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.).

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.

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.

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.

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.

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.

Subtyping CKD Patients by Consensus Clustering: The Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: CKD is a heterogeneous condition with multiple underlying causes, risk factors, and outcomes. Subtyping CKD with multidimensional patient data holds the key to precision medicine. Consensus clustering may reveal CKD subgroups with different risk profiles of adverse outcomes. METHODS: We used unsupervised consensus clustering on 72 baseline characteristics among 2696 participants in the prospective Chronic Renal Insufficiency Cohort (CRIC) study to identify novel CKD subgroups that best represent the data pattern. Calculation of the standardized difference of each parameter used the cutoff of ±0.3 to show subgroup features. CKD subgroup associations were examined with the clinical end points of kidney failure, the composite outcome of cardiovascular diseases, and death. RESULTS: The algorithm revealed three unique CKD subgroups that best represented patients' baseline characteristics. Patients with relatively favorable levels of bone density and cardiac and kidney function markers, with lower prevalence of diabetes and obesity, and who used fewer medications formed cluster 1 (n=1203). Patients with higher prevalence of diabetes and obesity and who used more medications formed cluster 2 (n=1098). Patients with less favorable levels of bone mineral density, poor cardiac and kidney function markers, and inflammation delineated cluster 3 (n=395). These three subgroups, when linked with future clinical end points, were associated with different risks of CKD progression, cardiovascular disease, and death. Furthermore, patient heterogeneity among predefined subgroups with similar baseline kidney function emerged. CONCLUSIONS: Consensus clustering synthesized the patterns of baseline clinical and laboratory measures and revealed distinct CKD subgroups, which were associated with markedly different risks of important clinical outcomes. Further examination of patient subgroups and associated biomarkers may provide next steps toward precision medicine.

Novel Risk Factors for Progression of Diabetic and Nondiabetic CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: Identification of novel risk factors for chronic kidney disease (CKD) progression may inform mechanistic investigations and improve identification of high-risk subgroups. The current study aimed to characterize CKD progression across levels of numerous risk factors and identify independent risk factors for CKD progression among those with and without diabetes. STUDY DESIGN: The Chronic Renal Insufficiency Cohort (CRIC) Study is a prospective cohort study of adults with CKD conducted at 7 US clinical centers. SETTING & PARTICIPANTS: Participants (N=3,379) had up to 12.3 years of follow-up; 47% had diabetes. PREDICTORS: 30 risk factors for CKD progression across sociodemographic, behavioral, clinical, and biochemical domains at baseline. OUTCOMES: Study outcomes were estimated glomerular filtration rate (eGFR) slope and the composite of halving of eGFR or initiation of kidney replacement therapy. ANALYTICAL APPROACH: Stepwise selection of independent risk factors was performed stratified by diabetes status using linear mixed-effects and Cox proportional hazards models. RESULTS: Among those without and with diabetes, respectively, mean eGFR slope was-1.4±3.3 and-2.7±4.7mL/min/1.73m2 per year. Among participants with diabetes, multivariable-adjusted hazard of the composite outcome was approximately 2-fold or greater with higher levels of the inflammatory chemokine CXCL12, the cardiac marker N-terminal pro-B-type natriuretic peptide (NT-proBNP), and the kidney injury marker urinary neutrophil gelatinase-associated lipocalin (NGAL). Among those without diabetes, low serum bicarbonate and higher high-sensitivity troponin T, NT-proBNP, and urinary NGAL levels were all significantly associated with a 1.5-fold or greater rate of the composite outcome. LIMITATIONS: The observational study design precludes causal inference. CONCLUSIONS: Strong associations for cardiac markers, plasma CXCL12, and urinary NGAL are comparable to that of systolic blood pressure≥140mm Hg, a well-established risk factor for CKD progression. This warrants further investigation into the potential mechanisms that these markers indicate and opportunities to use them to improve risk stratification.

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.

Slope of Kidney Function and Its Association with Longitudinal Mortality and Cardiovascular Disease among Individuals with CKD.

BACKGROUND: Slopes of eGFR have been associated with increased risks of death and cardiovascular events in a U-shaped fashion. Poor outcomes in individuals with rising eGFR are potentially attributable to sarcopenia, hemodilution, and other indicators of clinical deterioration. METHODS: To investigate the association between eGFR slopes and risks of death or cardiovascular events, accounting for multiple confounders, we studied 2738 individuals with moderate to severe CKD participating in the multicenter Chronic Renal Insufficiency Cohort (CRIC) Study. We used linear, mixed-effects models to estimate slopes with up to four annual eGFR assessments, and Cox proportional hazards models to investigate the association between slopes and the risks of death and cardiovascular events. RESULTS: Slopes of eGFR had a bell-shaped distribution (mean [SD], -1.5 [-2] ml/min per 1.73 m2 per year). Declines of eGFR that were steeper than the average decline associated with progressively increasing risks of death (hazard ratio [HR], 1.23; 95% confidence interval [95% CI], 1.09 to 1.39; for a slope 1 SD below the average) and cardiovascular events (HR, 1.19; 95% CI, 1.03 to 1.38). Rises of eGFR or declines lower than the average decline were not associated with the risk of death or cardiovascular events. CONCLUSIONS: In a cohort of individuals with moderate to severe CKD, we observed steep declines of eGFR were associated with progressively increasing risks of death and cardiovascular events; however, we found no increased risks associated with eGFR improvement. These findings support the potential value of eGFR slopes in clinical assessment of adults with CKD.

Hospitalizations among adults with chronic kidney disease in the United States: A cohort study.

BACKGROUND: Adults with chronic kidney disease (CKD) are hospitalized more frequently than those without CKD, but the magnitude of this excess morbidity and the factors associated with hospitalizations are not well known. METHODS AND FINDINGS: Data from 3,939 participants enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study between 2003 and 2008 at 7 clinical centers in the United States were used to estimate primary causes of hospitalizations, hospitalization rates, and baseline participant factors associated with all-cause, cardiovascular, and non-cardiovascular hospitalizations during a median follow up of 9.6 years. Multivariable-adjusted Poisson regression was used to identify factors associated with hospitalization rates, including demographics, blood pressure, estimated glomerular filtration rate (eGFR), and proteinuria. Hospitalization rates in CRIC were compared with rates in the Nationwide Inpatient Sample (NIS) from 2012. Of the 3,939 CRIC participants, 45.1% were female, and 41.9% identified as non-Hispanic black, with a mean age of 57.7 years, and the mean eGFR is 44.9 ml/min/1.73m2. CRIC participants had an unadjusted overall hospitalization rate of 35.0 per 100 person-years (PY) [95% CI: 34.3 to 35.6] and 11.1 per 100 PY [95% CI: 10.8 to 11.5] for cardiovascular-related causes. All-cause, non-cardiovascular, and cardiovascular hospitalizations were associated with older age (≥65 versus 45 to 64 years), more proteinuria (≥150 to <500 versus <150 mg/g), higher systolic blood pressure (≥140 versus 120 to <130 mmHg), diabetes (versus no diabetes), and lower eGFR (<60 versus ≥60 ml/min/1.73m2). Non-Hispanic black (versus non-Hispanic white) race/ethnicity was associated with higher risk for cardiovascular hospitalization [rate ratio (RR) 1.25, 95% CI: 1.16 to 1.35, p-value < 0.001], while risk among females was lower [RR 0.89, 95% CI: 0.83 to 0.96, p-value = 0.002]. Rates of cardiovascular hospitalizations were higher among those with ≥500 mg/g of proteinuria irrespective of eGFR. The most common causes of hospitalization were related to cardiovascular (31.8%), genitourinary (8.7%), digestive (8.3%), endocrine, nutritional or metabolic (8.3%), and respiratory (6.7%) causes. Hospitalization rates were higher in CRIC than the NIS, except for non-cardiovascular hospitalizations among individuals aged >65 years. Limitations of the study include possible misclassification by diagnostic codes, residual confounding, and potential bias from healthy volunteer effect due to its observational nature. CONCLUSIONS: In this study, we observed that adults with CKD had a higher hospitalization rate than the general population that is hospitalized, and even moderate reductions in kidney function were associated with elevated rates of hospitalization. Causes of hospitalization were predominantly related to cardiovascular disease, but other causes contributed, particularly, genitourinary, digestive, and endocrine, nutritional, and metabolic illnesses. High levels of proteinuria were observed to have the largest association with hospitalizations across a wide range of kidney function levels.

Serial Fibroblast Growth Factor 23 Measurements and Risk of Requirement for Kidney Replacement Therapy: The CRIC (Chronic Renal Insufficiency Cohort) Study.

RATIONALE & OBJECTIVE: Studies using a single measurement of fibroblast growth factor 23 (FGF-23) suggest that elevated FGF-23 levels are associated with increased risk for requirement for kidney replacement therapy (KRT) in patients with chronic kidney disease. However, the data do not account for changes in FGF-23 levels as kidney disease progresses. STUDY DESIGN: Case-cohort study. SETTING & PARTICIPANTS: To evaluate the association between serial FGF-23 levels and risk for requiring KRT, our primary analysis included 1,597 individuals in the Chronic Renal Insufficiency Cohort Study who had up to 5 annual measurements of carboxy-terminal FGF-23. There were 1,135 randomly selected individuals, of whom 266 initiated KRT, and 462 individuals who initiated KRT outside the random subcohort. EXPOSURE: Serial FGF-23 measurements and FGF-23 trajectory group membership. OUTCOMES: Incident KRT. ANALYTICAL APPROACH: To handle time-dependent confounding, our primary analysis of time-updated FGF-23 levels used time-varying inverse probability weighting in a discrete time failure model. To compare our results with prior data, we used baseline and time-updated FGF-23 values in weighted Cox regression models. To examine the association of FGF-23 trajectory subgroups with risk for incident KRT, we used weighted Cox models with FGF-23 trajectory groups derived from group-based trajectory modeling as the exposure. RESULTS: In our primary analysis, the HR for the KRT outcome per 1 SD increase in the mean of natural log-transformed (ln)FGF-23 in the past was 1.94 (95% CI, 1.51-2.49). In weighted Cox models using baseline and time-updated values, elevated FGF-23 level was associated with increased risk for incident KRT (HRs per 1 SD ln[FGF-23] of 1.18 [95% CI, 1.02-1.37] for baseline and 1.66 [95% CI, 1.49-1.86] for time-updated). Membership in the slowly and rapidly increasing FGF-23 trajectory groups was associated with ∼3- and ∼21-fold higher risk for incident KRT compared to membership in the stable FGF-23 trajectory group. LIMITATIONS: Residual confounding and lack of intact FGF-23 values. CONCLUSIONS: Increasing FGF-23 levels are independently associated with increased risk for incident KRT.

Pooled cohort equations heart failure risk score predicts cardiovascular disease and all-cause mortality in a nationally representative sample of US adults.

BACKGROUND: Heart failure (HF) represents an accumulated burden of systemic vascular damage and is the fastest growing form of cardiovascular disease (CVD). Due to increasing HF-attributable mortality rates, we sought to assess the association of the new 2019 Pooled Cohort equations to Prevent Heart Failure (PCP-HF) risk score with CVD and all-cause mortality. METHODS: We linked data for 6333 black and white men and women aged 40-79 years, whom underwent electrocardiographic examination from the Third National Health and Nutrition Exam Survey, to National Death Index record matches. Sex- and race-specific PCP-HF risk scores were calculated using data on age, smoking, body mass index, systolic blood pressure, total cholesterol, HDL-cholesterol, fasting blood glucose, QRS complex duration, and antihypertensive and/or glucose-lowering medications. Cox regression estimated hazard ratios for the association of the PCP-HF risk score with CVD and all-cause mortality. RESULTS: Individuals were on average 54.9 years old (51.7% women, 25.4% black) and the median 10-year HF risk was 1.6% (Q1 = 0.5, Q3 = 4.8). There were 3178 deaths, 1116 from CVD, over a median follow-up time of 22.3 years. Black women had a higher 10-year HF risk compared to white women (2.1% vs. 1.1%; p < 0.01), while no significant difference was observed in predicted HF risk between black men and white men (2.3% vs. 2.1%, p = 0.16). A two-fold higher PCP-HF risk score was associated with a significant 58% (HR = 1.58; 95% CI, 1.48-1.70; p < 0.0001) and 38% (HR = 1.38; 95% CI, 1.32-1.46; p < 0.0001) greater risk of CVD and all-cause mortality, respectively. CONCLUSION: The PCP-HF risk score predicts CVD and all-cause mortality, in addition to the 10-year risk of incident HF among white and black men and women. These results underline the expanded utility of the PCP-HF risk score and suggest that its implementation in the clinical and population health settings may improve primary CVD prevention in the United States.

Safety and cardiovascular efficacy of spironolactone in dialysis-dependent ESRD (SPin-D): a randomized, placebo-controlled, multiple dosage trial.

The safety and efficacy of spironolactone is uncertain in end-stage renal disease. We randomized 129 maintenance hemodialysis patients to placebo (n=51) or spironolactone 12.5 mg (n=27), 25 mg (n=26), or 50 mg (n=25) daily for 36 weeks in a double-blind, placebo-controlled, multiple dosage trial to assess safety, tolerability and feasibility and to explore cardiovascular efficacy. The primary safety endpoints were hyperkalemia (potassium > 6.5 mEq/L) and hypotension requiring emergency department visit or hospitalization. Diastolic function was assessed by Doppler echocardiography. 125 participants (97%) completed dose escalation, with no significant difference in permanent study drug discontinuation between the groups (27.5% in placebo versus 16.7% in the combined spironolactone groups and 28% in the 50 mg group). Hyperkalemia frequency was similar between spironolactone and placebo (0.49 versus 0.50 events per patient-year) but demonstrated a significant linear trend due primarily to an increased event rate at the 50 mg dose (0.89 events per patient-year). The primary hypotension outcome was infrequent and similar with spironolactone and placebo (0.11 versus 0 events per patient-year). Gynecomastia was rare and did not differ significantly between groups. Change in diastolic function was similar with spironolactone and placebo. Spironolactone appears safe in carefully monitored maintenance hemodialysis patients, but did not affect cardiovascular parameters in this small study. Hyperkalemia occurs more frequently as dosage increases to 50 mg daily.

Lipids, Apolipoproteins, and Risk of Atherosclerotic Cardiovascular Disease in Persons With CKD.

RATIONALE & OBJECTIVE: A large residual risk for atherosclerotic cardiovascular disease (ASCVD) remains in the setting of chronic kidney disease (CKD) despite treatment with statins. We sought to evaluate the associations of lipid and apolipoprotein levels with risk for ASCVD in individuals with CKD. STUDY DESIGN: Prospective cohort study. SETTINGS & PARTICIPANTS: Adults aged 21 to 74 years with non-dialysis-dependent CKD at baseline enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study in 7 clinical study centers in the United States. PREDICTOR: Baseline total cholesterol, non-high-density lipoprotein cholesterol (non-HDL-C), very low-density lipoprotein cholesterol (VLDL-C), triglycerides, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo-B), HDL-C, and apolipoprotein AI (Apo-AI) values stratified into tertiles. OUTCOME: A composite ASCVD event of myocardial infarction or ischemic stroke. ANALYTIC APPROACH: Multivariable Cox proportional hazards regression to estimate the risk for ASCVD for each tertile of lipoprotein predictor. RESULTS: Among 3,811 CRIC participants (mean age, 57.7 years; 41.8% white), there were 451 ASCVD events during a median follow-up of 7.9 years. There was increased ASCVD risk among participants with VLDL-C levels in the highest tertile (HR, 1.28; 95% CI, 1.01-1.64), Apo-B levels in the middle tertile (HR, 1.30; 95% CI, 1.03-1.64), HDL-C levels in the middle and lowest tertiles (HRs of 1.40 [95% CI, 1.08-1.83] and 1.77 [95% CI, 1.35-2.33], respectively), and Apo-AI levels in the middle and lowest tertiles (HRs of 1.77 [95% CI, 1.02-1.74] and 1.77 [95% CI, 1.36-2.32], respectively). LDL-C level was not significantly associated with the ASCVD outcome in this population (HR, 1.00 [95% CI, 0.77-1.30] for the highest tertile). LIMITATIONS: Associations based on observational data do not permit inferences about causal associations. CONCLUSIONS: Higher VLDL-C and Apo-B levels, as well as lower HDL-C and Apo-AI levels, are associated with increased risk for ASCVD. These findings support future investigations into pharmacologic targeting of lipoproteins beyond LDL-C, such as triglyceride-rich lipoproteins, to reduce residual risk for ASCVD among individuals with CKD.

Use of Measures of Inflammation and Kidney Function for Prediction of Atherosclerotic Vascular Disease Events and Death in Patients With CKD: Findings From the CRIC Study.

RATIONALE & OBJECTIVE: Traditional risk estimates for atherosclerotic vascular disease (ASVD) and death may not perform optimally in the setting of chronic kidney disease (CKD). We sought to determine whether the addition of measures of inflammation and kidney function to traditional estimation tools improves prediction of these events in a diverse cohort of patients with CKD. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: 2,399 Chronic Renal Insufficiency Cohort (CRIC) Study participants without a history of cardiovascular disease at study entry. PREDICTORS: Baseline plasma levels of biomarkers of inflammation (interleukin 1ß [IL-1ß], IL-1 receptor antagonist, IL-6, tumor necrosis factor α [TNF-α], transforming growth factor ß, high-sensitivity C-reactive protein, fibrinogen, and serum albumin), measures of kidney function (estimated glomerular filtration rate [eGFR] and albuminuria), and the Pooled Cohort Equation probability (PCEP) estimate. OUTCOMES: Composite of ASVD events (incident myocardial infarction, peripheral arterial disease, and stroke) and death. ANALYTICAL APPROACH: Cox proportional hazard models adjusted for PCEP estimates, albuminuria, and eGFR. RESULTS: During a median follow-up of 7.3 years, 86, 61, 48, and 323 participants experienced myocardial infarction, peripheral arterial disease, stroke, or death, respectively. The 1-decile greater levels of IL-6 (adjusted HR [aHR], 1.12; 95% CI, 1.08-1.16; P<0.001), TNF-α (aHR, 1.09; 95% CI, 1.05-1.13; P<0.001), fibrinogen (aHR, 1.07; 95% CI, 1.03-1.11; P<0.001), and serum albumin (aHR, 0.96; 95% CI, 0.93-0.99; P<0.002) were independently associated with the composite ASVD-death outcome. A composite inflammation score (CIS) incorporating these 4 biomarkers was associated with a graded increase in risk for the composite outcome. The incidence of ASVD-death increased across the quintiles of risk derived from PCEP, kidney function, and CIS. The addition of eGFR, albuminuria, and CIS to PCEP improved (P=0.003) the area under the receiver operating characteristic curve for the composite outcome from 0.68 (95% CI, 0.66-0.71) to 0.73 (95% CI, 0.71-0.76). LIMITATIONS: Data for cardiovascular death were not available. CONCLUSIONS: Biomarkers of inflammation and measures of kidney function are independently associated with incident ASVD events and death in patients with CKD. Traditional cardiovascular risk estimates could be improved by adding markers of inflammation and measures of kidney function.

Novel associations between blood metabolites and kidney function among Bogalusa Heart Study and Multi-Ethnic Study of Atherosclerosis participants.

INTRODUCTION: Chronic kidney disease (CKD) is a major public health challenge given its high global prevalence and associated risks of cardiovascular disease and progression to end stage renal disease. Although it is known that numerous metabolic changes occur in CKD patients, identifying novel metabolite associations with kidney function may enhance our understanding of the physiologic pathways relating to CKD. OBJECTIVES: The objective of this study was to elucidate novel metabolite associations with kidney function among participants of two community-based cohorts with carefully ascertained metabolomics, kidney function, and covariate data. METHODS: Untargeted ultrahigh-performance liquid chromatography-tandem mass spectrometry was used to detect and quantify blood metabolites. We used multivariate adjusted linear regression to examine associations between single metabolites and creatinine-based estimated glomerular filtration rate (eGFRcr) among 1243 Bogalusa Heart Study (BHS) participants (median eGFRcr: 94.4, 5th-95th percentile: 66.0-119.6 mL/min/1.73 m2). Replication, determined by statistical significance and consistent effect direction, was tested using gold standard measured glomerular filtration rate (mGFR) among 260 Multi-Ethnic Study of Atherosclerosis (MESA) participants (median mGFR: 72.0, 5th-95th percentile: 43.5-105.0 mL/min/1.73 m2). All analyses used Bonferroni-corrected alpha thresholds. RESULTS: Fifty-one novel metabolite associations with kidney function were identified, including 12 from previously unrelated sub-pathways: N6-carboxymethyllysine, gulonate, quinolinate, gamma-CEHC-glucuronide, retinol, methylmalonate, 3-hydroxy-3-methylglutarate, 3-aminoisobutyrate, N-methylpipecolate, hydroquinone sulfate, and glycine conjugates of C10H12O2 and C10H14O2(1). Significant metabolites were generally inversely associated with kidney function and smaller in mass-to-charge ratio than non-significant metabolites. CONCLUSION: The 51 novel metabolites identified may serve as early, clinically relevant, kidney function biomarkers.

Insulin resistance and chronic kidney disease progression, cardiovascular events, and death: findings from the chronic renal insufficiency cohort study.

BACKGROUND: Insulin resistance contributes to the metabolic syndrome, which is associated with the development of kidney disease. However, it is unclear if insulin resistance independently contributes to an increased risk of chronic kidney disease (CKD) progression or CKD complications. Additionally, predisposing factors responsible for insulin resistance in the absence of diabetes in CKD are not well described. This study aimed to describe factors associated with insulin resistance and characterize the relationship of insulin resistance to CKD progression, cardiovascular events and death among a cohort of non-diabetics with CKD. METHODS: Data was utilized from Chronic Renal Insufficiency Cohort Study participants without diabetes (N = 1883). Linear regression was used to assess associations with insulin resistance, defined using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). The relationship of HOMA-IR, fasting glucose, hemoglobin A1c (HbA1c), and C-peptide with CKD progression, cardiovascular events, and all-cause mortality was examined with Cox proportional hazards models. RESULTS: Novel positive associations with HOMA-IR included serum albumin, uric acid, and hemoglobin A1c. After adjustment, HOMA-IR was not associated with CKD progression, cardiovascular events, or all-cause mortality. There was a notable positive association of one standard deviation increase in HbA1c with the cardiovascular endpoint (HR 1.16, 95% CI: 1.00-1.34). CONCLUSION: We describe potential determinants of HOMA-IR among a cohort of non-diabetics with mild-moderate CKD. HOMA-IR was not associated with renal or cardiovascular events, or all-cause mortality, which adds to the growing literature describing an inconsistent relationship of insulin resistance with CKD-related outcomes.

Longitudinal FGF23 Trajectories and Mortality in Patients with CKD.

Elevated fibroblast growth factor 23 (FGF23) levels, measured at a single time, are strongly associated with increased risk of mortality in patients with CKD. There are minimal data on serial FGF23 measurements in CKD. In a prospective case-cohort study of the Chronic Renal Insufficiency Cohort, we measured FGF23 at two to five annual time points (mean 4.0±1.2) in a randomly selected subcohort of 1135 participants, of whom 203 died, and all remaining 390 participants who died through mid-2013. Higher FGF23 was independently associated with increased risk of death in multivariable-adjusted analyses of time-varying FGF23 (hazard ratio per 1-SD increase in ln-transformed FGF23, 1.84; 95% CI, 1.67 to 2.03). Median FGF23 was stable over 5 years of follow-up, but its gradually right-skewed distribution suggested a subpopulation with markedly elevated FGF23. Trajectory analysis revealed three distinct trajectories: stable FGF23 in the majority of participants (slope of lnFGF23 per year =0.03, 95% CI, 0.02 to 0.04, n=724) and smaller subpopulations with slowly (slope=0.14, 95% CI, 0.12 to 0.16, n=486) or rapidly (slope=0.46, 95% CI, 0.38 to 0.54, n=99) rising levels. Compared with stable FGF23, participants with slowly rising FGF23 trajectories were at 4.49-fold higher risk of death (95% CI, 3.17 to 6.35) and individuals with rapidly rising FGF23 trajectories were at 15.23-fold higher risk of death (95% CI, 8.24 to 28.14) in fully adjusted analyses. Trajectory analyses that used four or three annual FGF23 measurements yielded qualitatively similar results. In conclusion, FGF23 levels are stable over time in the majority of patients with CKD, but serial measurements identify subpopulations with rising levels and exceptionally high risk of death.

CKD Self-management: Phenotypes and Associations With Clinical Outcomes.

BACKGROUND: To slow chronic kidney disease (CKD) progression and its complications, patients need to engage in self-management behaviors. The objective of this study was to classify CKD self-management behaviors into phenotypes and assess the association of these phenotypes with clinical outcomes. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Adults with mild to moderate CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study. 3,939 participants in the CRIC Study recruited between 2003 and 2008 served as the derivation cohort and 1,560 participants recruited between 2013 and 2015 served as the validation cohort. PREDICTORS: CKD self-management behavior phenotypes. OUTCOMES: CKD progression, atherosclerotic events, heart failure events, death from any cause. MEASUREMENTS: Latent class analysis stratified by diabetes was used to identify CKD self-management phenotypes based on measures of body mass index, diet, physical activity, blood pressure, smoking status, and hemoglobin A1c concentration (if diabetic); Cox proportional hazards models. RESULTS: 3 identified phenotypes varied according to the extent of implementation of recommended CKD self-management behaviors: phenotype I characterized study participants with the most recommended behaviors; phenotype II, participants with a mixture of recommended and not recommended behaviors; and phenotype III, participants with minimal recommended behaviors. In multivariable-adjusted models for those with and without diabetes, phenotype III was strongly associated with CKD progression (HRs of 1.82 and 1.49), death (HRs of 1.95 and 4.14), and atherosclerotic events (HRs of 2.54 and 1.90; each P < 0.05). Phenotype II was associated with atherosclerotic events and death among those with and without diabetes. LIMITATIONS: No consensus definition of CKD self-management; limited to baseline behavior data. CONCLUSIONS: There are potentially 3 CKD self-management behavior phenotypes that distinguish risk for clinical outcomes. These phenotypes may inform the development of studies and guidelines regarding optimal self-management.