Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. CKD Patch is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures.Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several CKD Patches incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch.Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018-0.036] and 0.010 [0.007-0.013] and categorical net reclassification improvement 0.080 [0.032-0.127] and 0.056 [0.044-0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89-3.40) in very high-risk CKD (e.g., eGFR 30-44 ml/min/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48-2.44) in high-risk CKD (e.g., eGFR 45-59 ml/min/1.73m2 with albuminuria 30-299 mg/g), and 1.37 (1.14-1.69) in moderate risk CKD (e.g., eGFR 60-89 ml/min/1.73m2 with albuminuria 30-299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37-1.81), 1.24 (1.10-1.54), and 1.21 (0.98-1.46).Interpretation: The CKD Patch can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available.Funding: US National Kidney Foundation and the NIDDK

Albuminuria Testing in Hypertension and Diabetes:An Individual-Participant Data Meta-Analysis in a Global Consortium

Albuminuria is an under-recognized component of chronic kidney disease definition, staging, and prognosis. Guidelines, particularly for hypertension, conflict on recommendations for urine albumin-to-creatinine ratio (ACR) measurement. Separately among 1 344 594 adults with diabetes and 2 334 461 nondiabetic adults with hypertension from the chronic kidney disease Prognosis Consortium, we assessed ACR testing, estimated the prevalence and incidence of ACR ≥30 mg/g and developed risk models for ACR ≥30 mg/g. The ACR screening rate (cohort range) was 35.1% (12.3%-74.5%) in diabetes and 4.1% (1.3%-20.7%) in hypertension. Screening was largely unrelated to the predicted risk of prevalent albuminuria. The median prevalence of ACR ≥30 mg/g across cohorts was 32.1% in diabetes and 21.8% in hypertension. Higher systolic blood pressure was associated with a higher prevalence of albuminuria (odds ratio [95% CI] per 20 mm Hg in diabetes, 1.50 [1.42-1.60]; in hypertension, 1.36 [1.28-1.45]). The ratio of undetected (due to lack of screening) to detected ACR ≥30 mg/g was estimated at 1.8 in diabetes and 19.5 in hypertension. Among those with ACR/g, the median 5-year incidence of ACR ≥30 mg/g across cohorts was 23.9% in diabetes and 21.7% in hypertension. Incident albuminuria was associated with initiation of renin-angiotensin-aldosterone system inhibitors (incidence-rate ratio [95% CI], diabetes 3.09 [2.71-3.53]; hypertension 2.87 [2.29-3.59]). In conclusion, despite similar risk of albuminuria to those with diabetes, ACR screening in patients with hypertension was low. Our findings suggest that regular albuminuria screening should be emphasized to enable early detection of chronic kidney disease and initiation of treatment with cardiovascular and renal benefits

The kidney failure risk equation:evaluation of novel input variables including eGFR estimated using the CKD-EPI 2021 equation in 59 cohorts

SIGNIFICANCE STATEMENT: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict 2- and 5-year risk of kidney failure in populations with eGFR <60 ml/min per 1.73 m 2 . However, the CKD-EPI 2021 creatinine equation for eGFR is now recommended for use but has not been fully tested in the context of KFRE. In 59 cohorts comprising 312,424 patients with CKD, the authors assessed the predictive performance and calibration associated with the use of the CKD-EPI 2021 equation and whether additional variables and accounting for the competing risk of death improves the KFRE's performance. The KFRE generally performed well using the CKD-EPI 2021 eGFR in populations with eGFR <45 ml/min per 1.73 m 2 and was not improved by adding the 2-year prior eGFR slope and cardiovascular comorbidities. BACKGROUND: The kidney failure risk equation (KFRE) uses age, sex, GFR, and urine albumin-to-creatinine ratio (ACR) to predict kidney failure risk in people with GFR <60 ml/min per 1.73 m 2 . METHODS: Using 59 cohorts with 312,424 patients with CKD, we tested several modifications to the KFRE for their potential to improve the KFRE: using the CKD-EPI 2021 creatinine equation for eGFR, substituting 1-year average ACR for single-measure ACR and 1-year average eGFR in participants with high eGFR variability, and adding 2-year prior eGFR slope and cardiovascular comorbidities. We also assessed calibration of the KFRE in subgroups of eGFR and age before and after accounting for the competing risk of death. RESULTS: The KFRE remained accurate and well calibrated overall using the CKD-EPI 2021 eGFR equation. The other modifications did not improve KFRE performance. In subgroups of eGFR 45-59 ml/min per 1.73 m 2 and in older adults using the 5-year time horizon, the KFRE demonstrated systematic underprediction and overprediction, respectively. We developed and tested a new model with a spline term in eGFR and incorporating the competing risk of mortality, resulting in more accurate calibration in those specific subgroups but not overall. CONCLUSIONS: The original KFRE is generally accurate for eGFR <45 ml/min per 1.73 m 2 when using the CKD-EPI 2021 equation. Incorporating competing risk methodology and splines for eGFR may improve calibration in low-risk settings with longer time horizons. Including historical averages, eGFR slopes, or a competing risk design did not meaningfully alter KFRE performance in most circumstances

Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant–Based Meta-analysis

Financial Support: The CKD-PC Data Coordinating Center is funded in part by a program grant from the U.S. National Kidney Foundation and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100446). Various sources have supported enrollment and data collection, including laboratory measurements and follow-up, in the collaborating cohorts of the CKD-PC. These funding sources include government agencies, such as national institutes of health and medical research councils, as well as the foundations and industry sponsors listed in Supplemental Appendix 3 (available at Annals.org).Peer reviewedPostprin

Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes. An Individual-Participant Data Meta-Analysis

IMPORTANCE: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. OBJECTIVE: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. DESIGN, SETTING, AND PARTICIPANTS: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. EXPOSURES: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). MAIN OUTCOMES AND MEASURES: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. RESULTS: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]). CONCLUSIONS AND RELEVANCE: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations

Circulating Proteins and Mortality in CKD: A Proteomics Study of the AASK and ARIC Cohorts

Rationale &amp; Objective: Proteomics could provide pathophysiologic insight into the increased risk of mortality in patients with chronic kidney disease (CKD). This study aimed to investigate associations between the circulating proteome and all-cause mortality among patients with CKD. Study Design: Observational cohort study. Setting &amp; Participants: Primary analysis in 703 participants in the African American Study of Kidney Disease and Hypertension (AASK) and validation in 1,628 participants with CKD in the Atherosclerosis Risk in Communities (ARIC) study who attended visit 5. Exposure: Circulating proteins. Outcome: All-cause mortality. Analytical Approach: Among AASK participants, we evaluated the associations of 6,790 circulating proteins with all-cause mortality using multivariable Cox proportional hazards models. Proteins with significant associations were further studied in ARIC Visit 5 participants with CKD. Results: In the AASK cohort, the mean age was 54.5 years, 271 (38.5%) were women, and the mean measured glomerular filtration rate (GFR) was 46 mL/min/1.73 m2. The median follow-up was 9.6 years, and 7 distinct proteins were associated with all-cause mortality at the Bonferroni-level threshold (P < 0.05 of the 6,790) after adjustment for demographics and clinical factors, including baseline measured estimated GFR and proteinuria. In the ARIC visit 5 cohort, the mean age was 77.2 years, 903 (55.5%) were women, the mean estimated GFR was 54 mL/min/1.73 m2 and median follow-up was 6.9 years. Of the 7 proteins found in AASK, 3 (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide) were available in the ARIC data, with all 3 significantly associated with death in ARIC. Limitations: Possibility of unmeasured confounding. Cause of death was not known. Conclusions: Using large-scale proteomic analysis, proteins were reproducibly associated with mortality in 2 cohorts of participants with CKD. Plain-Language Summary: Patients with chronic kidney disease (CKD) have a high risk of premature death, with various pathophysiological processes contributing to this increased risk of mortality. This observational cohort study aimed to investigate the associations between circulating proteins and all-cause mortality in patients with CKD using large-scale proteomic analysis. The study analyzed data from the African American Study of Kidney Disease and Hypertension (AASK) study and validated the findings in the Atherosclerosis Risk in Communities (ARIC) Study. A total of 6,790 circulating proteins were evaluated in AASK, and 7 proteins were significantly associated with all-cause mortality. Three of these proteins (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide (BNP)) were also measured in ARIC and were significantly associated with death. Additional studies assessing biomarkers associated with mortality among patients with CKD are needed to evaluate their use in clinical practice

Metabolically Healthy Obesity and Risk of Kidney Function Decline

Objective: The aim of this study was to examine the association between BMI categories, stratified by metabolic health status, and the risk of kidney function decline (KFD). Methods: In this study, 42,128 adult patients with a stable BMI were classified over a 3-year baseline window by BMI and metabolic health status (assessed by Adult Treatment Panel-III criteria). KFD was defined as an estimated glomerular filtration rate (eGFR) decline ≥ 30%, eGFR \u3c 15 mL/min/1.73 m2, or receipt of dialysis and/or transplant. Results: Over a median of 5.1 years (interquartile range 2.1-8.9), 6,533 (15.5%) individuals developed KFD. Compared with the normal weight, metabolically healthy category, metabolically healthy obesity was associated with a higher risk of KFD (adjusted hazard ratio [aHR] 1.52; 95% CI: 1.22-1.89). aHRs for KFD were 1.17 (95% CI: 0.89-1.53), 2.21 (95% CI: 1.59-3.08), and 2.20 (95% CI: 1.55-3.11) for metabolically healthy obesity with BMI 30 to 34.9, BMI 35 to 39.9, and BMI ≥ 40 kg/m2. These associations were consistent among men and women, patients with eGFR ≥ or \u3c 90 mL/min/1.73 m2, and age ≥ or \u3c 55 years. The risk of KFD was highest among metabolically unhealthy individuals with BMI ≥ 40 (aHR 4.02; 95% CI: 3.40-4.75 vs. metabolically healthy individuals with normal weight). Conclusions: Obesity, whether in the presence or absence of metabolic health, is a risk factor for KFD

Development and validation of the American Heart Association Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations

Background: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the AHA Predicting Risk of CVD EVENTs (PREVENT) equations among US adults aged 30-79 years without known CVD.Methods: The derivation sample included individual-level participant data from 25 datasets (N=3,281,919) between 1992-2017. The primary outcome was CVD (atherosclerotic CVD [ASCVD] and heart failure [HF]). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, anti-hypertensive or statin use, diabetes) and estimated glomerular filtration rate [eGFR]. Models were sex-specific, race-free, developed on the age-scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each dataset and meta-analyzed. Discrimination was assessed using Harrell\u27s C-statistic. Calibration was calculated as the slope of the observed vs. predicted risk by decile. Additional equations to predict each CVD subtype (ASCVD, HF) and include optional predictors (urine albumin-to-creatinine ratio [UACR], hemoglobin A1c [HbA1c]), and social deprivation index [SDI]) were also developed. External validation was performed in 3,330,085 participants from 21 additional datasets.Results: Among 6,612,004 adults included, mean (SD) age was 53 (12) years and 56% were female. Over a mean (SD) follow-up of 4.8 (3.1) years, there were 211,515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval [IQI]: 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (IQI 0.81 -1.16) and 0.94 (0.81-1.13) among females and males, respectively. Similar estimates for discrimination and calibration were observed for ASCVD- and HF-specific models. The improvement in discrimination was small but statistically significant when UACR, HbA1c, and SDI were added together to the base model to total CVD (ΔC-statistic [IQI] 0.004 [0.004, 0.005] and 0.005 [0.004, 0.007] among females and males, respectively). Calibration improved significantly when UACR was added to the base model among those with marked albuminuria (\u3e300mg/g) (1.05 [0.84-1.20] vs. 1.39 [1.14-1.65], p=0.01).Conclusions: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults using routinely available clinical variables

Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium

Contains fulltext : 201236.pdf (publisher's version ) (Closed access