CKD Prevalence in the Military Health System: Coded Versus Uncoded CKD

Retaining Race in Chronic Kidney Disease Diagnosis and Treatment

The best overall measure of kidney function is glomerular filtration rate (GFR) as commonly estimated from serum creatinine concentrations (eGFRcr) using formulas that correct for the higher average creatinine concentrations in Blacks. After two decades of use, these formulas have come under scrutiny for estimating GFR differently in Blacks and non-Blacks. Discussions of whether to include race (Black vs. non-Black) in the calculation of eGFRcr fail to acknowledge that the original race-based eGFRcr provided the same CKD treatment recommendations for Blacks and non-Blacks based on directly (exogenously) measured GFR. Nevertheless, the National Kidney Foundation and the American Society of Nephrology Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease removed race in CKD treatment guidelines and pushed for the immediate adoption of a race-free eGFRcr formula by physicians and clinical laboratories. This formula is projected to negate CKD in 5.51 million White and other non-Black adults and reclassify CKD to less severe stages in another 4.59 million non-Blacks, in order to expand treatment eligibility to 434,000 Blacks not previously diagnosed and to 584,000 Blacks previously diagnosed with less severe CKD. This review examines: 1) the validity of the arguments for removing the original race correction, and 2) the performance of the proposed replacement formula. Excluding race in the derivation of eGFRcr changed the statistical bias from +3.7 to -3.6 ml/min/1.73m2 in Blacks and from +0.5 to +3.9 in non-Blacks, i.e., promoting CKD diagnosis in Blacks at the cost of restricting diagnosis in non-Blacks. By doing so, the revised eGFRcr greatly exaggerates the purported racial disparity in CKD burden. Claims that the revised formulas identify heretofore undiagnosed CKD in Blacks are not supported when studies that used kidney failure replacement therapy and mortality are interpreted as proxies for baseline CKD. Alternatively, a race-stratified eGFRcr (i.e., separate equations for Blacks and non-Blacks) would provide the least biased eGFRcr for both Blacks and non-Blacks and the best medical treatment for all patients.

Electronic Phenotype for Advanced Chronic Kidney Disease in a Veteran Health Care System Clinical Database: Systems-Based Strategy for Model Development and Evaluation

BACKGROUND

Identifying advanced (stages 4 and 5) chronic kidney disease (CKD) cohorts in clinical databases is complicated and often unreliable. Accurately identifying these patients can allow targeting this population for their specialized clinical and research needs.

OBJECTIVE

This study was conducted as a system-based strategy to identify all prevalent Veterans with advanced CKD for subsequent enrollment in a clinical trial. We aimed to examine the prevalence and accuracy of conventionally used diagnosis codes and estimated glomerular filtration rate (eGFR)-based phenotypes for advanced CKD in an electronic health record (EHR) database. We sought to develop a pragmatic EHR phenotype capable of improving the real-time identification of advanced CKD cohorts in a regional Veterans health care system.

METHODS

Using the Veterans Affairs Informatics and Computing Infrastructure services, we extracted the source cohort of Veterans with advanced CKD based on a combination of the latest eGFR value ≤30 ml·min-1·1.73 m-2 or existing International Classification of Diseases (ICD)-10 diagnosis codes for advanced CKD (N18.4 and N18.5) in the last 12 months. We estimated the prevalence of advanced CKD using various prior published EHR phenotypes (ie, advanced CKD diagnosis codes, using the latest single eGFR <30 ml·min-1·1.73 m-2, utilizing two eGFR values) and our operational EHR phenotypes of a high-, intermediate-, and low-risk advanced CKD cohort. We evaluated the accuracy of these phenotypes by examining the likelihood of a sustained reduction of eGFR <30 ml·min-1·1.73 m-2 over a 6-month follow-up period.

RESULTS

Of the 133,756 active Veteran enrollees at North Florida/South Georgia Veterans Health System (NF/SG VHS), we identified a source cohort of 1759 Veterans with advanced nondialysis CKD. Among these, 1102 (62.9%) Veterans had diagnosis codes for advanced CKD; 1391(79.1%) had the index eGFR <30 ml·min-1·1.73 m-2; and 928 (52.7%), 480 (27.2%), and 315 (17.9%) Veterans had high-, intermediate-, and low-risk advanced CKD, respectively. The prevalence of advanced CKD among Veterans at NF/SG VHS varied between 1% and 1.5% depending on the EHR phenotype. At the 6-month follow-up, the probability of Veterans remaining in the advanced CKD stage was 65.3% in the group defined by the ICD-10 codes and 90% in the groups defined by eGFR values. Based on our phenotype, 94.2% of high-risk, 71% of intermediate-risk, and 16.1% of low-risk groups remained in the advanced CKD category.

CONCLUSIONS

While the prevalence of advanced CKD has limited variation between different EHR phenotypes, the accuracy can be improved by utilizing two eGFR values in a stratified manner. We report the development of a pragmatic EHR-based model to identify advanced CKD within a regional Veterans health care system in real time with a tiered approach that allows targeting the needs of the groups at risk of progression to end-stage kidney disease.

Development and Validation of a Lifetime Risk Model for Kidney Failure and Treatment Benefit in Type 2 Diabetes: 10-Year and Lifetime Risk Prediction Models

BACKGROUND AND OBJECTIVES

Individuals with type 2 diabetes are at a higher risk of developing kidney failure. The objective of this study was to develop and validate a decision support tool for estimating 10-year and lifetime risks of kidney failure in individuals with type 2 diabetes as well as estimating individual treatment effects of preventive medication.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

The prediction algorithm was developed in 707,077 individuals with prevalent and incident type 2 diabetes from the Swedish National Diabetes Register for 2002-2019. Two Cox proportional regression functions for kidney failure (first occurrence of kidney transplantation, long-term dialysis, or persistent eGFR <15 ml/min per 1.73 m2) and all-cause mortality as respective end points were developed using routinely available predictors. These functions were combined into life tables to calculate the predicted survival without kidney failure while using all-cause mortality as the competing outcome. The model was externally validated in 256,265 individuals with incident type 2 diabetes from the Scottish Care Information Diabetes database between 2004 and 2019.

RESULTS

During a median follow-up of 6.8 years (interquartile range, 3.2-10.6), 8004 (1%) individuals with type 2 diabetes in the Swedish National Diabetes Register cohort developed kidney failure, and 202,078 (29%) died. The model performed well, with c statistics for kidney failure of 0.89 (95% confidence interval, 0.88 to 0.90) for internal validation and 0.74 (95% confidence interval, 0.73 to 0.76) for external validation. Calibration plots showed good agreement in observed versus predicted 10-year risk of kidney failure for both internal and external validation.

CONCLUSIONS

This study derived and externally validated a prediction tool for estimating 10-year and lifetime risks of kidney failure as well as life years free of kidney failure gained with preventive treatment in individuals with type 2 diabetes using easily available clinical predictors.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2022_11_04_CJN05020422.mp3.

Chronic kidney disease in outpatients with arterial hypertension: clinical characteristics and treatment efficacy (according to the national registry)

Аim. To investigate the clinical characteristics and quality of treatment (according to the national guidelines) of patients with arterial hypertension (AH) and chronic kidney disease observed in primary health care. Materials and methods. The study was carried out on the basis of the AH registry data (n=43 133; 20052019 years). Glomerular filtration rate (eGFR) was calculated using the CKD-EPI formula; renal structure and albuminuria were not evaluated. The analysis was performed using the SPSS software (version 22; SPSS Inc). Results. The creatinine level was assessed in 60% of patients, 23.6% of them had decreased eGFR60 ml/ min/1.73 m2. The incidence of co-morbid CVD and type 2 diabetes in patients with hypertension increased markedly with a decrease in eGFR (14 groups): the incidence of coronary artery disease increased 1.8 times (up to 72.5%), myocardial infarction 1.7 times (up to 20.6%), chronic heart failure 2 times (up to 84.0%), atrial fibrillation 10 times (up to 18.3%), history of stroke 3.7 times (up to 15.3%) and type 2 diabetes 2.4 times (up to 32.8%). Achievement of target goals of CV risk factors was not enough: systolic BP less than 50% of patients, triglycerides less than 7%, LDL-C in high and very high CVD risk patients less than 13%. Conclusion. Conducting timely assessment of renal function, drug therapy and lifestyle changes in patients with AH and decreased renal functional could prevent severe kidney damage, the development of CV complications, chronic renal failure and reduce mortality.

Prevalence and Characteristics of CKD in the US Military Health System: A Retrospective Cohort Study

Rationale & Objective

The US Military Health System (MHS) is a global health care network with a diverse population that is more representative of the US population than other study cohorts and with fewer disparities in health care access. We aimed to examine the prevalence of chronic kidney disease (CKD) in the MHS and within demographic subpopulations.

Study Design

Multiple cross-sectional analyses of demographic and claims-based data extracted from the MHS Data Repository, 1 for each fiscal year from 2006-2015.

Setting & Population

Multicenter health care network including active-duty military, retirees, and dependents. The average yearly sample size was 3,285,348 individuals.

Exposures

Age, sex, race, active-duty status, and active-duty rank (a surrogate for socioeconomic status).

Outcome

CKD, defined as the presence of matching International Classification of Diseases, Ninth Revision, codes on either 1 or more inpatient or 2 or more outpatient encounters.

Analytical Approach

t test for continuous variables and χ² test for categorical variables; multivariable logistic regression for odds ratios.

Results

For 2015, the mean (standard deviation) age was 38 (16). Crude CKD prevalence was 2.9%. Age-adjusted prevalence was 4.9% overall—1.9% active-duty and 5.4% non–active-duty individuals. ORs for CKD were calculated with multiple imputations to account for missing data on race. After adjustment, the ORs for CKD (all P < 0.001) were 1.63 (95% CI, 1.62-1.64) for an age greater than 40 years, 1.16 (95% CI, 1.15-1.17) for Black race, 1.15 (95% CI, 1.14-1.16) for senior enlisted rank, 0.94 (95% CI, 0.93-0.95) for women, and 0.50 (95% CI, 0.49-0.51) for active-duty status.

Limitations

Retrospective study based on International Classification of Diseases, Ninth Revision, coding.

Conclusions

Within the MHS, older age, Black race, and senior enlisted rank were associated with a higher risk of CKD, whereas female sex and active-duty status were associated with a lower risk.