's guidelines on acuity assessment]

BACKGROUND

Emergency care in Germany is in transition. Emergency departments (EDs) treat their patients based on symptoms and acuity. However, this perspective is not reflected in claims data. The aim of the AKTIN project was to establish an Emergency Department Data Registry as a data privacy-compliant infrastructure for the use of routine medical data.

METHODS

Data from the respective documentation systems are continuously transmitted to local data warehouses using a standardized interface. They are available for several applications such as internal reports but also multicentre studies, in compliance with data privacy regulations. Based on a 12-months period we evaluate the population with focus on acuity assessment (triage) and vital parameters in combination with presenting complaints.

RESULTS

For the period April 2018 to March 2019, 436,149 cases from 15 EDs were available. A triage level is documented in 86.0% of cases, and 70.5% were triaged within 10 min of arrival. Ten EDs collected a presenting complaint regularly (82.3%). The respective documentation of vital signs shows plausible patterns.

CONCLUSIONS

The AKTIN registry provides an almost real-time insight into German EDs, regardless of the primary documentation system and health insurance claims data. The Federal Joint Committee's requirements are largely met. Standardized presenting complaints allow for symptom-based analyses as well as health surveillance.

Value-Based Care and Kidney Disease: Emergence and Future Opportunities

The United States health care system has increasingly embraced value-based programs that reward improved outcomes and lower costs. Health care value, defined as quality per unit cost, was a major goal of the 2010 Patient Protection and Affordable Care Act amid high and rising US health care expenditures. Many early value-based programs were specifically designed for patients with end-stage renal disease (ESRD) and targeted toward dialysis facilities, including the ESRD Prospective Payment System, ESRD Quality Incentive Program, and ESRD Seamless Care Organizations. While a great deal of attention has been paid to these ESRD-focused programs, other value-based programs targeted toward hospitals and health systems may also affect the quality and costs of care for a broader population of patients with kidney disease. Value-based care for kidney disease is increasingly relevant in light of the Advancing American Kidney Health initiative, which introduces new value-based payment models: the mandatory ESRD Treatment Choices Model in 2021 and voluntary Kidney Care Choices Model in 2022. In this review article, we summarize the emergence and impact of value-based programs on the quality and costs of kidney care, with a focus on federal programs. Key opportunities in value-based kidney care include shifting the focus toward chronic kidney disease, enhancing population health management capabilities, improving quality measurement, and leveraging programs to advance health equity.

Identifying a minimum data set as a necessity to design a web-based personal health record for patients under chronic dialysis

Objective:

Many people suffer from kidney disease, and self-management is essential in these patients. Personal health record (PHR) can be used as a tool to improve self-management in these patients. This study aimed to identify a minimum data set (MDS) of PHR in dialysis patients.

Methods:

This descriptive and cross-sectional study was conducted in 2019, and national and international scientific literature entitled “Personal Health Record,” “Electronic Personal Health Record,” “Dialysis Patient Portal,” “Dialysis Health Record,” and “Dialysis Information Needs” by content analysis method was reviewed. A questionnaire with 14 items was designed to examine patients’ problems and data needs based on the review of scientific literature and web-based PHRs. Based on the patients’ survey and the review of scientific literature, a questionnaire with 114 questions was designed. Finally, with experts’ opinions, data elements were determined.

Results:

An MDS for developing web-based PHR for patients under chronic dialysis was created with 17 data classes including demographic information, insurance information, contact information in case of emergency, information on dialysis sessions, physicians information, dialysis center information, information on individual measured values (blood pressure, blood sugar, and weight), disease history information, information on surgical procedures and operations, history of visits, allergies, vaccinations, family history, drugs, laboratory tests, diet, and education materials for the patient.

Conclusion:

In this study, an MDS was developed for a web-based PHR for dialysis patients. The use of standard data can help collect the data that is essential to improve the patient’s health and track his medical condition.

Effectiveness and Safety of Apixaban versus Warfarin in Venous Thromboembolism Patients with Chronic Kidney Disease

There has been limited evidence reported about the outcomes of oral anticoagulants among patients with venous thromboembolism (VTE) and chronic kidney disease (CKD), especially those with stage V/end-stage renal disease (ESRD). This retrospective cohort analysis of five U.S. claims databases evaluated the risk of recurrent VTE, major bleeding (MB), and clinically relevant nonmajor bleeding (CRNMB) for apixaban versus warfarin among VTE patients diagnosed with CKD, including ESRD. Inverse probability treatment weighting (IPTW) was used to balance patient characteristics between treatment cohorts. Hazard ratios (HRs) were calculated for recurrent VTE, MB, and CRNMB among patients with CKD who experienced an index VTE. An interaction analysis was conducted to evaluate treatment effects across different stages of CKD. A total of 29,790 VTE patients with CKD were selected for analyses, of whom 10,669 (35.8%) initiated apixaban and 19,121 (64.2%) initiated warfarin. Among IPTW-balanced patient cohorts, the apixaban group had significantly lower risk of recurrent VTE (HR: 0.78; 95% confidence interval [CI]: 0.66-0.92), MB (HR: 0.76; 95% CI: 0.65-0.88), and CRNMB (HR: 0.86; 95% CI: 0.80-0.93) than the warfarin group. When stratified by CKD stage (stage I/II: 8.2%; stage III: 49.4%; stage IV: 12.8%; stage V/ESRD: 12.0%; stage unspecified: 17.6%), no significant interaction was observed for effects of apixaban versus warfarin on recurrent VTE or MB. In summary, apixaban was associated with a significantly lower risk of recurrent VTE and MB than warfarin among VTE patients with CKD. CKD stages did not have significant impact on treatment effects for recurrent VTE and MB.

Big Data in Nephrology

A huge array of data in nephrology is collected through patient registries, large epidemiological studies, electronic health records, administrative claims, clinical trial repositories, mobile health devices and molecular databases. Application of these big data, particularly using machine-learning algorithms, provides a unique opportunity to obtain novel insights into kidney diseases, facilitate personalized medicine and improve patient care. Efforts to make large volumes of data freely accessible to the scientific community, increased awareness of the importance of data sharing and the availability of advanced computing algorithms will facilitate the use of big data in nephrology. However, challenges exist in accessing, harmonizing and integrating datasets in different formats from disparate sources, improving data quality and ensuring that data are secure and the rights and privacy of patients and research participants are protected. In addition, the optimism for data-driven breakthroughs in medicine is tempered by scepticism about the accuracy of calibration and prediction from in silico techniques. Machine-learning algorithms designed to study kidney health and diseases must be able to handle the nuances of this specialty, must adapt as medical practice continually evolves, and must have global and prospective applicability for external and future datasets.

Redesigning Kidney Disease Care to Improve Value Delivery

This article describes the articulation, development, and deployment of a machine learning (ML) model-driven value solution for chronic kidney disease (CKD) in a health system. The ML model activated an electronic medical record (EMR) trigger that alerted CKD patients to seek primary care. Simultaneously, primary care physicians (PCPs) received an alert that a CKD patient needed an appointment. Using structured checklists, PCPs addressed and controlled comorbid conditions, reconciled drug dosing and choice to CKD stage, and ordered prespecified laboratory and imaging tests pertinent to CKD. After completion of checklist prescribed tasks, PCPs referred patients to nephrology. CKD patients had multiple comorbidities and ML recognition of CKD provided a facile insight into comorbid burden. Operational results of this program have exceeded expectations and the program is being expanded to the entire health system. This paradigm of ML-driven, checklist-enabled care can be used agnostic of EMR platform to deliver value in CKD through structured engagement of complexity in health systems.

Combination of Thigh Circumference and Indices of Central Obesity Helps Predict Incident Chronic Kidney Disease: A 14-Year Prospective Cohort Study Using a Three-Dimensional Body Laser Scanner

OBJECTIVE

Obesity, high body mass index, and visceral fat accumulation are associated with renal diseases. However, the association between body measurements and chronic kidney disease (CKD) is still unclear.

METHODS

A cohort of 7,825 participants scheduled for follow-up of CKD was recruited from 2000 to 2008 in Taiwan. A questionnaire was developed to collect the basic demographics, lifestyle variables, personal disease history, and family disease history of the participants. A 3-dimensional body surface scanning system was used to take their body measurements. The participants underwent an average follow-up of 14.3 years for evaluation of the incidence of CKD. A multiple Cox regression model was built.

RESULTS

Three body measurements, namely chest width (hazard ratio [HR] 1.059, 95% confidence interval [CI] 1.011-1.110), waist circumference (HR 1.017, 95% CI 1.006-1.029), and thigh circumference (HR 0.941, 95% CI 0.922-0.961), were significantly associated with CKD. Two combinations of body measurements, namely the waist-to-thigh ratio and chest-to-thigh ratio, were derived to predict the occurrence of CKD. Participants with the highest quartile of waist-to-thigh ratio and chest-to-thigh ratio had a 2.175-fold and 2.182-fold risk of developing CKD, respectively.

CONCLUSIONS

This study suggests that along with central obesity, body limb measurements can be used as an indicator to predict the occurrence of CKD. The effects of limb measurements on CKD could help provide an innovative perspective regarding the intervention to be developed for the treatment of CKD and a preventive medicine for high-risk individuals. The association of thigh circumference with CKD warrants further investigation.

Proton-pump inhibitor vs. H2-receptor blocker use and overall risk of CKD progression

Background

The relationship between proton-pump inhibitor (PPI) use and chronic kidney disease (CKD) progression remains controversial. Specifically, there is a lack of data evaluating renal outcomes in established CKD patients. The aim of our study is to determine the risk of progression to end-stage kidney disease (ESKD) or death amongst CKD patients on PPI, histamine-2 receptor blocker (H2B), or no anti-acid therapy.

Methods

Using our CKD registry, we evaluated the relationship between PPI and H2B use and outcomes amongst patients with CKD (eGFR < 60), with at least 2 PCP visits in the year prior. A Cox proportional hazards model was used to evaluate the relationship between medication groups and overall mortality, while competing risks regression models were used to determine the risk of ESKD with death as a competing risk.

Results

25,455 patients met inclusion criteria and were stratified according to medication group: no antacid therapy (15,961), PPI use (8646), or H2B use (848). At 4 years, the cumulative incidence of ESKD with death as a competing risk was 2.0% (95% CI: 1.7, 2.4), 1.5% (0.8, 2.8), and 1.6%(1.4, 1.9) among PPI, H2B, and no medication respectively (P = 0.22). The cumulative incidence of death with ESKD as a competing risk was 17.6% (95% CI: 16.6, 18.6), 16.7% (13.7, 19.8), and 17.3% (16.6, 18.0) (P = 0.71).

Conclusions

Use of PPI in a CKD population was not associated with increased mortality or progression to ESKD when compared to H2 blocker and to no acid suppressing therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02449-0.

Electronic Medical Record Risk Modeling of Cardiovascular Outcomes Among Patients with Type 2 Diabetes

INTRODUCTION

Increased utilization of electronic health records (EHR) has enriched databases for creating risk models. We used machine learning techniques to develop an EHR-based risk model locally fitted to patients with type 2 diabetes mellitus (T2DM) for predicting cardiovascular disease.

METHODS

This retrospective observational study was conducted within Ochsner Health, Louisiana, USA, between 2013-2017. Data analysis included 6245 patients who had two outpatient diagnoses of T2DM recorded on separate days or a diagnosis recorded during an inpatient encounter. Baseline clinical data were limited to 180 days before the index diagnosis. Cardiovascular outcomes were coronary heart disease (CHD), heart failure and stroke. Machine learning approaches were used to select predictor variables into Cox proportional hazards models for each outcome. Locally fit equations were compared to "generalized" risk equations (RECODe, AS-CVD, QRISK3) using model discrimination and calibration.

RESULTS

Among factors identified in the Ochsner (n = 11), RECODe (n = 14), AS-CVD (n = 15) and QRISK3 (n = 23), only age was common to all four risk equations. The Ochsner model had high internal discrimination for CHD (C-statistics 0.85) and better discrimination than RECODe (C-statistics 0.45), the QRISK3 (C-statistics 0.72) and AS-CVD (C-statistics 0.54).

CONCLUSIONS

The Ochsner model overestimated 5-year CHD risk, but had relatively higher calibration than the other models in CHD. Risk equations fitted for local populations improved cardiovascular risk stratification for patients with T2DM. Application of machine learning simplified the models compared to "generalized" risk equations.

Data Challenges in Addressing Chronic Kidney Disease in Low- and Lower-Middle-Income Countries

The burden of chronic kidney disease (CKD) is growing globally, particularly in low- and lower-middle-income countries (LLMICs) where access to treatment is poor and the largest increases in disease burden will occur. The individual and societal costs of kidney disease are well recognized, especially in developed health care systems where treatments for the advanced stages of CKD are more readily available. The consequences of CKD are potentially more catastrophic in developing health care systems where such resources are often lacking. Central to addressing this challenge is the availability of data to understand disease burden and ensure that investments in treatments and health resources are effective at a local level. Use of routinely collected administrative data is helpful in this regard, however, the barriers to developing a more systematic focus on data collection should not be underestimated. This article reviews the current tools that have been used to measure the burden of CKD and considers limitations regarding their use in LLMICs. A review of the literature investigating the use of registries, disease specific databases and administrative data to identify populations with CKD in LLMICs, which indicate these to be underused resources, is included. Suggestions regarding the potential use of administrative data for measuring CKD burden in LLMICs are explored.

Electronic health record-based disease surveillance systems: A systematic literature review on challenges and solutions

OBJECTIVE

Disease surveillance systems are expanding using electronic health records (EHRs). However, there are many challenges in this regard. In the present study, the solutions and challenges of implementing EHR-based disease surveillance systems (EHR-DS) have been reviewed.

MATERIALS AND METHODS

We searched the related keywords in ProQuest, PubMed, Web of Science, Cochrane Library, Embase, and Scopus. Then, we assessed and selected articles using the inclusion and exclusion criteria and, finally, classified the identified solutions and challenges.

RESULTS

Finally, 50 studies were included, and 52 unique solutions and 47 challenges were organized into 6 main themes (policy and regulatory, technical, management, standardization, financial, and data quality). The results indicate that due to the multifaceted nature of the challenges, the implementation of EHR-DS is not low cost and easy to implement and requires a variety of interventions. On the one hand, the most common challenges include the need to invest significant time and resources; the poor data quality in EHRs; difficulty in analyzing, cleaning, and accessing unstructured data; data privacy and security; and the lack of interoperability standards. On the other hand, the most common solutions are the use of natural language processing and machine learning algorithms for unstructured data; the use of appropriate technical solutions for data retrieval, extraction, identification, and visualization; the collaboration of health and clinical departments to access data; standardizing EHR content for public health; and using a unique health identifier for individuals.

CONCLUSIONS

EHR systems have an important role in modernizing disease surveillance systems. However, there are many problems and challenges facing the development and implementation of EHR-DS that need to be appropriately addressed.

Electronic Health Record (EHR) Abstraction

The purpose of electronic health record (EHR) abstraction includes collection of data related to administrative coding functions, quality improvement, clinical registry functions and clinical research. This article examines the different abstraction methods, such as manual abstraction, simple query, and natural language processing (NLP). It also discusses the advantages and disadvantages of each of those methods. The process used for successful EHR abstraction is also discussed and includes the scope and resources needed (time, budget, type of healthcare professionals RHIA, RHIT, etc.). The relationship between EHRs and the clinical registry is also examined with a focus on validity of the data extracted. Future research in this area to examine abstraction methods across hospitals who do data abstraction are being finalized for a future publication.

Impact of pre-dialysis nephrology care engagement and decision-making on provider and patient action toward permanent vascular access

BACKGROUND

While catheters are often thought the result of emergency hemodialysis (HD) initiation among patients with little or no pre-dialysis nephrology care, the role of patient level of engagement in care and modality decision-making have not been fully explored.

METHODS

This is a retrospective medical record review of adults (age 18-89 years) who received care in academically affiliated private practice, public hospital, or Veterans Administration settings prior to initiating HD with a catheter between 10/1/2011 and 9/30/2012. Primary predictors were level of patient engagement in nephrology care within 6 months of HD initiation and timing of modality decision-making. Primary outcomes were provider action (referral) and any patient action (evaluation by a vascular surgeon, vein mapping or vascular surgery) toward [arteriovenous fistula or graft, (AVF/AVG)] creation.

RESULTS

Among 92 incident HD patients, 66% (n = 61) initiated HD via catheter, of whom 34% (n = 21) had ideal engagement in care but 42% (n = 25) had no documented decision. Providers referred 48% (n = 29) of patients for AVF/AVG, of whom 72% (n = 21) took any action. Ideal engagement in care predicted provider action (adjusted OR 13.7 [95% CI 1.08, 175.1], p = 0.04), but no level of engagement in care predicted patient action (p > 0.3). Compared to patients with no documented decision, those with documented decisions within 3, 3-12, or more than 12 months before initiating dialysis were more likely to have provider action toward AVF/AVG (adjusted OR [95% CI]: 9.0 [1.4,55.6], p = 0.2, 37.6 [3.3423.4] p = 0.003, and 4.8 [0.8, 30.6], p = 0.1, respectively); and patient action (adjusted OR [95% CI]: 18.7 [2.3, 149.0], p = 0.006, 20.4 [2.6, 160.0], p = 0.004, and 6.2 [0.9, 44.0], p = 0.07, respectively).

CONCLUSIONS

Timing of patient modality decision-making, but not level of engagement in pre-dialysis nephrology care, was predictive of patient and provider action toward AVF/AVG Interventions addressing patients' psychological preparation for dialysis are needed.

Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review

Background

Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research.

Objective

This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions.

Methods

A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines.

Results

A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance.

Conclusions

Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

Improving hepatitis B vaccination rates for advanced chronic kidney disease patients: a quality improvement initiative

Introduction

Chronic kidney disease (CKD) patients are vulnerable to hepatitis B, and immunization prior to end stage kidney disease is recommended to optimize seroconversion. Our institution undertook a process improvement approach to increase hepatitis B vaccination in stage 4 and 5 CKD patients.

Methods

Four strategies were utilized such as: (1) Electronic health record (EHR)-based CKD registry to identify patients, (2) EHR-based physician/nurse reminders, (3) a co-located nurse appointment for vaccine administration, and (4) information sharing and provider awareness effort. The CKD registry was utilized to identify patients with stage 4 or 5 CKD, with at least two clinic visits in the prior 2 years, who had not received the hepatitis B vaccine or did not have serologic evidence of immunity. Target monthly vaccination rate was set at 75%, based on clinic leadership, nephrologist, and nurse consensus.

Results

A total of 239 patients were included in the study period, from November 2018 to January 2019 (observation period) and from February 2019 to September 2019 (intervention period). Monthly vaccination rate improved from 48% in November 2018 to the target rate of 75% by the end of the intervention (August and September 2019). There was a statistically significant increase from the rate of vaccination at a unique patient level in the first month of the baseline period, compared to the last month of the intervention period (51 vs. 75% p = 0.03).

Conclusions

Utilizing a nurse-led approach to hepatitis B vaccination, coupled with EHR-based tools, along with continuous monitoring of performance, helped to improve hepatitis B vaccination among CKD stage 4 and 5 patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10157-020-02013-4.

Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019

Objective

To describe the design, implementation, and utilization of electronic health record (EHR)-based digital health surveillance strategies used to manage the coronavirus disease 2019 (COVID-19) pandemic and to ensure delivery of high-quality clinical care, such as case identification, remote monitoring, telemedicine services, and recruitment to clinical trials at Mayo Clinic.

Methods

The design and implementation work described in this report was performed at Mayo Clinic, a large multistate integrated health care system with more than 1.5 million annual patient visits that uses the Epic EHR system. Rule-based live registries were designed in the EHR system to classify patients who currently test positive for COVID-19, patients who test positive but have recovered from COVID-19, patients who are thought to have COVID-19 but do not yet meet clinical diagnostic criteria, patients who test negative for COVID-19, and patients who exceed a risk score for serious complications from COVID-19.

Results

By use of registries, custom dashboards and operational reports were developed to provide a daily high-level summary for clinical practice use and up-to-date information to manage individual patients affected by COVID-19, including support of case identification, contact isolation, and other care management tasks.

Conclusion

We developed and implemented a systematic approach to the use of EHR patient registries to manage the COVID-19 pandemic that proved feasible and useful in a large multistate group clinical practice. The key to harnessing the potential of digital surveillance tools to promote patient-centered care during the COVID-19 pandemic was to use the registry data, reports, and dashboards as informatics tools to inform decision-making.

Incidence of Myocardial Infarction and Cerebrovascular Accident in Patients With Hidradenitis Suppurativa

Importance

Although hidradenitis suppurativa (HS) is associated with several cardiovascular risk mediators, information on the risk of myocardial infarction (MI) and cerebrovascular accident (CVA) in this population is sparse.

Objective

To compare risk of MI, CVA, and composite disease (MI or CVA) in patients with HS, stratified by use of biologic agents, with controls without HS.

Design, Setting, and Participants

A retrospective cohort analysis was conducted between January 1, 1999, and April 1, 2019, using a demographically heterogeneous population-based sample of over 56 million unique patients. Individuals with HS (n = 49 862) and without HS (n = 1 421 223) were identified using electronic health records data.

Main Outcomes and Measures

The primary outcome was incidence of composite MI or CVA.

Results

Of the 49 862 patients with HS, 37 981 were women (76.2%), 29 711 were white (59.6%), and mean (SD) age was 38.3 (13.3) years. Crude incidence rate of composite disease was 6.6 (95% CI, 6.3-7.0) per 1000 person-years in patients with HS compared with 6.8 (95% CI, 6.7-6.8) per 1000 person-years in controls. In patients with HS, crude incidence rates were 2.9 (95% CI, 2.6-3.1) per 1000 person-years for MI alone and 4.1 (95% CI, 3.9-4.4) per 1000 person-years for CVA alone compared with 3.2 (95% CI, 3.18-3.25) per 1000 person-years for MI alone in control patients and 4.1 (95% CI, 4.0-4.1) per 1000 person-years for CVA alone in control patients. In adjusted analysis, patients with HS had a 23% increased risk of composite disease (hazard ratio [HR], 1.23; 95% CI, 1.17-1.30; P < .001) and a similar increase in the risk of MI alone (HR, 1.21; 95% CI, 1.12-1.32; P < .001) and CVA alone (HR, 1.22; 95% CI, 1.14-1.31; P < .001) compared with control patients. The relative difference in composite MI or CVA risk between patients with HS and controls was highest among younger patients HR in subgroup aged 18-29 years: 1.67; 95% CI, 1.37-2.03).

Conclusions and Relevance

Patients with HS appear to have an increased risk of MI and CVA. Early management of modifiable cardiovascular risk mediators may be warranted in patients with HS.

Agreement Between Administrative Database and Medical Chart Review for the Prediction of Chronic Kidney Disease G category

Background

Chronic kidney disease (CKD) is a major health issue and cardiovascular risk factor. Validity assessment of administrative data for the detection of CKD in research for drug benefit and risk using real-world data is important. Existing algorithms have limitations and we need to develop new algorithms using administrative data, giving the importance of drug benefit/risk ratio in real world.

Objective

The aim of this study was to validate a predictive algorithm for CKD GFR category 4-5 (eGFR < 30 mL/min/1.73 m² but not receiving dialysis or CKD G4-5ND) using the administrative databases of the province of Quebec relative to estimated glomerular filtration rate (eGFR) as a reference standard.

Design

This is a retrospective cohort study using chart collection and administrative databases.

Setting

The study was conducted in a community outpatient medical clinic and pre-dialysis outpatient clinic in downtown Montreal and rural area.

Patients

Patient medical files with at least 2 serum creatinine measures (up to 1 year apart) between September 1, 2013, and June 30, 2015, were reviewed consecutively (going back in time from the day we started the study). We excluded patients with end-stage renal disease on dialysis. The study was started in September 2013.

Measurement

Glomerular filtration rate was estimated using the CKD Epidemiological Collaboration (CKD-EPI) from each patient's file. Several algorithms were developed using 3 administrative databases with different combinations of physician claims (diagnostics and number of visits) and hospital discharge data in the 5 years prior to the cohort entry, as well as specific drug use and medical intervention in preparation for dialysis in the 2 years prior to the cohort entry.

Methods

Chart data were used to assess eGFR. The validity of various algorithms for detection of CKD groups was assessed with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Results

A total of 434 medical files were reviewed; mean age of patients was 74.2 ± 10.6 years, and 83% were older than 65 years. Sensitivity of algorithm #3 (diagnosis within 2-5 years and/or specific drug use within 2 years and nephrologist visit ≥4 within 2-5 years) in identification of CKD G4-5ND ranged from 82.5% to 89.0%, specificity from 97.1% to 98.9% with PPV and NPV ranging from 94.5% to 97.7% and 91.1% to 94.2%, respectively. The subsequent subgroup analysis (diabetes, hypertension, and <65 and ≥65 years) and also the comparisons of predicted prevalence in a cohort of older adults relative to published data emphasized the accuracy of our algorithm for patients with severe CKD (CKD G4-5ND).

Limitations

Our cohort comprised mostly older adults, and results may not be generalizable to all adults. Participants with CKD without 2 serum creatinine measurements up to 1 year apart were excluded.

Conclusions

The case definition of severe CKD G4-5ND derived from an algorithm using diagnosis code, drug use, and nephrologist visits from administrative databases is a valid algorithm compared with medical chart reviews in older adults.

Burden and Cost of Caring for US Veterans With CKD: Initial Findings From the VA Renal Information System (VA-REINS)

Kidney disease is a common, complex, costly, and life-limiting condition. Most kidney disease registries or information systems have been limited to single institutions or regions. A national US Department of Veterans Affairs (VA) Renal Information System (VA-REINS) was recently developed. We describe its creation and present key initial findings related to chronic kidney disease (CKD) without kidney replacement therapy (KRT). Data from the VA's Corporate Data Warehouse were processed and linked with national Medicare data for patients with CKD receiving KRT. Operational definitions for VA user, CKD, acute kidney injury, and kidney failure were developed. Among 7 million VA users in fiscal year 2014, CKD was identified using either a strict or liberal operational definition in 1.1 million (16.4%) and 2.5 million (36.3%) veterans, respectively. Most were identified using an estimated glomerular filtration rate laboratory phenotype, some through proteinuria assessment, and very few through International Classification of Diseases, Ninth Revision coding. The VA spent ∼$18 billion for the care of patients with CKD without KRT, most of which was for CKD stage 3, with higher per-patient costs by CKD stage. VA-REINS can be leveraged for disease surveillance, population health management, and improving the quality and value of care, thereby enhancing VA's capacity as a patient-centered learning health system for US veterans.

Does the Encounter Type Matter When Defining Diabetes Complications in Electronic Health Records?

BACKGROUND

Electronic health records (EHRs) and claims records are widely used in defining type 2 diabetes mellitus (T2DM) complications across different types of health care encounters.

OBJECTIVE

This study investigates whether using different EHR encounter types to define diabetes complications may lead to different results when examining associations between diabetes complications and their risk factors in patients with T2DM.

RESEARCH DESIGN

The study cohort of 64,855 adult patients with T2DM was created from EHR data from the Research Action for Health Network (REACHnet), using the Surveillance Prevention, and Management of Diabetes Mellitus (SUPREME-DM) definitions. Incidence of coronary heart disease (CHD) and stroke events were identified using International Classification of Diseases (ICD)-9/10 codes and grouped by encounter types: (1) inpatient (IP) or emergency department (ED) type, or (2) any health care encounter type. Cox proportional hazards regression was used to estimate associations between diabetes complications (ie, CHD and stroke) and risk factors (ie, low-density lipoprotein cholesterol and hemoglobin A1c).

RESULTS

The incidence rates of CHD and stroke in all health care settings were more than twice the incidence rates of CHD and stroke in IP/ED settings. The age-adjusted and multivariable-adjusted hazard ratios for incident CHD and stroke across different levels of low-density lipoprotein cholesterol and hemoglobin A1c were similar between IP/ED and all settings.

CONCLUSION

While there are large variations in incidence rates of CHD and stroke as absolute risks, the associations between both CHD and stroke and their respective risk factors measured by hazard ratios as relative risks are similar, regardless of alternative definitions.

Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data

Background

Quantifying the burden of multimorbidity for healthcare research using administrative data has been constrained. Existing measures incompletely capture chronic conditions of relevance and are narrowly focused on risk-adjustment for mortality, healthcare cost or utilization. Moreover, the measures have not undergone a rigorous review for how accurately the components, specifically the International Classification of Diseases, Ninth Revision (ICD-9) codes, represent the chronic conditions that comprise the measures. We performed a comprehensive, structured literature review of research studies on the accuracy of ICD-9 codes validated using external sources across an inventory of 81 chronic conditions. The conditions as a weighted measure set have previously been demonstrated to impact not only mortality but also physical and mental health-related quality of life.

Methods

For each of 81 conditions we performed a structured literature search with the goal to identify 1) studies that externally validate ICD-9 codes mapped to each chronic condition against an external source of data, and 2) the accuracy of ICD-9 codes reported in the identified validation studies. The primary measure of accuracy was the positive predictive value (PPV). We also reported negative predictive value (NPV), sensitivity, specificity, and kappa statistics when available. We searched PubMed and Google Scholar for studies published before June 2019.

Results

We identified studies with validation statistics of ICD-9 codes for 51 (64%) of 81 conditions. Most of the studies (47/51 or 92%) used medical chart review as the external reference standard. Of the validated using medical chart review, the median (range) of mean PPVs was 85% (39–100%) and NPVs was 91% (41–100%). Most conditions had at least one validation study reporting PPV ≥70%.

Conclusions

To help facilitate the use of patient-centered measures of multimorbidity in administrative data, this review provides the accuracy of ICD-9 codes for chronic conditions that impact a universally valued patient-centered outcome: health-related quality of life. These findings will assist health services studies that measure chronic disease burden and risk-adjust for comorbidity and multimorbidity using patient-centered outcomes in administrative data.

Acute kidney injury in critically ill children and 5-year hypertension

BACKGROUND

To develop a pediatric-specific hypertension algorithm using administrative data and use it to evaluate the association between acute kidney injury (AKI) in the intensive care unit (ICU) and hypertension diagnosis 5 years post-discharge.

METHODS

Two-center retrospective cohort study of children (≤ 18 years old) admitted to the pediatric ICU in Montreal, Canada, between 2003 and 2005 and followed until 2010. Patients with a valid healthcare number and without end-stage renal disease were included. Patients who could not be merged with the provincial database, did not survive admission, underwent cardiac surgery, had pre-existing renal disease associated with hypertension or a prior diagnosis of hypertension were excluded. AKI defined using the Kidney Disease: Improving Global Outcomes (KDIGO) definition. Using diagnostic codes and medications from administrative data, novel pediatric-specific hypertension definitions were designed. Both the evaluation of the prevalence of hypertension diagnosis and the association between AKI and hypertension occurred.

RESULTS

Nineteen hundred and seventy eight patients were included (median age at admission [interquartile range] 4.3 years [1.1-11.8], 44% female, 325 (16.4%) developed AKI). Of these patients, 130 (7%) had a hypertension diagnosis 5 years after discharge. Patients with AKI had a higher prevalence of hypertension diagnosis [non-AKI: 84/1653 (5.1%) vs. AKI: 46/325 (14.2%), p < .001]. Children with AKI had a higher adjusted risk of hypertension diagnosis (hazard ratio [95% confidence interval] 2.19 [1.47-3.26]).

CONCLUSIONS

Children admitted to the ICU have a high prevalence of hypertension post-discharge and children with AKI have over two times higher risk of hypertension compared to those with no AKI.

J-CKD-DB: a nationwide multicentre electronic health record-based chronic kidney disease database in Japan

The Japan Chronic Kidney Disease (CKD) Database (J-CKD-DB) is a large-scale, nation-wide registry based on electronic health record (EHR) data from participating university hospitals. Using a standardized exchangeable information storage, the J-CKD-DB succeeded to efficiently collect clinical data of CKD patients across hospitals despite their different EHR systems. CKD was defined as dipstick proteinuria ≥1+ and/or estimated glomerular filtration rate <60 mL/min/1.73 m² base on both out- and inpatient laboratory data. As an initial analysis, we analyzed 39,121 CKD outpatients (median age was 71 years, 54.7% were men, median eGFR was 51.3 mL/min/1.73 m²) and observed that the number of patients with a CKD stage G1, G2, G3a, G3b, G4 and G5 were 1,001 (2.6%), 2,612 (6.7%), 23,333 (59.6%), 8,357 (21.4%), 2,710 (6.9%) and 1,108 (2.8%), respectively. According to the KDIGO risk classification, there were 30.1% and 25.5% of male and female patients with CKD at very high-risk, respectively. As the information from every clinical encounter from those participating hospitals will be continuously updated with an anonymized patient ID, the J-CKD-DB will be a dynamic registry of Japanese CKD patients by expanding and linking with other existing databases and a platform for a number of cross-sectional and prospective analyses to answer important clinical questions in CKD care.

Serum magnesium, mortality and disease progression in chronic kidney disease

Introduction

Magnesium disorders are commonly encountered in chronic kidney disease (CKD) and are typically a consequence of decreased kidney function or frequently prescribed medications such as diuretics and proton pump inhibitors. While hypomagnesemia has been linked with increased mortality, the association between elevated magnesium levels and mortality is not clearly defined. Additionally, associations between magnesium disorders, type of death, and CKD progression have not been reported. Therefore, we studied the associations between magnesium levels, CKD progression, mortality, and cause specific deaths in patients with CKD.

Methods

Using the Cleveland Clinic CKD registry, we identified 10,568 patients with estimated Glomerular Filtration Rate (eGFR) between 15 and 59 ml/min/1.73 m² in this range for a minimum of 3 months with a measured magnesium level. We categorized subjects into 3 groups based on these magnesium levels (≤ 1.7, 1.7–2.6 and > 2.6 mg/dl) and applied cox regression modeling and competing risk models to identify associations with overall and cause-specific mortality. We also evaluated the association between magnesium level and slope of eGFR using mixed models.

Results

During a median follow-up of 3.7 years, 4656 (44%) patients died. After adjusting for relevant covariates, a magnesium level < 1.7 mg/dl (vs. 1.7–2.6 mg/dl) was associated with higher overall mortality (HR = 1.14, 95% CI: 1.04, 1.24), and with higher sub-distribution hazards for non-cardiovascular non-malignancy mortality (HR = 1.29, 95% CI: 1.12, 1.49). Magnesium levels > 2.6 mg/dl (vs. 1.7–2.6 mg/dl) was associated with a higher risk of all-cause death only (HR = 1.23, 95% CI: 1.03, 1.48). We found similar results when evaluating magnesium as a continuous measure. There were no significant differences in the slope of eGFR across all three magnesium groups (p = 0.10).

Conclusions

In patients with CKD stage 3 and 4, hypomagnesemia was associated with higher all-cause and non-cardiovascular non-malignancy mortality. Hypermagnesemia was associated with higher all-cause mortality. Neither hypo nor hypermagnesemia were associated with an increased risk of CKD progression.

Clinical Characteristics of and Risk Factors for Chronic Kidney Disease Among Adults and Children: An Analysis of the CURE-CKD Registry

Importance

Chronic kidney disease (CKD) is serious and common, yet recognition and public health responses are limited.

Objective

To describe clinical features of, prevalence of, major risk factors for, and care for CKD among patients treated in 2 large US health care systems.

Design, Setting, and Participants

This cohort study collected data from the Center for Kidney Disease Research, Education, and Hope (CURE-CKD) registry, an electronic health record-based registry jointly curated and sponsored by Providence St Joseph Health and the University of California, Los Angeles. Patients were adults and children with CKD (excluding end-stage kidney disease) and adults at risk of CKD (ie, with diabetes, hypertension, or prediabetes) identified by laboratory values, vital signs, prescriptions, and administrative codes. Data were collected from January 2006 through December 2017, with analyses performed from March 2019 through November 2019.

Exposures

Diabetes, hypertension, and prediabetes.

Main Outcomes and Measures

Clinical and demographic characteristics, prevalence, and prescribed medications.

Results

Of 2 625 963 adults and children in the sample, 606 064 adults (23.1%) with CKD had a median (interquartile range [IQR]) age of 70 (59-81) years, with 338 785 women (55.9%) and 434 474 non-Latino white individuals (71.7%). A total of 12 591 children (0.4%) with CKD had a median (IQR) age of 6 (1-13) years, with 7079 girls (56.2%) and 6653 non-Latino white children (52.8%). Median (IQR) estimated glomerular filtration rate was 53 (41-61) mL/min/1.73 m2 among adults and 70 (50-95) mL/min/1.73 m2 in children. Prevalence rates for CKD in adults were 4.8% overall (606 064 of 12 669 700) with 1.6% (93 644 of 6 011 129) during 2006 to 2009, 5.7% (393 455 of 6 903 084) during 2010 to 2013, and 8.4% (683 574 of 8 179 860) during 2014 to 2017 (P < .001). A total of 226 693 patients (37.4%) had category 3a CKD; 100 239 (16.5%), category 3b CKD; 39 125 (6.5%), category 4 CKD; and 20 328 (3.4%), category 5 CKD. Among adults with CKD, albuminuria and proteinuria assessments were available in 52 551 (8.7%) and 25 035 (4.1%) patients, respectively. A renin-angiotensin system inhibitor was prescribed to 124 575 patients (20.6%), and 204 307 (33.7%) received nonsteroidal anti-inflammatory drugs or proton pump inhibitors. Of 1 973 258 adults (75.1%) at risk, one-quarter had diabetes or prediabetes (512 299 [26.0%]), nearly half had hypertension (955 812 [48.4%]), and one-quarter had both hypertension and diabetes or prediabetes (505 147 [25.6%]).

Conclusions and Relevance

This registry-based cohort study revealed a burgeoning number of patients with CKD and its major risk factors. Rates of identification and use of kidney protective agents were low, while potential nephrotoxin use was widespread, underscoring the pressing need for practice-based improvements in CKD prevention, recognition, and treatment.

Rationale and design of a multicenter Chronic Kidney Disease (CKD) and at-risk for CKD electronic health records-based registry: CURE-CKD

BACKGROUND

Chronic kidney disease (CKD) is a global public health problem, exhibiting sharp increases in incidence, prevalence, and attributable morbidity and mortality. There is a critical need to better understand the demographics, clinical characteristics, and key risk factors for CKD; and to develop platforms for testing novel interventions to improve modifiable risk factors, particularly for the CKD patients with a rapid decline in kidney function.

METHODS

We describe a novel collaboration between two large healthcare systems (Providence St. Joseph Health and University of California, Los Angeles Health) supported by leadership from both institutions, which was created to develop harmonized cohorts of patients with CKD or those at increased risk for CKD (hypertension/HTN, diabetes/DM, pre-diabetes) from electronic health record data.

RESULTS

The combined repository of candidate records included more than 3.3 million patients with at least a single qualifying measure for CKD and/or at-risk for CKD. The CURE-CKD registry includes over 2.6 million patients with and/or at-risk for CKD identified by stricter guide-line based criteria using a combination of administrative encounter codes, physical examinations, laboratory values and medication use. Notably, data based on race/ethnicity and geography in part, will enable robust analyses to study traditionally disadvantaged or marginalized patients not typically included in clinical trials.

DISCUSSION

CURE-CKD project is a unique multidisciplinary collaboration between nephrologists, endocrinologists, primary care physicians with health services research skills, health economists, and those with expertise in statistics, bio-informatics and machine learning. The CURE-CKD registry uses curated observations from real-world settings across two large healthcare systems and has great potential to provide important contributions for healthcare and for improving clinical outcomes in patients with and at-risk for CKD.

Acute Kidney Injury in Critically Ill Children and Subsequent Chronic Kidney Disease

BACKGROUND

The progression from acute kidney injury (AKI) to chronic kidney disease (CKD) is not well understood in children.

OBJECTIVES

We aimed to develop a pediatric CKD definition using administrative data and use it to evaluate the association between AKI in critically ill children and CKD 5 years after hospital discharge.

DESIGN

Retrospective cohort study using chart collection and administrative data.

SETTING

Two-center study in Montreal, Canada.

PATIENTS

Children (≤18 years old) admitted to two pediatric intensive care units (ICUs) between 2003 and 2005. We a priori excluded patients with end-stage renal disease or no health care number. Only the first admission during the study period was included. We excluded patients who could not be linked to administrative data, did not survive hospitalization, or had preexisting renal disease.

MEASUREMENTS

Acute kidney injury was defined using Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patients were defined as having CKD 5 years post-discharge if they had ≥1 CKD diagnostic code or ≥1 CKD-specific medication prescription.

METHODS

Chart data used to define the exposure (AKI) were merged with provincial administrative data used to define the outcome (CKD). Cox regression was used to evaluate the AKI-CKD association.

RESULTS

A total of 2235 (56% male) patients were included, and the median admission age was 3.7 years. A total of 464 (21%) patients developed AKI during pediatric ICU admission. At 5 years post-discharge, 43 (2%) patients had a CKD diagnosis. Patients with both stage 1 and stage 2-3 AKI had increased risk of a CKD diagnosis, with the adjusted hazard ratios (95% confidence intervals) of 2.2 (1.1-4.5) and 2.5 (1.1-5.7), respectively (P < .001).

LIMITATIONS

Results may not be generalizable to non-ICU patients. We were not able to control for post-discharge variables; future research should try to explore these additional potential risk factors further.

CONCLUSIONS

Acute kidney injury is associated with 5-year post-discharge CKD diagnosis defined by administrative health care data.

Incidence and risk of dialysis therapy within 30 days after contrast enhanced computed tomography in patients coded with chronic kidney disease: a nation-wide, population-based study

Background

Patients with chronic kidney disease (CKD) are considered at risk of contrast-induced acute kidney injury and possible subsequent need for dialysis therapy. Computed tomography (CT) is the most commonly performed examination requiring intravenous iodinated contrast media (ICM) injection. The actual risk of dialysis in CKD patients undergoing CT with ICM remains controversial. Furthermore, it is also uncertain whether these at-risk patients can be identified by means of administrative data. Our study is conducted in order to determine the incidence and risk of dialysis within 30 days after undergoing contrast enhanced CT in CKD coded patients.

Methods

This longitudinal, nation-wide, populated-based study is carried out by analyzing the Taiwan National Health Insurance Research Database retrospectively. Patients coded under the diagnosis of CKD who underwent CT are identified within randomly selected one million subjects of the database. From January 2012 to December 2013, 487 patients had undergone CT with ICM. A total of 924 patients who underwent CT without ICM are selected as the control group. Patients with advanced CKD or intensive care unit (ICU) admissions are assigned to the subgroups for analysis. The primary outcome is measured by dialysis events within 30 days after undergoing CT scans. The cumulative incidence is assessed by the Kaplan–Meier method and log-rank test. The risk of 30-day dialysis relative to the control group is analyzed by the Cox proportional hazards model after adjusting for age, sex, and baseline comorbidities.

Results

The numbers and percentages of dialysis events within 30 days after undergoing CT scans are 20 (4.1%) in the CT with ICM group and 66 (7.1%) in the CT without ICM group (p = 0.03). However, the adjusted hazard ratio (aHR) for 30-day dialysis was 0.84 (95% CI [0.46–1.54], p = 0.57), which is statistically non-significant. In both advanced CKD and ICU admission subgroups, there are also no significant differences in 30-day dialysis risks with the aHR of 1.12 (95% CI [0.38–3.33], p = 0.83) and 0.95 (95% CI [0.44–2.05], p = 0.90), respectively.

Conclusions

Within 30 days of receiving contrast-enhanced CT scans, 4.1% of CKD coded patients required dialysis, which appear to be lower compared with subjects who received non-contrast CT scans. However, no statistically significant difference is observed after adjustments are made for other baseline conditions. Thereby, the application of administrative data to identify patients with CKD cannot be viewed as a risk factor for the necessity to undergo dialysis within 30 days of receiving contrast-enhanced CT scans.

Using electronic health record data to establish a chronic kidney disease surveillance system in China: protocol for the China Kidney Disease Network (CK-NET)-Yinzhou Study

INTRODUCTION

Chronic kidney disease (CKD) is an important public health problem worldwide. However, there are few active disease surveillance systems for it. The China Kidney Disease Network (CK-NET) was established as a comprehensive surveillance system for CKD using various data sources. As part of this, the proposed CK-NET-Yinzhou study aims to build a regional surveillance system in a developed coastal area in China to obtain detailed dynamic information about kidney disease and to improve the ability to manage the disease effectively.

METHODS AND ANALYSIS

Yinzhou is a district of Ningbo city, Zhejiang province. The district has a population of more than 1 million. By 2016, 98% were registered in a regional health information system that started in 2009. This system includes administrative databases containing general demographic characteristics, health check information, inpatient and outpatient electronic medical records, health insurance information, disease surveillance and management information, and death certificates. We will use longitudinal individual electronic health record data to identify people with CKD by repeated laboratory measurements and diagnostic codes. We will also evaluate the associated risk factors, prognosis and disease management. An intelligent clinical decision support system (CDSS) will be developed based on clinical guidelines, domain expert knowledge and real-world data, and will be integrated into the hospital information system.

ETHICS AND DISSEMINATION

The CK-NET-Yinzhou study has been reviewed and approved by the Peking University First Hospital Ethics Committee. Privacy of local residents registered with the health information system will be tightly protected through the study process. The findings of the study will be disseminated through peer-reviewed journal articles, posters and presentations in national and international scientific conferences, as well as among local practitioners through the CDSS.

Can billing codes accurately identify rapidly progressing stage 3 and stage 4 chronic kidney disease patients: a diagnostic test study

Background

The International Classification of Diseases (ICD) coding system is the industry standard tool for billing, disease classification, and epidemiology purposes. However, ICD codes are often not assigned or incorrectly given, particularly among Chronic Kidney disease (CKD) patients. Our study evaluated the diagnostic accuracy of CKD-staging ICD codes among CKD patients from a large insurer database in identifying individuals rapidly progressing towards end-stage renal disease (ESRD).

Patients and methods

Serial observations including outpatient serum creatinine measurements collected from 2007 through 2014 of 216,529 patients were examined. The progression of CKD using a serum creatinine based longitudinal mixed-model was contrasted with that documented by CKD-staging ICD codes. Rapid progressors, defined as those with yearly estimated glomerular filtration rate (eGFR) loss greater than 4 ml/min/1.73m²) were identified. The diagnosis of CKD using eGFR was also compared to diagnosis using a set of CKD related ICD codes.

Results

Of 10,927 clinically identified CKD patients qualifying for inclusion in the progression analysis, 323 were clinically identified as rapid progressors. CKD-staging ICD codes identified 83 of these, for a sensitivity of 25.7% with positive predictive value (PPV) of 13.74%, and specificity 95.09% with negative predictive value (NPV) of 97.68%. Of 28,762 laboratory-confirmed CKD patients, 9249 had a qualifying ICD code, for a sensitivity of 16% with PPV of 63.10%; Of 187,767 patients with laboratory-confirmed absence of CKD, 182,359 also did not have a qualifying ICD code, for a specificity of 97.12% with NPV of 90.33%.

Conclusion

This study depicts the novel finding that ICD-codes display poor capacity to identify rapidly progressing CKD patients when compared to gold standard eGFR measures, and further demonstrates the limitations of coding in CKD diagnosis. This analysis further defines the limitations of ICD codes in addressing diagnosis of disease severity or disease progression for clinical or epidemiological purposes.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1429-4) contains supplementary material, which is available to authorized users.

Creating a 13-year National Longitudinal Cohort of veterans with chronic kidney disease

BACKGROUND

The development of large-scale chronic kidney disease (CKD) cohorts within the Veterans Affairs (VA) system has been limited by several factors, including the high proportion of missing race data etc. The goal of this study is to address the limitations of prior studies by creating a large cohort utilizing robust KDIGO recommendations for identifying and staging CKD.

METHODS

Multiple patient and administrative files from the Veterans Health Administration (VHA) National Patient Care were linked to create a national cohort of Veterans with chronic kidney disease (CKD) between January 2000 - December 2012; patients identified during this period were followed until 2015. CKD was defined for stages 1 through 5 if markers of kidney damage, specifically proteinuria, were present for at least 3 months. Estimated glomerular filtration rate (eGFR) values were calculated based on serum creatinine levels and the patient's age, gender, and race using both the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas.

RESULTS

About 50 million observations were collected that supported a CKD diagnosis during the study period; these observations corresponded to 3,051,001 unique veterans; 80.9% were non-Hispanic white (NHW), 13.4% were non-Hispanic black (NHB), 3.6% were Hispanic, and 2.0% were in other groups. The mean age 76.7, about 97% were male and 50.2% died prior to January 2016. Among those with stage 3, 12.3% progressed to stage 4, 21.6% of those with stage 4 progressed to stage 5. We found that eGFR values calculated from serum creatinine levels identified about 98% of all patients, while about 11.4% of patients could be identified through ICD-9 codes; only 6.4% could be identified through both sources.

CONCLUSION

This 13-year national cohort provides an important resource for answering numerous research questions in the future such as racial/ethnic disparities questions, tracking health service utilization, medication adherence, cost and health outcomes in veterans with CKD.

The association between the severity of chronic kidney disease and medical costs among patients with type 2 diabetes

AIMS

Examine healthcare costs across chronic kidney disease (CKD) stages for US patients with type 2 diabetes (T2D).

MATERIALS AND METHODS

IQVIA Real World Data Adjudicated Claims linked electronic medical records and insurance claims from January 1, 2012 through March 31, 2017 were used for this retrospective study. Adults diagnosed with T2D and comorbid CKD were included. General linear models incorporating splines were constructed, and information from these regressions were used to inform the relationship between medical costs and CKD. Multivariable analyses controlled for patient characteristics, vital signs, general health, prior medication use, prior visit to specialists, index A1c, and year of index date.

RESULTS

There were 6,645 individuals who met the study criteria. Results generally indicate sharp increases in annual total medical costs and non-drug medical costs in the 1 year post-period for patients with Stage 4 or 5 CKD (estimated glomerular filtration rate [eGFR] ≤ 30 mL/min/1.73 m²) with each 1 point reduction in eGFR from 30 associated with an increase of $1,870 in all-cause total medical costs (p < 0.0001) and $1,805 of all-cause non-drug medical costs (p < 0.0001). Similarly, each point decline below 30 mL/min was associated annual cost increases of $1,701 for CKD-related total medical costs, $1,695 for CKD-related non-drug medical costs, $173 for diabetes-related medical costs, and $187 for diabetes-related non-drug medical costs (all p < 0.0001).

LIMITATIONS

The investigation included only patients with medical insurance and laboratory test results, and results may not be generalizable to all T2D patients with CKD. The methodology allowed us to determine associations, not causation, and potential confounders, such as duration of diabetes, diet, exercise, or social support, could not be assessed.

CONCLUSIONS

Results indicate there are sharp and significant increases in medical costs among T2D patients with Stage 4 and 5 CKD compared to those with earlier stages of CKD.

Development of an electronic health record-based chronic kidney disease registry to promote population health management

BACKGROUND

Electronic health record (EHR) based chronic kidney disease (CKD) registries are central to population health strategies to improve CKD care. In 2015, Partners Healthcare System (PHS), encompassing multiple academic and community hospitals and outpatient care facilities in Massachusetts, developed an EHR-based CKD registry to identify opportunities for quality improvement, defined as improvement on both process measures and outcomes measures associated with clinical care.

METHODS

Patients are included in the registry based on the following criteria: 1) two estimated glomerular filtration rate (eGFR) results < 60 ml/min/1.73m2 separated by 90 days, including the most recent eGFR being < 60 ml/min/1.73m2; or 2) the most recent two urine protein values > 300 mg protein/g creatinine on either urine total protein/creatinine ratio or urine albumin/creatinine ratio; or 3) an EHR problem list diagnosis of end stage renal disease (ESRD). The registry categorizes patients by CKD stage and includes rates of annual testing for eGFR and proteinuria, blood pressure control, use of angiotensin converting enzyme inhibitors (ACE-Is) or angiotensin receptor blockers (ARBs), nephrotoxic medication use, hepatitis B virus (HBV) immunization, vascular access placement, transplant status, CKD progression risk; number of outpatient nephrology visits, and hospitalizations.

RESULTS

The CKD registry includes 60,503 patients and has revealed several opportunities for care improvement including 1) annual proteinuria testing performed for 17% (stage 3) and 31% (stage 4) of patients; 2) ACE-I/ARB used in 41% (stage 3) and 46% (stage 4) of patients; 3) nephrotoxic medications used among 23% of stage 4 patients; and 4) 89% of stage 4 patients lack HBV immunity. For advanced CKD patients there are opportunities to improve vascular access placement, transplant referrals and outpatient nephrology contact.

CONCLUSIONS

A CKD registry can identify modifiable care gaps across the spectrum of CKD care and enable population health strategy implementation. No linkage to Social Security Death Master File or US Renal Data System (USRDS) databases limits our ability to track mortality and progression to ESRD.

Characteristics and Outcomes of Patients With Aortic Stenosis and Chronic Kidney Disease

Background We sought to study longer term survival in patients with aortic stenosis ( AS ) and nondialysis chronic kidney disease ( CKD ). Methods and Results We studied 839 patients (aged 78±9 years and 51% male) with CKD and AS on echocardiogram from 2005 to 2012. Longer term all-cause and cardiovascular mortality was compared with a CKD group without AS , propensity matched for age, sex, race, left ventricular ejection fraction and CKD stage. Cox models were used to evaluate all-cause mortality and competing-risks regression models censored at time of aortic valve replacement to evaluate cardiac mortality in patients with AS and CKD . Overall, 511 (61%), 252 (30%), and 76 (9%) patients had CKD stages 3a, 3b, and 4, respectively; 93% had hypertension, 28% had diabetes mellitus, and 37% had coronary artery disease. In total, 185 (22%) had mild AS, 355 (42%) had moderate AS, and 299 (36%) had severe AS (66 symptomatic). Patients with CKD and AS had higher cardiac and all-cause mortality compared with controls with CKD and no AS ( P<0.001). Among patients with AS and CKD , there were 156 (19%) aortic valve replacements and 454 (54%) deaths (203 cardiac deaths) at 4.0±2.3 years of follow-up. Lower estimated glomerular filtration rate (hazard ratio per 10 mL/min per 1.73 m2: 1.18; 95% CI, 1.08-1.29) was associated with increased risk of all-cause mortality but not cardiac mortality (hazard ratio: 1.12; 95% CI, 0.97-1.30; P=0.13). Of patients undergoing aortic valve replacement, 61% had improvement in estimated glomerular filtration rate within 1 year (median percentage change=+2.8% per month). Conclusions Among patients with nondialysis CKD , AS is associated with significantly higher cardiac and all-cause mortality; lower estimated glomerular filtration rate is associated with increased mortality, and aortic valve replacement was associated with improved survival.

Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care

BACKGROUND

Electronic health record (EHR) data is increasingly used to identify patients with chronic kidney disease (CKD). EHR queries used to capture CKD status, identify comorbid conditions, measure awareness by providers, and track adherence to guideline-concordant processes of care have not been validated.

METHODS

We extracted EHR data for primary-care patients with two eGFRcreat 15-59 mL/min/1.73 m^2 at least 90 days apart. Two nephrologists manually reviewed a random sample of 50 charts to determine CKD status, associated comorbidities, and physician awareness of CKD. We also assessed the documentation of a CKD diagnosis with guideline-driven care.

RESULTS

Complete data were available on 1767 patients with query-defined CKD of whom 822 (47%) had a CKD diagnosis in their chart. Manual chart review confirmed the CKD diagnosis in 34 or 50 (68%) patients. Agreement between the reviewers and the EHR diagnoses on the presence of comorbidities was good (κ > 0.70, p < 0.05), except for congestive heart failure, (κ = 0.45, p < 0.05). Reviewers felt the providers were aware of CKD in 23 of 34 (68%) of the confirmed CKD cases. A CKD diagnosis was associated with higher odds of guideline-driven care including CKD-specific laboratory tests and prescriptions for statins. After adjustment, CKD diagnosis documentation was not significantly associated with ACE/ARB prescription.

CONCLUSIONS

Identifying CKD status by historical eGFRs overestimates disease prevalence. A CKD diagnosis in the patient chart was a reasonable surrogate for provider awareness of disease status, but CKD awareness remains relatively low. CKD in the patient chart was associated with higher rates of albuminuria testing and use of statins, but not use of ACE/ARB.

Associations between Water Quality Measures and Chronic Kidney Disease Prevalence in Taiwan

To determine the relationships between exposure to environmental contaminants in water and chronic kidney disease (CKD), we investigated the associations of 61 water attributes with the prevalence of CKD and End-Stage Renal Disease (ESRD) using data from 2005 to 2011 from all 22 counties and cities in the main island of Taiwan. We acquired patient information from the Taiwan Longitudinal Health Insurance Database to calculate the age-standardized CKD and ESRD prevalence rates and linked the patients’ residences to the water quality monitoring data, which were sampled periodically for a total of over 45,000 observations obtained from the Taiwan Environmental Water Quality Information Database. The association analysis adjusting for gender, age, and annual effects showed that the zinc (Zn), ammonia, chemical oxygen demand (COD), and dissolved oxygen in rivers were weakly correlated with CKD (τ = 0.268/0.250/0.238/−0.267, p = 6.01×10⁻⁶/2.52×10⁻⁵/6.05×10⁻⁵/3.30×10⁻⁵, respectively), but none for ESRD. The importances of Zn and COD in rivers were also demonstrated in a CKD regression model. Moreover, an unusually high CKD prevalence was related to arsenic contamination in groundwater. A further prospective cohort study would improve our understanding of what level of environmental water with risky properties could affect the development of CKD.

Data and knowledge standards for learning health: A population management example using chronic kidney disease

The widespread creation of learning health care systems (LHSs) will depend upon the use of standards for data and knowledge representation. Standards can facilitate the reuse of approaches for the identification of patient cohorts and the implementation of interventions. Standards also support rapid evaluation and dissemination across organizations. Building upon widely-used models for process improvement, we identify specific LHS activities that will require data and knowledge standards. Using chronic kidney disease (CKD) as an example, we highlight the specific data and knowledge requirements for a disease-specific LHS cycle, and subsequently identify areas where standards specifications, clarification, and tools are needed. The current data standards for CKD population management recommendations were found to be partially ambiguous, leading to barriers in phenotyping, risk identification, patient-centered clinical decision support, patient education needs, and care planning. Robust tools are needed to effectively identify patient health care needs and preferences and to measure outcomes that accurately depict the multiple facets of CKD. This example presents an approach for defining the specific data and knowledge representation standards required to implement condition-specific population health management programs. These standards specifications can be promoted by disease advocacy and professional societies to enable the widespread design, implementation, and evaluation of evidence-based health interventions, and the subsequent dissemination of experience in different settings and populations.

Cause-Specific Mortality in Patients with Chronic Kidney Disease and Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is associated with death in patients with chronic kidney disease (CKD). We examined the associations between AF and cause-specific mortality in a large CKD population.

METHODS

We included 62,459 patients with estimated glomerular filtration rate 15-59 mL/min/1.73 m2 (6,639 patients with AF and 55,820 without AF) followed in a large health care system. Outcomes included overall and cause-specific deaths (a) cardiovascular; (b) malignancy; and (c) non-cardiovascular/non-malignancy causes. Cox regression models for overall mortality and separate competing risk models for each major cause of death category were used to evaluate their respective associations with AF.

RESULTS

During a median follow-up of 4.1 years, 19,094 patients died; cause of death was known for 18,854 patients. After multivariable adjustment (demographics, comorbidities, relevant laboratory data, medication use, and kidney function), AF was associated with 23% (95% CI 18-29%) higher risk of all-cause mortality, 45% (95% CI 31-61%) higher risk of cardiovascular mortality and 13% (95% CI 3-22%) lower risk of malignancy-related mortality. Exclusion of patients with malignancy yielded similar results except for a lack of association between AF and malignancy-related deaths. Results were consistent across various stages of CKD.

CONCLUSIONS

In a non-dialysis-dependent CKD population, the presence of AF was associated with higher all-cause and cardiovascular mortality. These data suggest that patients with both CKD and AF are at high cardiovascular risk, and thus clinical practice (or trials) should aim at reducing the overall excess cardiovascular mortality (not stroke alone) in patients with AF and CKD.

Validated registry of pre-dialysis chronic kidney disease: description of a large cohort

Introduction:

Chronic diseases account for the majority of deaths in Brazil. These include hypertension (SAH) and diabetes mellitus (DM), which are the main causes of chronic kidney disease (CKD).

Objective:

This study aimed to validate the data of an electronic health record and to point out characteristics of the profile of these users in relation to clinical quality indicators for a pre-dialytic CKD.

Methods:

Retrospective cohort, August/2010 to December/2014. Included users > 18 years, with at least two queries. Variables analyzed: sociodemographic, underlying disease, main medications and main clinical indicators of control. A descriptive analysis was performed and the percentage of users was evaluated in the goals at admission and at the end of the study.

Results:

Exported, converted and validated data of 1,977 users with average follow-up time of 21 months. Of these, 51.4% were men, 58% were > 64 years of age and 81.6% were overweight. The main medications in use were diuretics (82.9%), BRAT (62%), Statin (60.7%) and ACE inhibitors (49.9%). The percentage of users with a decline in the glomerular filtration rate was 33.7%. Regarding glycated hemoglobin, users with CKD and DM, 36% were within the initial goal and 52.1% of the final. Blood pressure was at the target for admission at 34.3% and 49.8% at the end of follow-up.

Conclusion:

Validated data are of vital importance for health managers to monitor users. The population of this study is predominantly elderly, obese, requiring multi-professional care to slow the progression of the disease and decrease morbidity and mortality.

High-density lipoprotein cholesterol and causes of death in chronic kidney disease

BACKGROUND

Recent data suggest a U-shaped association between high-density lipoprotein cholesterol (HDL-c) and death in chronic kidney disease (CKD). However, whether the increased mortality in patients with extreme levels is explained by specific causes of death remains unclear.

OBJECTIVES

We studied the associations between HDL-c and cause-specific deaths in CKD.

METHODS

We included 38,377 patients with estimated glomerular filtration rate 15-59 mL/min/1.73 m². We classified deaths into 3 major categories: (1) cardiovascular; (2) malignant; and (3) noncardiovascular/nonmalignant causes. We fitted Cox regression models for overall mortality and separate competing risk models for each major cause of death category to evaluate their respective associations with categories of HDL-c (≤30, 31-40, 41-50 [referent], 51-60, >60 mg/dL). Separate analyses were conducted for men and women.

RESULTS

During a median follow-up of 4.5 years, 9665 patients died. After adjusting for relevant covariates, in both sexes, HDL-c 31 to 40 mg/dL and ≤30 mg/dL were associated with higher risk of all-cause mortality, cardiovascular mortality, malignancy-related deaths, and noncardiovascular/nonmalignancy-related deaths. HDL-c >60 mg/dL was associated with lower all-cause (hazard ratio: 0.75, 95% confidence interval: 0.69, 0.81), cardiovascular, malignancy-related, and noncardiovascular/nonmalignancy-related deaths among women but not in men. Similar results were noted when HDL-c was examined as a continuous measure.

CONCLUSIONS

In a non-dialysis-dependent CKD population, HDL-c ≤40 mg/dL was associated with risk of higher all-cause, cardiovascular, malignant, and noncardiovascular/nonmalignant mortality in men and women. HDL >60 mg/dL was associated with lower risk of all-cause, cardiovascular, malignant, and noncardiovascular/nonmalignant mortality in women but not in men.

Associations of dysnatremias with mortality in chronic kidney disease

Background

Hyponatremia and hypernatremia are associated with death in the general population and those with chronic kidney disease (CKD). We studied the associations between dysnatremias, all-cause mortality and causes of death in a large cohort of Stage 3 and 4 CKD patients.

Methods

We included 45 333 patients with Stage 3 and 4 CKDs followed in a large healthcare system. Associations between hyponatremia (<136 mmol/L) and hypernatremia (>145), and all-cause mortality and causes of death (cardiovascular, malignancy related and non-cardiovascular/non-malignancy related) were studied using Cox proportional hazards and competing risk models.

Results

Dysnatremias were found in 9.2% of the study population. In separate multivariable Cox proportional hazards models using baseline serum sodium levels and time-dependent repeated measures, both hyponatremia and hypernatremia were associated with all-cause mortality. In the competing risk analyses, hyponatremia was significantly associated with increased risk for various cause-specific mortality categories [cardiovascular (hazard ratio, HR 1.16, 95% confidence interval, CI: 1.04, 1.30), malignancy related (HR 1.48, 95% CI: 1.33, 1.65) and non-cardiovascular/non-malignancy deaths (HR 1.25, 95% CI: 1.13, 1.39)], while hypernatremia was significantly associated with higher non-cardiovascular/non-malignancy mortality only (HR 1.36, 95% CI: 1.08, 1.72).

Conclusions

In those with CKD, hyponatremia was associated with all-cause mortality, cardiovascular, malignancy and non-cardiovascular/non-malignancy-related deaths. Hypernatremia was associated with all-cause and non-cardiovascular/non-malignancy-related deaths. Further studies are needed to elucidate the mechanisms of differences in cause-specific death among CKD patients with hyponatremia and hypernatremia.