Five-Year Cumulative Cardiovascular Health and Clinical Events in Patients With Chronic Kidney Disease: The CRIC Study.

BACKGROUND: Higher cardiovascular health (CVH) score is associated with lower risks of cardiovascular disease (CVD) and mortality in the general population. However, it is unclear whether cumulative CVH is associated with CVD, end-stage kidney disease (ESKD), and death in patients with chronic kidney disease. METHODS AND RESULTS: Among individuals from the prospective CRIC (Chronic Renal Insufficiency Cohort) Study, we used the percentage of the maximum possible CVH score attained from baseline to the year 5 visit to calculate cumulative CVH score. Multivariable-adjusted Cox proportional hazards regression was used to investigate the associations of cumulative CVH with risks of adjudicated CVD (myocardial infarction, stroke, and heart failure), ESKD, and all-cause mortality. A total of 3939 participants (mean age, 57.7 years; 54.9% men) were included. The mean (SD) cumulative CVH score attained during 5 years was 55.5% (12.3%). Over a subsequent median 10.2-year follow-up, 597 participants developed CVD, 656 had ESKD, and 1324 died. A higher cumulative CVH score was significantly associated with lower risks of CVD, ESKD, and mortality, independent of the CVH score at year 5. Multivariable-adjusted hazard ratios and 95% CIs per 10% higher cumulative CVH score during 5 years were 0.81 (0.69-0.95) for CVD, 0.82 (0.70-0.97) for ESKD, and 0.80 (0.72-0.89) for mortality. CONCLUSIONS: Among patients with chronic kidney disease stages 2 to 4, a better CVH status maintained throughout 5 years is associated with lower risks of CVD, ESKD, and all-cause mortality. The findings support the need for interventions to maintain ideal CVH status for prevention of adverse outcomes in the population with chronic kidney disease.

Depressive Symptoms, Antidepressants, and Clinical Outcomes in Chronic Kidney Disease: Findings from the CRIC Study.

Rationale & Objective: The extent to which depression affects the progression of chronic kidney disease (CKD) and leads to adverse clinical outcomes remains inadequately understood. We examined the association of depressive symptoms (DS) and antidepressant medication use on clinical outcomes in 4,839 adults with nondialysis CKD. Study Design: Observational cohort study. Setting and Participants: Adults with mild to moderate CKD who participated in the multicenter Chronic Renal Insufficiency Cohort Study (CRIC). Exposure: The Beck Depression Inventory (BDI) was used to quantify DS. Antidepressant use was identified from medication bottles and prescription lists. Individual effects of DS and antidepressants were examined along with categorization as follows: (1) BDI <11 and no antidepressant use, (2) BDI <11 with antidepressant use, (3) BDI ≥11 and no antidepressant use, and (4) BDI ≥11 with antidepressant use. Outcomes: CKD progression, incident cardiovascular disease composite, all-cause hospitalizations, and mortality. Analytic Approach: Cox regression models were fitted for outcomes of CKD progression, incident cardiovascular disease, and all-cause mortality, whereas hospitalizations used Poisson regression. Results: At baseline, 27.3% of participants had elevated DS, and 19.7% used antidepressants. Elevated DS at baseline were associated with significantly greater risk for an incident cardiovascular disease event, hospitalization, and all-cause mortality, but not CKD progression, adjusted for antidepressants. Antidepressant use was associated with higher risk for all-cause mortality and hospitalizations, after adjusting for DS. Compared to participants without elevated DS and not using antidepressants, the remaining groups (BDI <11 with antidepressants; BDI ≥11 and no antidepressants; BDI ≥11 with antidepressants) showed higher risks of hospitalization and all-cause mortality. Limitations: Inability to infer causality among depressive symptoms, antidepressants, and outcomes. Additionally, the absence of nonpharmacological data, and required exploration of generalizability and alternative analytical approaches. Conclusions: Elevated DS increased adverse outcome risk in nondialysis CKD, unattenuated by antidepressants. Additionally, investigation into the utilization and counterproductivity of antidepressants in this population is warranted.

We analyzed data from 4,839 nondialysis chronic kidney disease (CKD) patients in the Chronic Renal Insufficiency Cohort Study to explore how depression and antidepressants affect CKD-related outcomes. Using the Beck Depression Inventory (BDI), we assessed depressive symptoms (DS) and identified antidepressant use through medication records. Outcomes included CKD progression, cardiovascular events, hospitalizations, and mortality. Elevated DS at baseline raised the risk of cardiovascular events, hospitalizations, and mortality, regardless of antidepressant use. Antidepressant use alone was associated with higher mortality and hospitalization risks. In comparison to those without elevated DS and no antidepressant use, all other groups faced increased hospitalization and mortality risks. Elevated DS posed a significant risk to nondialysis CKD patients, and antidepressants did not mitigate this risk.

Social, Behavioral, and Metabolic Risk Factors and Racial Disparities in Cardiovascular Disease Mortality in U.S. Adults : An Observational Study.

BACKGROUND: Cardiovascular disease (CVD) mortality is persistently higher in the Black population than in other racial and ethnic groups in the United States. OBJECTIVE: To examine the degree to which social, behavioral, and metabolic risk factors are associated with CVD mortality and the extent to which racial differences in CVD mortality persist after these factors are accounted for. DESIGN: Prospective cohort study. SETTING: NHANES (National Health and Nutrition Examination Survey) 1999 to 2018. PARTICIPANTS: A nationally representative sample of 50 808 persons aged 20 years or older. MEASUREMENTS: Data on social, behavioral, and metabolic factors were collected in each NHANES survey using standard methods. Deaths from CVD were ascertained from linkage to the National Death Index with follow-up through 2019. RESULTS: Over an average of 9.4 years of follow-up, 2589 CVD deaths were confirmed. The age- and sex-standardized rates of CVD mortality were 484.7 deaths per 100 000 person-years in Black participants, 384.5 deaths per 100 000 person-years in White participants, 292.4 deaths per 100 000 person-years in Hispanic participants, and 255.1 deaths per 100 000 person-years in other race groups. In a multiple Cox regression analysis adjusted for all measured risk factors simultaneously, several social (unemployment, low family income, food insecurity, lack of home ownership, and unpartnered status), behavioral (current smoking, lack of leisure-time physical activity, and sleep <6 or >8 h/d), and metabolic (obesity, hypertension, and diabetes) risk factors were associated with a significantly higher risk for CVD death. After adjustment for these metabolic, behavioral, and social risk factors separately, hazard ratios of CVD mortality for Black compared with White participants were attenuated from 1.54 (95% CI, 1.34 to 1.77) to 1.34 (CI, 1.16 to 1.55), 1.31 (CI, 1.15 to 1.50), and 1.04 (CI, 0.90 to 1.21), respectively. LIMITATION: Causal contributions of social, behavioral, and metabolic risk factors to racial and ethnic disparities in CVD mortality could not be established. CONCLUSION: The Black-White difference in CVD mortality diminished after adjustment for behavioral and metabolic risk factors and completely dissipated with adjustment for social determinants of health in the U.S. population. PRIMARY FUNDING SOURCE: National Institutes of Health.

Lipoprotein(a) and the Risk for Recurrent Atherosclerotic Cardiovascular Events Among Adults With CKD: The Chronic Renal Insufficiency Cohort (CRIC) Study.

Rationale & Objective: Many adults with chronic kidney disease (CKD) and atherosclerotic cardiovascular disease (ASCVD) have high lipoprotein(a) levels. It is unclear whether high lipoprotein(a) levels confer an increased risk for recurrent ASCVD events in this population. We estimated the risk for recurrent ASCVD events associated with lipoprotein(a) in adults with CKD and prevalent ASCVD. Study Design: Observational cohort study. Setting & Participants: We included 1,439 adults with CKD and prevalent ASCVD not on dialysis enrolled in the Chronic Renal Insufficiency Cohort study between 2003 and 2008. Exposure: Baseline lipoprotein(a) mass concentration, measured using a latex-enhanced immunoturbidimetric assay. Outcomes: Recurrent ASCVD events (primary outcome), kidney failure, and death (exploratory outcomes) through 2019. Analytical Approach: We used Cox proportional-hazards regression models to estimate adjusted HR (aHRs) and 95% CIs. Results: Among participants included in the current analysis (mean age 61.6 years, median lipoprotein(a) 29.4 mg/dL [25th-75th percentiles 9.9-70.9 mg/dL]), 641 had a recurrent ASCVD event, 510 developed kidney failure, and 845 died over a median follow-up of 6.6 years. The aHR for ASCVD events associated with 1 standard deviation (SD) higher log-transformed lipoprotein(a) was 1.04 (95% CI, 0.95-1.15). In subgroup analyses, 1 SD higher log-lipoprotein(a) was associated with an increased risk for ASCVD events in participants without diabetes (aHR, 1.23; 95% CI, 1.02-1.48), but there was no evidence of an association among those with diabetes (aHR, 0.99; 95% CI, 0.88-1.10, P comparing aHRs = 0.031). The aHR associated with 1 SD higher log-lipoprotein(a) in the overall study population was 1.16 (95% CI, 1.04-1.28) for kidney failure and 1.02 (95% CI, 0.94-1.11) for death. Limitations: Lipoprotein(a) was not available in molar concentration. Conclusions: Lipoprotein(a) was not associated with the risk for recurrent ASCVD events in adults with CKD, although it was associated with a risk for kidney failure.

A prediction model on incident chronic kidney disease among individuals with type 2 diabetes in the United States.

AIM: Early identification of incident chronic kidney disease (CKD) in individuals with diabetes may help improve patients' clinical outcomes. This study aimed to develop a prediction equation for incident CKD among people with type 2 diabetes (T2D). MATERIALS AND METHODS: A time-varying Cox model was applied to data from the ACCORD trial to predict the risk of incident CKD. A list of candidate variables was chosen based on literature reviews and experts' consultations, including demographic characteristics, vitals, laboratory results, medical history, drug use and health care utilization. Model performance was evaluated. Decomposition analysis was conducted, and external validation was performed. RESULTS: In total, 6006 patients with diabetes free of CKD were included, with a median follow-up of 3 years and 2257 events. The risk model included age at T2D diagnosed, smoking status, body mass index, high-density lipoprotein, very-low-density lipoprotein, alanine aminotransferase, estimated glomerular filtration rate, urine albumin-creatinine ratio, hypoglycaemia, retinopathy, congestive heart failure, coronary heart disease history, antihyperlipidaemic drug use, antihypertensive drug use and hospitalization. The urine albumin-creatinine ratio, estimated glomerular filtration rate and congestive heart failure were the top three factors that contributed most to the incident CKD prediction. The model showed acceptable discrimination [C-statistic: 0.772 (95% CI 0.767-0.805)] and calibration [Brier Score: 0.0504 (95% CI 0.0477-0.0531)] in the Harmony Outcomes Trial. CONCLUSION: Incident CKD prediction among individuals with T2D was developed and validated for use in decision support of CKD prevention.

Effects of epigenetic age acceleration on kidney function: a Mendelian randomization study.

BACKGROUND: Previous studies have reported cross-sectional associations between measures of epigenetic age acceleration (EAA) and kidney function phenotypes. However, the temporal and potentially causal relationships between these variables remain unclear. We conducted a bidirectional two-sample Mendelian randomization study of EAA and kidney function. Genetic instruments for EAA and estimate glomerular filtration rate (eGFR) were identified from previous genome-wide association study (GWAS) meta-analyses of European-ancestry participants. Causal effects of EAA on kidney function and kidney function on EAA were assessed through summary-based Mendelian randomization utilizing data from the CKDGen GWAS meta-analysis of log-transformed estimated glomerular filtration rate (log-eGFR; n = 5,67,460) and GWAS meta-analyses of EAA (n = 34,710). An allele score-based Mendelian randomization leveraging individual-level data from UK Biobank participants (n = 4,33,462) further examined the effects of EAA on kidney function. RESULTS: Using summary-based Mendelian randomization, we found that each 5 year increase in intrinsic EAA (IEAA) and GrimAge acceleration (GrimAA) was associated with - 0.01 and - 0.02 unit decreases in log-eGFR, respectively (P = 0.02 and P = 0.09, respectively), findings which were strongly supported by allele-based Mendelian randomization study (both P < 0.001). Summary-based Mendelian randomization identified 24% increased odds of CKD with each 5-unit increase in IEAA (P = 0.05), with consistent findings observed in allele score-based analysis (P = 0.07). Reverse-direction Mendelian randomization identified potentially causal effects of decreased kidney function on HannumAge acceleration (HannumAA), GrimAA, and PhenoAge acceleration (PhenoAA), conferring 3.14, 1.99, and 2.88 year decreases in HanumAA, GrimAA, and PhenoAA, respectively (P = 0.003, 0.05, and 0.002, respectively) with each 1-unit increase in log-eGFR. CONCLUSION: This study supports bidirectional causal relationships between EAA and kidney function, pointing to potential prevention and therapeutic strategies.

A prediction model on incident ESKD among individuals with T2D and CKD.

BACKGROUND: Diabetes is the leading cause of end-stage kidney disease (ESKD). This study aimed to predict incident ESKD among individuals with T2D and CKD. METHOD: The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial data were split into a training set and a validation set by a ratio of 7:3. A dynamic time-varying Cox model was fit to predict the development of incident ESKD. Significant predictors were identified from a list of candidate variables, including demographic characteristics, physical exam results, laboratory results, medical history, drug information, and healthcare utilization. Model performance was evaluated by Brier score and C statistics. Decomposition analysis was conducted to assess the variable importance. Patient-level data from Harmony Outcome clinical trial and CRIC study were used for external validation. RESULTS: A total of 6982 diabetes patients with CKD were used for model development, with a median follow-up of four years and 312 ESKD events. The significant predictors for the final model were female sex, race, smoking status, age at T2D diagnosis, SBP, HR, HbA1c, estimated glomerular filtration rate (eGFR), urine albumin-creatinine ratio (UACR), retinopathy event occurring in last year, antihypertensive drug use, and an interaction term between SBP and female. The model demonstrated good performance in discrimination (C-statistic 0.764 [95 % CI 0.763-0.811]) and calibration (Brier Score 0.0083 [95 % CI 0.0063-0.0108]). The top 3 most important predictors in the prediction model were eGFR, retinopathy event, and UACR. Acceptable discrimination (C-statistic: 0.701 [95 % CI 0.665-0.716]; 0.86 [95 % CI 0.847-0.872]) and calibration (Brier Score: 0.0794 [95 % CI 0.0733-0.1022]; 0.0476 [95 % CI 0.0440, 0.0506]) were demonstrated in the Harmony Outcome and CRIC data, respectively. CONCLUSION: The dynamic risk prediction of incident ESKD among individuals with T2D can be a useful tool to support better disease management to lower the risk of developing ESKD.

A prediction model of CKD progression among individuals with type 2 diabetes in the United States.

BACKGROUND: CKD progression among individuals with T2D is associated with poor health outcomes and high healthcare costs, which have not been fully studied. This study aimed to predict CKD progression among individuals with diabetes. METHOD: Using ACCORD trial data, a time-varying Cox model was developed to predict the risk of CKD progression among patients with CKD and T2D. CKD progression was defined as a 50 % decline, or 25 mL/min/1.73 m2 decline in eGFR from baseline, doubling of the serum creatinine, or onset of ESKD. A list of candidate variables included demographic characteristics, physical exam results, laboratory results, medical history, drug use, and healthcare utilization. A stepwise algorithm was used for variable selection. Model performance was evaluated by Brier score and C-statistics. Confidence intervals (CI) were calculated using a bootstrap method. Decomposition analysis was conducted to assess the predictor contribution. Generalizability was assessed on patient-level data of the Harmony Outcome trial and CRIC study. RESULTS: A total of 6982 diabetes patients with CKD were used for model development, with a median follow-up of 4 years and 3346 events. The predictors for CKD progression included female sex, age at T2D diagnosis, smoking status, SBP, DBP, HR, HbA1c, alanine aminotransferase (ALT), eGFR, UACR, retinopathy event, hospitalization. The model demonstrated good discrimination (C-statistics 0.745 [95 % CI 0.723-0.763]) and calibration (Brier Score 0.0923 [95 % CI 0.0873-0.0965]) performance in the ACCORD data. The most contributing predictors for CKD progression were eGFR, HbA1c, and SBP. The model demonstrated acceptable discrimination and calibration performance in the two external data. CONCLUSION: For high-risk patients with both diabetes and CKD, the tool as a dynamic risk prediction of CKD progression may help develop novel strategies to lower the risk of CKD progression.

Cardiac Biomarkers and Risk of Atherosclerotic Cardiovascular Disease in Patients with CKD.

Background: Several cardiac biomarkers of cardiac stress, inflammation, and fibrosis (N-terminal pro brain-type natriuretic peptide [NT-proBNP], high-sensitivity troponin T [hsTnT], growth differentiation factor 15 [GDF-15], and soluble ST2 [sST2]) have been associated with atherosclerotic disease in the general population. We hypothesized that these cardiac biomarkers may also be associated with the atherosclerotic cardiovascular disease in patients with CKD. Methods: We analyzed levels of NT-proBNP, hsTnT, GDF-15, and sST2 in a cohort of 2732 participants with mild to moderate CKD from the Chronic Renal Insufficiency Cohort (CRIC) study. Outcomes included incident atherosclerotic disease, defined as the first instance of myocardial infarction, stroke, or peripheral vascular disease. We used Cox proportional hazard models to the test the association of each cardiac biomarker with risk of incident atherosclerotic disease, adjusting for multiple possible confounders. Results: When modeled continuously (per SD increase in the log-transformed biomarker), NT-proBNP, hsTnT, GDF-15, and sST2 were significantly associated with incident atherosclerotic disease after adjustment for multiple potential confounders: (NT-proBNP HR, 1.51; 95% CI, 1.27 to 1.81; hsTnT HR, 1.61; 95% CI, 1.38 to 1.89; GDF-15 HR, 1.44; 95% CI, 1.19 to 1.73; and sST2 HR, 1.19; 95% CI, 1.04 to 1.36). Conclusions: NT-proBNP, hsTnT, GDF-15, and sST2 were significantly associated with incident atherosclerotic cardiovascular disease in patients with CKD. These associations may highlight important mechanisms for the development of atherosclerotic disease in CKD.

Vitamin K Status and Cognitive Function in Adults with Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort.

Vitamin K is linked to cognitive function, but studies in individuals with chronic kidney disease (CKD), who are at risk for vitamin K insufficiency and cognitive impairment, are lacking. The cross-sectional association of vitamin K status biomarkers with cognitive performance was evaluated in ≥55-y-old adults with CKD (N = 714, 49% female, 44% black). A composite score of a cognitive performance test battery, calculated by averaging the z scores of the individual tests, was the primary outcome. Vitamin K status was measured using plasma phylloquinone and dephospho-uncarboxylated matrix Gla protein [(dp)ucMGP]. Participants with low plasma (dp)ucMGP, reflecting higher vitamin K status, had better cognitive performance than those in the two higher (dp)ucMGP categories based on the composite outcome (P = 0.03), whereas it did not significantly differ according to plasma phylloquinone categories (P = 0.08). Neither biomarker was significantly associated with performance on individual tests (all P > 0.05). The importance of vitamin K to cognitive performance in adults with CKD remains to be clarified.

Predicting incident heart failure among patients with type 2 diabetes mellitus: The DM-CURE risk score.

AIM: Early identification and prediction of incident heart failure (HF) is important because of severe morbidity and mortality. This study aimed to predict onset of HF among patients with diabetes. METHODS: A time-varying Cox model was derived from ACCORD clinical trial to predict the risk of incident HF, defined by hospitalization for HF (HHF). External validation was performed on patient-level data from the Harmony Outcome trial and Chronic Renal Insufficiency Cohort (CRIC) study. The model was transformed into an integer-based scoring algorithm for 10-year risk evaluation. A stepwise algorithm identified and selected predictors from demographic characteristics, physical examination, laboratory results, medical history, medication and health care utilization, to develop a risk prediction model. The main outcome was incident HF, defined by HHF. The C statistic and Brier score were used to assess model performance. RESULTS: In total, 9649 patients with diabetes free of HF were used, with median follow-up of 4 years and 299 incident hospitalization of HF events. The model identified several predictors for the 10-year HF incidence risk score 'DM-CURE': socio-Demographic [education, age at type 2 diabetes (T2DM) diagnosis], Metabolic (glycated haemoglobin, systolic blood pressure, body mass index, high-density lipoproteins), diabetes-related Complications (myocardial infarction, revascularization, cardiovascular medications, neuropathy, hypertension duration, albuminuria, urine albumin-to-creatinine ratio, End Stage Kidney Disease), and health care Utilization (all-cause hospitalization, emergency room visits) for Risk Evaluation. Among them, the strongest impact factors for future HF were age at T2DM diagnosis, health care utilization and cardiovascular disease-related variables. The model showed good discrimination (C statistic: 0.838, 95% CI: 0.821-0.855) and calibration (Brier score: 0.006, 95% CI: 0.006-0.007) in the ACCORD data and good performance in the validation data (Harmony: C statistic: 0.881, 95% CI: 0.863-0.899; CRIC: C statistic: 0.813, 95% CI: 0.794-0.833). The 10-year risk of incident HF increased in a graded fashion, from ≤1% in quintile 1 (score ≤14), 1%-5% in quintile 2 (score 15-23), 5%-10% in quintile 3 (score 24-27), 10%-20% in quintile 4 (score 28-33) and ≥20% in quintile 5 (score >33). CONCLUSIONS: The DM-CURE model and score were useful for population risk stratification of incident HHF among patients with T2DM and can be easily applied in clinical practice.

Menopausal hormone therapy and risk of cardiovascular events in women with prediabetes or type 2 diabetes: A pooled analysis of 2917 postmenopausal women.

BACKGROUND AND AIMS: The effect of MHT on cardiovascular disease (CVD) risk among women with prediabetes or type 2 diabetes (PreDM or T2DM) is unclear. We examined the association between ever or early use MHT and CVD risk in postmenopausal women with PreDM or T2DM, and the potential modifying effect of race. METHODS: 2,917 postmenopausal women with PreDM or T2DM were pooled from 3 prospective CVD cohorts (the Atherosclerosis Risk in Communities, the Multi-Ethnic Study of Atherosclerosis, and the Jackson Heart Study). Ever (yes vs no) or early use of MHT (MHT initiated ≤5 vs > 5 years since menopause), and their associations with ischemic stroke, coronary heart disease (CHD), and atherosclerotic cardiovascular disease (ASCVD) were assessed using Cox proportional hazards models. RESULTS: During a median follow-up of 15 years, 264 stroke, 484 CHD, and 659 ASCVD events were observed. In fully adjusted models, ever use of MHT was associated with reduced risk of stroke (hazard ratio 0.86, 95% CI 0.76-0.98), CHD (0.85, 0.74-0.98), and ASCVD (0.83, 0.73-0.95) in white women with PreDM or T2DM. Early use of MHT was associated with reduced risk of stroke (0.82, 0.72-0.95), CHD (0.85, 0.74-0.98), and ASCVD (0.82, 0.70-0.96) in the white group. No risk reduction with ever or early use of MHT was found for black women with PreDM or T2DM. CONCLUSIONS: MHT is associated with statistically reduced CVD risk among white but not black women with PreDM or DM. Race is an effect modifier in the association between MHT use and CVD.

Prediction of End-Stage Kidney Disease Using Estimated Glomerular Filtration Rate With and Without Race : A Prospective Cohort Study.

BACKGROUND: New estimated glomerular filtration rate (eGFR) equations removed race adjustment, but the impact of its removal on prediction of end-stage kidney disease (ESKD) is unknown. OBJECTIVE: To compare the ESKD prediction performance of different eGFR equations. DESIGN: Observational, prospective cohort study. SETTING: 7 U.S. clinical centers. PARTICIPANTS: 3873 participants with chronic kidney disease (CKD) from the CRIC (Chronic Renal Insufficiency Cohort) Study contributing 13 902 two-year risk periods. MEASUREMENTS: ESKD was defined as initiation of dialysis or transplantation. eGFR was calculated using 5 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on serum creatinine and/or cystatin C, with or without race adjustment. The predicted 2-year risk for ESKD was calculated using the 4-variable Kidney Failure Risk Equation (KFRE). We evaluated the prediction performance of eGFR equations and the KFRE score using discrimination and calibration analyses. RESULTS: During a maximum 16 years of follow-up, 856 participants developed ESKD. Across all eGFR equations, the KFRE score was superior for predicting 2-year incidence of ESKD compared with eGFR alone (area under the curve ranges, 0.945 to 0.954 vs. 0.900 to 0.927). Prediction performance of KFRE scores using different eGFR equations was similar, but the creatinine equation without race adjustment improved calibration among Black participants. Among all participants, compared with an eGFR less than 20 mL/min/1.73 m2, a KFRE score greater than 20% had similar specificity for predicting 2-year ESKD risk (ranges, 0.94 to 0.97 vs. 0.95 to 0.98) but higher sensitivity (ranges, 0.68 to 0.78 vs. 0.42 to 0.66). LIMITATION: Data are solely from the United States. CONCLUSION: The KFRE score better predicts 2-year risk for ESKD compared with eGFR alone, regardless of race adjustment. The creatinine equation with age and sex may improve calibration among Black patients. A KFRE score greater than 20% showed high specificity and sensitivity for predicting 2-year risk for ESKD. PRIMARY FUNDING SOURCE: National Institutes of Health.

Atherosclerotic Cardiovascular Disease Events in Adults With CKD Taking a Moderate- or High-Intensity Statin: The Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: The 2018 American Heart Association/American College of Cardiology (AHA/ACC) cholesterol guideline uses risk stratification to guide the decision to initiate nonstatin lipid-lowering medication among adults with atherosclerotic cardiovascular disease (CVD). We determined atherosclerotic CVD (ASCVD) event rates among adults with chronic kidney disease (CKD) taking statin therapy within 2018 AHA/ACC cholesterol guideline risk categories. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: Adults with CKD not on dialysis in the Chronic Renal Insufficiency Cohort (CRIC) study who were taking a moderate/high-intensity statin 1 year after enrollment (baseline for the current analysis, n = 1,753). EXPOSURE: 2018 AHA/ACC cholesterol guideline risk categories: without a history of ASCVD, a history of 1 major ASCVD event and multiple high-risk conditions, and a history of ≥2 major ASCVD events. OUTCOME: Adjudicated ASCVD events after the year 1 study visit. ANALYTICAL APPROACH: We calculated age-sex standardized rates for ASCVD events and age-sex adjusted hazard ratios for ASCVD events accounting for the competing risk of death. RESULTS: There were 394 ASCVD events over a median follow-up period of 8 years. The ASCVD event rates (with 95% CI) per 1,000 person-years among participants without a history of ASCVD, with a history of 1 major ASCVD event and multiple high-risk conditions, and with a history of ≥2 major ASCVD events were 21.7 (18.4-25.1), 45.0 (37.8-52.3), and 73.3 (53.3-93.4), respectively. Compared with participants without a history of ASCVD, the HR (95% CI) rates for ASCVD events among those with a history of 1 major ASCVD event and multiple high-risk conditions, and with a history of ≥2 major ASCVD events were 1.89 (1.52-2.36) and 2.50 (1.85-3.39), respectively. LIMITATIONS: Data on whether participants were taking a maximally tolerated statin dosage were unavailable. CONCLUSIONS: The 2018 AHA/ACC cholesterol guideline identifies adults with CKD who have very high ASCVD risk despite taking a moderate/high-intensity statin.

Race, Genetic Ancestry, and Estimating Kidney Function in CKD.

BACKGROUND: The inclusion of race in equations to estimate the glomerular filtration rate (GFR) has become controversial. Alternative equations that can be used to achieve similar accuracy without the use of race are needed. METHODS: In a large national study involving adults with chronic kidney disease, we conducted cross-sectional analyses of baseline data from 1248 participants for whom data, including the following, had been collected: race as reported by the participant, genetic ancestry markers, and the serum creatinine, serum cystatin C, and 24-hour urinary creatinine levels. RESULTS: Using current formulations of GFR estimating equations, we found that in participants who identified as Black, a model that omitted race resulted in more underestimation of the GFR (median difference between measured and estimated GFR, 3.99 ml per minute per 1.73 m2 of body-surface area; 95% confidence interval [CI], 2.17 to 5.62) and lower accuracy (percent of estimated GFR within 10% of measured GFR [P10], 31%; 95% CI, 24 to 39) than models that included race (median difference, 1.11 ml per minute per 1.73 m2; 95% CI, -0.29 to 2.54; P10, 42%; 95% CI, 34 to 50). The incorporation of genetic ancestry data instead of race resulted in similar estimates of the GFR (median difference, 1.33 ml per minute per 1.73 m2; 95% CI, -0.12 to 2.33; P10, 42%; 95% CI, 34 to 50). The inclusion of non-GFR determinants of the serum creatinine level (e.g., body-composition metrics and urinary excretion of creatinine) that differed according to race reported by the participants and genetic ancestry did not eliminate the misclassification introduced by removing race (or ancestry) from serum creatinine-based GFR estimating equations. In contrast, the incorporation of race or ancestry was not necessary to achieve similarly statistically unbiased (median difference, 0.33 ml per minute per 1.73 m2; 95% CI, -1.43 to 1.92) and accurate (P10, 41%; 95% CI, 34 to 49) estimates in Black participants when GFR was estimated with the use of cystatin C. CONCLUSIONS: The use of the serum creatinine level to estimate the GFR without race (or genetic ancestry) introduced systematic misclassification that could not be eliminated even when numerous non-GFR determinants of the serum creatinine level were accounted for. The estimation of GFR with the use of cystatin C generated similar results while eliminating the negative consequences of the current race-based approaches. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others.).

Early Menopause and Cardiovascular Disease Risk in Women With or Without Type 2 Diabetes: A Pooled Analysis of 9,374 Postmenopausal Women.

OBJECTIVE: Early menopause may be associated with higher cardiovascular disease (CVD) risk. Type 2 diabetes mellitus (T2DM), coupled with early menopause, may result in even greater CVD risk in women. We examined CVD risk in women with early compared with normal-age menopause, with and without T2DM overall, and by race/ethnicity. RESEARCH DESIGN AND METHODS: We pooled data from the Atherosclerosis Risk in Communities study, the Multi-Ethnic Study of Atherosclerosis, and the Jackson Heart Study. We included women with data on menopausal status, menopausal age, and T2DM, excluding pre- or perimenopausal women and those with prevalent CVD. Outcomes included incident coronary heart disease (CHD), stroke, heart failure (HF), and atherosclerotic cardiovascular disease (ASCVD) (CHD or stroke). We estimated the risk associated with early (<45 years) compared with normal-age menopause using Cox proportional hazards models. Covariates included age, race/ethnicity, education, BMI, blood pressure, cholesterol, smoking, alcohol consumption, antihypertensive medication, lipid-lowering medication, hormone therapy use, and pregnancy history. RESULTS: We included 9,374 postmenopausal women for a median follow-up of 15 years. We observed 1,068 CHD, 659 stroke, 1,412 HF, and 1,567 ASCVD events. T2DM significantly modified the effect of early menopause on CVD risk. Adjusted hazard ratios for early menopause and the outcomes were greater in women with T2DM versus those without (CHD 1.15 [95% CI 1.00, 1.33] vs. 1.09 [1.03, 1.15]; stroke 1.21 [1.04, 1.40] vs. 1.10 [1.04, 1.16]; ASCVD 1.29 [1.09, 1.51] vs. 1.10 [1.04, 1.17]; HF 1.18 [1.00, 1.39] vs. 1.09 [1.03, 1.16]). The modifying effect of T2DM on the association between early menopause and ASCVD was only statistically significant in Black compared with White women. CONCLUSIONS: Early menopause was associated with an increased risk for CVD in postmenopausal women. T2DM may further augment the risk, particularly in Black women.

Plasma Metabolomic Signatures of Healthy Dietary Patterns in the Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: In individuals with chronic kidney disease (CKD), healthy dietary patterns are inversely associated with CKD progression. Metabolomics, an approach that measures many small molecules in biofluids, can identify biomarkers of healthy dietary patterns. OBJECTIVES: We aimed to identify known metabolites associated with greater adherence to 4 healthy dietary patterns in CKD patients. METHODS: We examined associations between 486 known plasma metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension (DASH) diet, and alternate Mediterranean diet (aMED) in 1056 participants (aged 21-74 y at baseline) in the Chronic Renal Insufficiency Cohort (CRIC) Study. Usual dietary intake was assessed using a semiquantitative FFQ. We conducted multivariable linear regression models to study associations between healthy dietary patterns and individual plasma metabolites, adjusting for sociodemographic characteristics, health behaviors, and clinical factors. We used principal component analysis to identify groups of metabolites associated with individual food components within healthy dietary patterns. RESULTS: After Bonferroni correction, we identified 266 statistically significant diet-metabolite associations (HEI: n = 60; AHEI: n = 78; DASH: n = 77; aMED: n = 51); 78 metabolites were associated with >1 dietary pattern. Lipids with a longer acyl chain length and double bonds (unsaturated) were positively associated with all 4 dietary patterns. A metabolite pattern low in saturated diacylglycerols and triacylglycerols, and a pattern high in unsaturated triacylglycerols was positively associated with intake of healthy food components. Plasmalogens were negatively associated with the consumption of nuts and legumes and healthy fat, and positively associated with the intake of red and processed meat. CONCLUSIONS: We identified many metabolites associated with healthy dietary patterns, indicative of food consumption. If replicated, these metabolites may be considered biomarkers of healthy dietary patterns in patients with CKD.

Effect of Kidney Function on Relationships between Lifestyle Behaviors and Mortality or Cardiovascular Outcomes: A Pooled Cohort Analysis.

BACKGROUND: Adherence to healthy behaviors reduces risks of cardiovascular disease and death in the general population. However, among people with kidney disease, a group at higher risk for cardiovascular disease, such benefits have not been established. METHODS: We pooled data from three cohort studies with a total of 27,271 participants. Kidney function was categorized on the basis of eGFR (≥60, 45 to <60, and <45 ml/min per 1.73 m2). We used proportional hazard frailty models to estimate associations between healthy behaviors (not smoking, at recommended body mass index [BMI], physical activity, healthy diet, and moderate to no alcohol intake) and outcomes (all-cause death, major coronary events, ischemic stroke, and heart failure events). RESULTS: All recommended lifestyle behaviors were significantly associated with lower risks of death, regardless of eGFR. Not smoking (versus current) and any moderate to vigorous physical activity (versus none) was significantly associated with reduced risks of major coronary and heart failure events, regardless of eGFR. Any (versus no) moderate or vigorous physical activity significantly associated with decreased risk of ischemic stroke events only among those with eGFR ≥60. Moderate to no daily alcohol intake (versus excessive) was significantly associated with an increased risk of major coronary events, regardless of eGFR. For heart failure events, a BMI of 18.5 to 30 associated with decreased risk, regardless of eGFR. Across all eGFR categories, the magnitude of risk reduction for death and all cardiovascular outcomes increased with greater numbers of recommended lifestyle behaviors. CONCLUSIONS: Recommended lifestyle behaviors are associated with lower risk of death and cardiovascular disease events among individuals with or without reduced kidney function, supporting lifestyle behaviors as potentially modifiable risk factors for people with kidney disease.