Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification.

BACKGROUND AND AIMS: Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed. METHODS: In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score. RESULTS: Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787). CONCLUSIONS: Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.

Sodium-glucose cotransporter 2 inhibitors: are they ready for prime time in the management of lupus nephritis?

PURPOSE OF REVIEW: Lupus nephritis is a common complication of systemic lupus erythematosus and is associated with significant morbidity and mortality. The utility of sodium-glucose cotransporter 2 (SGLT2) inhibitors in the management of lupus nephritis is currently uncertain. Here, we summarize the rationale for their use among patient with lupus nephritis. RECENT FINDINGS: SGLT2 inhibitors were initially developed as antihyperglycemic agents. They have since been shown to have additional, profound effects to slow the progression of chronic kidney disease and lessen the long-term risks of cardiovascular disease in large clinic trials of patients with chronic kidney disease, with and without diabetes, as well as in patients with and without proteinuria. Patients with recent exposure to immunosuppression were excluded from these trials due to concern for risk of infection. In the few, small trials of patients with lupus nephritis, SGLT2 inhibitors were found to be well tolerated. They have been shown to reduce proteinuria and to have modest beneficial effects on blood pressure and BMI among patients with lupus nephritis. They have not been shown to influence disease activity. SUMMARY: SGLT2 inhibitors may have a role in mitigating the chronic renal and cardiovascular effects of lupus nephritis. They should be introduced after kidney function has been stabilized with appropriate immunosuppression, in conjunction with angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. They currently have no role in active disease.

Risk for Chronic Kidney Disease Progression After Acute Kidney Injury: Findings From the Chronic Renal Insufficiency Cohort Study.

BACKGROUND: Prior studies associating acute kidney injury (AKI) with more rapid subsequent loss of kidney function had methodological limitations, including inadequate control for differences between patients who had AKI and those who did not. OBJECTIVE: To determine whether AKI is independently associated with subsequent kidney function trajectory among patients with chronic kidney disease (CKD). DESIGN: Multicenter prospective cohort study. SETTING: United States. PARTICIPANTS: Patients with CKD (n = 3150). MEASUREMENTS: Hospitalized AKI was defined by a 50% or greater increase in inpatient serum creatinine (SCr) level from nadir to peak. Kidney function trajectory was assessed using estimated glomerular filtration rate (eGFR) based on SCr level (eGFRcr) or cystatin C level (eGFRcys) measured at annual study visits. RESULTS: During a median follow-up of 3.9 years, 433 participants had at least 1 AKI episode. Most episodes (92%) had stage 1 or 2 severity. There were decreases in eGFRcr (-2.30 [95% CI, -3.70 to -0.86] mL/min/1.73 m2) and eGFRcys (-3.61 [CI, -6.39 to -0.82] mL/min/1.73 m2) after AKI. However, in fully adjusted models, the decreases were attenuated to -0.38 (CI, -1.35 to 0.59) mL/min/1.73 m2 for eGFRcr and -0.15 (CI, -2.16 to 1.86) mL/min/1.73 m2 for eGFRcys, and the CI bounds included the possibility of no effect. Estimates of changes in eGFR slope after AKI determined by either SCr level (0.04 [CI, -0.30 to 0.38] mL/min/1.73 m2 per year) or cystatin C level (-0.56 [CI, -1.28 to 0.17] mL/min/1.73 m2 per year) also had CI bounds that included the possibility of no effect. LIMITATIONS: Few cases of severe AKI, no adjudication of AKI cause, and lack of information about nephrotoxic exposures after hospital discharge. CONCLUSION: After pre-AKI eGFR, proteinuria, and other covariables were accounted for, the association between mild to moderate AKI and worsening subsequent kidney function in patients with CKD was small. PRIMARY FUNDING SOURCE: National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health.

Low concentrations of medium-sized HDL particles predict incident CVD in chronic kidney disease patients.

Patients with chronic kidney disease (CKD) are at high risk for CVD. However, traditional CVD risk factors cannot completely explain the increased risk. Altered HDL proteome is linked with incident CVD in CKD patients, but it is unclear whether other HDL metrics are associated with incident CVD in this population. In the current study, we analyzed samples from two independent prospective case-control cohorts of CKD patients, the Clinical Phenotyping and Resource Biobank Core (CPROBE) and the Chronic Renal Insufficiency Cohort (CRIC). We measured HDL particle sizes and concentrations (HDL-P) by calibrated ion mobility analysis and HDL cholesterol efflux capacity (CEC) by cAMP-stimulated J774 macrophages in 92 subjects from the CPROBE cohort (46 CVD and 46 controls) and in 91 subjects from the CRIC cohort (34 CVD and 57 controls). We tested associations of HDL metrics with incident CVD using logistic regression analysis. No significant associations were found for HDL-C or HDL-CEC in either cohort. Total HDL-P was only negatively associated with incident CVD in the CRIC cohort in unadjusted analysis. Among the six sized HDL subspecies, only medium-sized HDL-P was significantly and negatively associated with incident CVD in both cohorts after adjusting for clinical confounders and lipid risk factors with odds ratios (per 1-SD) of 0.45 (0.22-0.93, P = 0.032) and 0.42 (0.20-0.87, P = 0.019) for CPROBE and CRIC cohorts, respectively. Our observations indicate that medium-sized HDL-P-but not other-sized HDL-P or total HDL-P, HDL-C, or HDL-CEC-may be a prognostic cardiovascular risk marker in CKD.

Excess risk of cardiovascular events in patients in the United States vs. Japan with chronic kidney disease is mediated mainly by left ventricular structure and function.

While patients receiving dialysis therapy in the United States are more likely to develop cardiovascular disease (CVD) than those in Japan, direct comparisons of patients with predialysis chronic kidney disease (CKD) are rare. To study this, we compared various outcomes in patients with predialysis CKD using data from the Chronic Renal Insufficiency Cohort (CRIC) and CKD Japan Cohort (CKD-JAC) studies and determined mediators of any differences. Candidate mediators included left ventricular (LV) indices assessed by echocardiography. Among 3125 CRIC and 1097 CKD-JAC participants, the mean LV mass index (LVMI) and ejection fraction (EF) were 55.7 and 46.6 g/m2 and 54% and 65%, respectively (both significant). The difference in body mass index (32 and 24 kg/m2, respectively) largely accounted for the differences in LVMI and C-reactive protein levels across cohorts. Low EF and high LVMI were significantly associated with subsequent CVD in both cohorts. During a median follow-up of five years, CRIC participants were at higher risk for CVD (adjusted hazard ratio [95% confidence interval]: 3.66 [2.74-4.89]) and death (4.69 [3.05-7.19]). A three-fold higher C-reactive protein concentration and higher phosphate levels in the United States cohort were moderately strong mediators of the differences in CVD. However, echocardiographic parameters were stronger mediators than these laboratory measures. LVMI, EF and their combination mediated the observed difference in CVD (27%, 50%, and 57%, respectively) and congestive heart failure (33%, 62%, and 70%, respectively). Thus, higher LV mass and lower EF, even in the normal range, were found to be predictive of CVD in CKD.

Ultraprocessed Foods and Kidney Disease Progression, Mortality, and Cardiovascular Disease Risk in the CRIC Study.

RATIONALE & OBJECTIVE: Ultraprocessed foods are widely consumed in the United States and are associated with cardiovascular disease (CVD), mortality, and kidney function decline in the general population. We investigated associations between ultraprocessed food intake and chronic kidney disease (CKD) progression, all-cause mortality, and incident CVD in adults with chronic kidney disease (CKD). STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Chronic Renal Insufficiency Cohort Study participants who completed baseline dietary questionnaires. EXPOSURE: Ultraprocessed food intake (in servings per day) classified according to the NOVA system. OUTCOMES: CKD progression (≥50% decrease in estimated glomerular filtration rate [eGFR] or initiation of kidney replacement therapy), all-cause mortality, and incident CVD (myocardial infarction, congestive heart failure, or stroke). ANALYTICAL APPROACH: Cox proportional hazards models adjusted for demographic, lifestyle, and health covariates. RESULTS: There were 1,047 CKD progression events observed during a median follow-up of 7 years. Greater ultraprocessed food intake was associated with higher risk of CKD progression (tertile 3 vs tertile 1, HR, 1.22; 95% CI, 1.04-1.42; P=0.01 for trend). The association differed by baseline kidney function, such that greater intake was associated with higher risk among people with CKD stages 1/2 (eGFR≥60mL/min/1.73m2; tertile 3 vs tertile 1, HR, 2.61; 95% CI, 1.32-5.18) but not stages 3a-5 (eGFR<60mL/min/1.73m2; P=0.003 for interaction). There were 1,104 deaths observed during a median follow-up of 14 years. Greater ultraprocessed food intake was associated with higher risk of mortality (tertile 3 vs tertile 1, HR, 1.21; 95% CI, 1.04-1.40; P=0.004 for trend). LIMITATIONS: Self-reported diet. CONCLUSIONS: Greater ultraprocessed food intake may be associated with CKD progression in earlier stages of CKD and is associated with higher risk of all-cause mortality in adults with CKD. PLAIN LANGUAGE SUMMARY: Ultraprocessed foods are industrial formulations produced using ingredients and processes that are not commonly used in culinary preparations and contain few, if any, intact unprocessed foods. Ultraprocessed foods are widely consumed in the United States, and high intakes of such foods have been linked to cardiovascular disease, kidney disease, and mortality in the general population. In this study, we found that greater intake of ultraprocessed foods was associated with higher risk of kidney disease progression and mortality in adults with chronic kidney disease. Our findings suggest that patients with kidney disease may benefit from greater consumption of fresh, whole, and homemade or hand-prepared foods and fewer highly processed foods.

Acute Kidney Injury Associates with Long-Term Increases in Plasma TNFR1, TNFR2, and KIM-1: Findings from the CRIC Study.

BACKGROUND: Some markers of inflammation-TNF receptors 1 and 2 (TNFR1 and TNFR2)-are independently associated with progressive CKD, as is a marker of proximal tubule injury, kidney injury molecule 1 (KIM-1). However, whether an episode of hospitalized AKI may cause long-term changes in these biomarkers is unknown. METHODS: Among adult participants in the Chronic Renal Insufficiency Cohort (CRIC) study, we identified 198 episodes of hospitalized AKI (defined as peak/nadir inpatient serum creatinine values ≥1.5). For each AKI hospitalization, we found the best matched non-AKI hospitalization (unique patients), using prehospitalization characteristics, including eGFR and urine protein/creatinine ratio. We measured TNFR1, TNFR2, and KIM-1 in banked plasma samples collected at annual CRIC study visits before and after the hospitalization (a median of 7 months before and 5 months after hospitalization). RESULTS: In the AKI and non-AKI groups, we found similar prehospitalization median levels of TNFR1 (1373 pg/ml versus 1371 pg/ml, for AKI and non-AKI, respectively), TNFR2 (47,141 pg/ml versus 46,135 pg/ml, respectively), and KIM-1 (857 pg/ml versus 719 pg/ml, respectively). Compared with matched study participants who did not experience AKI, study participants who did experience AKI had greater increases in TNFR1 (23% versus 10%, P<0.01), TNFR2 (10% versus 3%, P<0.01), and KIM-1 (13% versus -2%, P<0.01). CONCLUSIONS: Among patients with CKD, AKI during hospitalization was associated with increases in plasma TNFR1, TNFR2, and KIM-1 several months after their hospitalization. These results highlight a potential mechanism by which AKI may contribute to more rapid loss of kidney function months to years after the acute insult.

Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study.

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

High-Throughput Metabolomics and Diabetic Kidney Disease Progression: Evidence from the Chronic Renal Insufficiency (CRIC) Study.

INTRODUCTION: Metabolomics could offer novel prognostic biomarkers and elucidate mechanisms of diabetic kidney disease (DKD) progression. Via metabolomic analysis of urine samples from 995 CRIC participants with diabetes and state-of-the-art statistical modeling, we aimed to identify metabolites prognostic to DKD progression. METHODS: Urine samples (N = 995) were assayed for relative metabolite abundance by untargeted flow-injection mass spectrometry, and stringent statistical criteria were used to eliminate noisy compounds, resulting in 698 annotated metabolite ions. Utilizing the 698 metabolites' ion abundance along with clinical data (demographics, blood pressure, HbA1c, eGFR, and albuminuria), we developed univariate and multivariate models for the eGFR slope using penalized (lasso) and random forest models. Final models were tested on time-to-ESKD (end-stage kidney disease) via cross-validated C-statistics. We also conducted pathway enrichment analysis and a targeted analysis of a subset of metabolites. RESULTS: Six eGFR slope models selected 9-30 variables. In the adjusted ESKD model with highest C-statistic, valine (or betaine) and 3-(4-methyl-3-pentenyl)thiophene were associated (p < 0.05) with 44% and 65% higher hazard of ESKD per doubling of metabolite abundance, respectively. Also, 13 (of 15) prognostic amino acids, including valine and betaine, were confirmed in the targeted analysis. Enrichment analysis revealed pathways implicated in kidney and cardiometabolic disease. CONCLUSIONS: Using the diverse CRIC sample, a high-throughput untargeted assay, followed by targeted analysis, and rigorous statistical analysis to reduce false discovery, we identified several novel metabolites implicated in DKD progression. If replicated in independent cohorts, our findings could inform risk stratification and treatment strategies for patients with DKD.

Absence of long-term changes in urine biomarkers after AKI: findings from the CRIC study.

BACKGROUND: Mechanisms by which AKI leads to CKD progression remain unclear. Several urine biomarkers have been identified as independent predictors of progressive CKD. It is unknown whether AKI may result in long-term changes in these urine biomarkers, which may mediate the effect of AKI on CKD progression. METHODS: We selected 198 episodes of hospitalized AKI (defined as peak/nadir inpatient serum creatinine values ≥ 1.5) among adult participants in the Chronic Renal Insufficiency Cohort (CRIC) Study. We matched the best non-AKI hospitalization (unique patients) for each AKI hospitalization using pre-hospitalization characteristics including eGFR and urine protein/creatinine ratio. Biomarkers were measured in banked urine samples collected at annual CRIC study visits. RESULTS: Urine biomarker measurements occurred a median of 7 months before and 5 months after hospitalization. There were no significant differences in the change in urine biomarker-to-creatinine ratio between the AKI and non-AKI groups: KIM-1/Cr + 9% vs + 7%, MCP-1/Cr + 4% vs + 1%, YKL-40/Cr + 7% vs -20%, EGF/Cr -11% vs -8%, UMOD/Cr -2% vs -7% and albumin/Cr + 17% vs + 13% (all p > 0.05). CONCLUSION: In this cohort of adults with CKD, AKI did not associate with long-term changes in urine biomarkers.

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.

Adiposity, Physical Function, and Their Associations With Insulin Resistance, Inflammation, and Adipokines in CKD.

RATIONALE & OBJECTIVES: Adiposity and physical fitness levels are major drivers of cardiometabolic risk, but these relationships have not been well-characterized in chronic kidney disease (CKD). We examined the associations of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intrahepatic fat, and physical function with inflammation, insulin resistance, and adipokine levels in patients with CKD. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Participants with stages 3-5 CKD not receiving maintenance dialysis, followed up at one of 8 clinical sites in the Chronic Renal Insufficiency Cohort (CRIC) Study, and who underwent magnetic resonance imaging of the abdomen at an annual CRIC Study visit (n = 419). PREDICTORS: VAT volume, SAT volume, intrahepatic fat, body mass index, waist circumference, and time taken to complete the 400-m walk test (physical function). OUTCOMES: Markers of inflammation (interleukin 1ß [IL-1ß], IL-6, tumor necrosis factor receptor 1 [TNFR1], and TNFR2), insulin resistance (homeostasis model assessment of insulin resistance), and adipokine levels (adiponectin, total and high molecular weight, resistin, and leptin). ANALYTICAL APPROACH: Multivariable linear regression of VAT and SAT volume, intrahepatic fat, and physical function with individual markers (log-transformed values), adjusting for relevant covariates. RESULTS: Mean age of the study population was 64.3 years; 41% were women, and mean estimated glomerular filtration rate was 53.2±14.6 (SD) mL/min/1.73m2. More than 85% were overweight or obese, and 40% had diabetes. Higher VAT volume, SAT volume, and liver proton density fat fraction were associated with lower levels of total and high-molecular-weight adiponectin, higher levels of leptin and insulin resistance, and lower high-density lipoprotein cholesterol and higher serum triglyceride levels. A slower 400-m walk time was associated only with higher levels of leptin, total adiponectin, plasma IL-6, and TNFR1 and did not modify the associations between fat measures and cardiometabolic risk factors. LIMITATIONS: Lack of longitudinal data and dietary details. CONCLUSIONS: Various measures of adiposity are associated with cardiometabolic risk factors. Physical function was also associated with the cardiometabolic risk factors studied and does not modify associations between fat measures and cardiometabolic risk factors. Longitudinal studies of the relationship between body fat and aerobic fitness with cardiovascular and kidney disease progression are warranted.

Fibroblast Growth Factor 23 and Risk of Hospitalization with Infection in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: Risk of infectious disease is increased among individuals with CKD. Fibroblast growth factor 23 (FGF23) is often elevated in CKD, and may impair immune function directly or indirectly through proinflammatory and vitamin D-suppressing pathways. Whether FGF23 is associated with risk of infection has not been evaluated in a CKD population. METHODS: In 3655 participants of the Chronic Renal Insufficiency Cohort study, we evaluated the association of baseline plasma levels of C-terminal FGF23 with time to first hospitalization with major infection, defined by hospital discharge with a diagnosis code for urinary tract infection, pneumonia, cellulitis/osteomyelitis, or bacteremia/septicemia. Multivariable Cox models were used to estimate hazard ratios (HRs) and adjust for confounding. RESULTS: During a median follow-up of 6.5 years, 1051 individuals (29%) were hospitalized with major infection. Multivariable Cox analysis indicated a graded increase in the risk of infection with higher levels of FGF23 (HR, 1.51; 95% CI, 1.23 to 1.85 with the highest quartile [≥235.9 RU/ml] versus lowest quartile [<95.3 RU/ml]; HR, 1.26; 95% CI, 1.18 to 1.35 per SD increment in log FGF23). The association was consistent across infection subtypes and demographic and clinical subgroups, and remained significant after additional adjustment for biomarkers of inflammation (IL-6, TNF-α, high-sensitivity C-reactive protein, fibrinogen, and albumin), and bone mineral metabolism (25-hydroxyvitamin D, phosphorus, calcium, and parathyroid hormone). The association was consistent across infection subtypes of urinary tract infection (482 cases), cellulitis/osteomyelitis (422 cases), pneumonia (399 cases), and bacteremia/septicemia (280 cases). CONCLUSIONS: Among individuals with CKD, higher FGF23 levels were independently and monotonically associated with an increased risk of hospitalization with infection.

Inflammatory Markers and Incidence of Hospitalization With Infection in Chronic Kidney Disease.

Persons with chronic kidney disease (CKD) are at high risk of infection. While low-grade inflammation could impair immune response, it is unknown whether inflammatory markers are associated with infection risk in this clinical population. Using 2003-2013 data from the Chronic Renal Insufficiency Cohort Study (3,597 participants with CKD), we assessed the association of baseline plasma levels of 4 inflammatory markers (interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), interleukin-1 receptor antagonist (IL-1RA), and transforming growth factor-ß (TGF-ß)) with incident hospitalization with major infection (pneumonia, urinary tract infection, cellulitis and osteomyelitis, and bacteremia and sepsis). During follow-up (median 7.5 years), 36% (n = 1,290) had incident hospitalization with major infection. In multivariable Cox analyses with each inflammatory marker modeled as a restricted cubic spline, higher levels of IL-6 and TNF-α were monotonically associated with increased risk of hospitalization with major infection (for 95th vs. 5th percentile, hazard ratio = 2.11 (95% confidence interval: 1.68, 2.66) for IL-6 and 1.88 (95% confidence interval: 1.51, 2.33) for TNF-α), while corresponding associations for IL-1RA or TGF-ß were nonsignificant. Thus, higher plasma levels of IL-6 and TNF-α, but not IL-1RA or TGF-ß, were significantly associated with increased risk of hospitalization with major infection. Future studies should investigate whether inflammatory pathways that involve IL-6 and TNF-α increase susceptibility to infection among individuals with CKD.

Metabolomic Markers of Kidney Function Decline in Patients With Diabetes: Evidence From the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: Biomarkers that provide reliable evidence of future diabetic kidney disease (DKD) are needed to improve disease management. In a cross-sectional study, we previously identified 13 urine metabolites that had levels reduced in DKD compared with healthy controls. We evaluated associations of these 13 metabolites with future DKD progression. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: 1,001 Chronic Renal Insufficiency Cohort (CRIC) participants with diabetes with estimated glomerular filtration rates (eGFRs) between 20 and 70mL/min/1.73m2 were followed up prospectively for a median of 8 (range, 2-10) years. PREDICTORS: 13 urine metabolites, age, race, sex, smoked more than 100 cigarettes in lifetime, body mass index, hemoglobin A1c level, blood pressure, urinary albumin, and eGFR. OUTCOMES: Annual eGFR slope and time to incident kidney failure with replacement therapy (KFRT; ie, initiation of dialysis or receipt of transplant). ANALYTICAL APPROACH: Several clinical metabolite models were developed for eGFR slope as the outcome using stepwise selection and penalized regression, and further tested on the time-to-KFRT outcome. A best cross-validated (final) prognostic model was selected based on high prediction accuracy for eGFR slope and high concordance statistic for incident KFRT. RESULTS: During follow-up, mean eGFR slope was-1.83±1.92 (SD) mL/min/1.73m2 per year; 359 (36%) participants experienced KFRT. Median time to KFRT was 7.45 years from the time of entry to the CRIC Study. In our final model, after adjusting for clinical variables, levels of metabolites 3-hydroxyisobutyrate (3-HIBA) and 3-methylcrotonyglycine had a significant negative association with eGFR slope, whereas citric and aconitic acid were positively associated. Further, 3-HIBA and aconitic acid levels were associated with higher and lower risk for KFRT, respectively (HRs of 2.34 [95% CI, 1.51-3.62] and 0.70 [95% CI, 0.51-0.95]). LIMITATIONS: Subgroups for whom metabolite signatures may not be optimal, nontargeted metabolomics by flow-injection analysis, and 2-stage modeling approaches. CONCLUSIONS: Urine metabolites may offer insights into DKD progression. If replicated in future studies, aconitic acid and 3-HIBA could identify individuals with diabetes at high risk for GFR decline, potentially leading to improved clinical care and targeted therapies.

Prognostic score matching methods for estimating the average effect of a non-reversible binary time-dependent treatment on the survival function.

In evaluating the benefit of a treatment on survival, it is often of interest to compare post-treatment survival with the survival function that would have been observed in the absence of treatment. In many practical settings, treatment is time-dependent in the sense that subjects typically begin follow-up untreated, with some going on to receive treatment at some later time point. In observational studies, treatment is not assigned at random and, therefore, may depend on various patient characteristics. We have developed semi-parametric matching methods to estimate the average treatment effect on the treated (ATT) with respect to survival probability and restricted mean survival time. Matching is based on a prognostic score which reflects each patient's death hazard in the absence of treatment. Specifically, each treated patient is matched with multiple as-yet-untreated patients with similar prognostic scores. The matched sets do not need to be of equal size, since each matched control is weighted in order to preserve risk score balancing across treated and untreated groups. After matching, we estimate the ATT non-parametrically by contrasting pre- and post-treatment weighted Nelson-Aalen survival curves. A closed-form variance is proposed and shown to work well in simulation studies. The proposed methods are applied to national organ transplant registry data.

Predictors of Net Acid Excretion in the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: Higher urine net acid excretion (NAE) is associated with slower chronic kidney disease progression, particularly in patients with diabetes mellitus. To better understand potential mechanisms and assess modifiable components, we explored independent predictors of NAE in the CRIC (Chronic Renal Insufficiency Cohort) Study. STUDY DESIGN: Cross-sectional. SETTING & PARTICIPANTS: A randomly selected subcohort of adults with chronic kidney disease enrolled in the CRIC Study with NAE measurements. PREDICTORS: A comprehensive set of variables across prespecified domains including demographics, comorbid conditions, medications, laboratory values, diet, physical activity, and body composition. OUTCOME: 24-hour urine NAE. ANALYTICAL APPROACH: NAE was defined as the sum of urine ammonium and calculated titratable acidity in a subset of CRIC participants. 22 individuals were excluded for urine pH < 4 (n = 1) or ≥7.4 (n = 19) or extreme outliers of NAE values (n = 2). From an analytic sample of 978, we identified the association of individual variables with NAE in the selected domains using linear regression. We estimated the percent variance explained by each domain using the adjusted R2 from a domain-specific model. RESULTS: Mean NAE was 33.2 ± 17.4 (SD) mEq/d. Multiple variables were associated with NAE in models adjusted for age, sex, estimated glomerular filtration rate (eGFR), race/ethnicity, and body surface area, including insulin resistance, dietary potential renal acid load, and a variety of metabolically active medications (eg, metformin, allopurinol, and nonstatin lipid agents). Body size, as indicated by body surface area, body mass index, or fat-free mass; race/ethnicity; and eGFR also were independently associated with NAE. By domains, more variance was explained by demographics, body composition, and laboratory values, which included eGFR and serum bicarbonate level. LIMITATIONS: Cross-sectional; use of stored biological samples. CONCLUSIONS: NAE relates to several clinical domains including body composition, kidney function, and diet, but also to metabolic factors such as insulin resistance and the use of metabolically active medications.

Serum Calcification Propensity and Coronary Artery Calcification Among Patients With CKD: The CRIC (Chronic Renal Insufficiency Cohort) Study.

RATIONALE & OBJECTIVE: Coronary artery calcification (CAC) is prevalent among patients with chronic kidney disease (CKD) and increases risks for cardiovascular disease events and mortality. We hypothesized that a novel serum measure of calcification propensity is associated with CAC among patients with CKD stages 2 to 4. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Participants from the Chronic Renal Insufficiency Cohort (CRIC) Study with baseline (n=1,274) and follow-up (n=780) CAC measurements. PREDICTORS: Calcification propensity, quantified as transformation time (T50) from primary to secondary calciprotein particles, with lower T50 corresponding to higher calcification propensity. Covariates included age, sex, race/ethnicity, clinical site, estimated glomerular filtration rate, proteinuria, diabetes, systolic blood pressure, number of antihypertensive medications, current smoking, history of cardiovascular disease, total cholesterol level, and use of statin medications. OUTCOMES: CAC prevalence, severity, incidence, and progression. ANALYTICAL APPROACH: Multivariable-adjusted generalized linear models. RESULTS: At baseline, 824 (65%) participants had prevalent CAC. After multivariable adjustment, T50 was not associated with CAC prevalence but was significantly associated with greater CAC severity among participants with prevalent CAC: 1-SD lower T50 was associated with 21% (95% CI, 6%-38%) greater CAC severity. Among 780 participants followed up an average of 3 years later, 65 (20%) without baseline CAC developed incident CAC, while 89 (19%) with baseline CAC had progression, defined as annual increase≥100 Agatston units. After multivariable adjustment, T50 was not associated with incident CAC but was significantly associated with CAC progression: 1-SD lower T50 was associated with 28% (95% CI, 7%-53%) higher risk for CAC progression. LIMITATIONS: Potential selection bias in follow-up analyses; inability to distinguish intimal from medial calcification. CONCLUSIONS: Among patients with CKD stages 2 to 4, higher serum calcification propensity is associated with more severe CAC and CAC progression.

Continuous quality improvement in nephrology: a systematic review.

BACKGROUND: Continuous quality improvement (CQI) has been successfully applied in business and engineering for over 60 years. While using CQI techniques within nephrology has received increased attention, little is known about where, and with what measure of success, CQI can be attributed to improving outcomes within nephrology care. This is particularly important as payors' focus on value-based healthcare and reimbursement is tied to achieving quality improvement thresholds. We conducted a systematic review of CQI applications in nephrology. METHODS: Studies were identified from PubMed, MEDLINE, Scopus, Web of Science, CINAHL, Google Scholar, ProQuest Dissertation Abstracts and sources of grey literature (i.e., available in print/electronic format but not controlled by commercial publishers) between January 1, 2004 and October 13, 2014. We developed a systematic evaluation protocol and pre-defined criteria for review. All citations were reviewed by two reviewers with disagreements resolved by consensus. RESULTS: We initially identified 468 publications; 40 were excluded as duplicates or not available/not in English. An additional 352 did not meet criteria for full review due to: 1. Not meeting criteria for inclusion = 196 (e.g., reviews, news articles, editorials) 2. Not nephrology-specific = 153, 3. Only available as abstracts = 3. Of 76 publications meeting criteria for full review, the majority [45 (61%)] focused on ESRD care. 74% explicitly stated use of specific CQI tools in their methods. The highest number of publications in a given year occurred in 2011 with 12 (16%) articles. 89% of studies were found in biomedical and allied health journals and most studies were performed in North America (52%). Only one was randomized and controlled although not blinded. CONCLUSIONS: Despite calls for healthcare reform and funding to inspire innovative research, we found few high quality studies either rigorously evaluating the use of CQI in nephrology or reporting best practices. More rigorous research is needed to assess the mechanisms and attributes by which CQI impacts outcomes before there is further promotion of its use for improvement and reimbursement purposes.

Quantitative lung ultrasound comet measurement: method and initial clinical results.

BACKGROUND/AIMS: Recently, ultrasound signals termed 'lung water comets' associated with pulmonary edema have been correlated with adverse clinical events in dialysis patients. These comets fluctuate substantially during the ultrasound exam highlighting the need for objective quantitative measurement methods. METHODS: We developed an image-processing algorithm for the detection and quantification of lung comets. Quantification measures included comet number (comet count) and the fraction of the ultrasound beams with comet findings (comet fraction). We used this algorithm in a pilot study in 20 stable dialysis outpatients to identify associations between ultrasound comets and clinical parameters including blood pressure (BP), percent blood volume reduction on dialysis (%BV), ejection fraction (EF), and ultrafiltration on dialysis (UF). RESULTS: Positive findings included associations with lung comet measurements with pre-dialysis Diastolic BP (r = 0.534, p = 0.015), subject age (r = -0.446, p = 0.049), and a combination of EF and end dialysis %BV reduction (r = -0.585, p = 0.028). Comet fraction and comet count were closely correlated due to the inherent relationship between these two metrics (r = 0.973, p < 0.001). Negative findings included ultrasound comets that did not change from beginning to end of dialysis (p = 0.756), and were not significantly correlated with single dialysis treatment UF (p = 0.522), subject body weight (p = 0.208), or BMI (p = 0.358). CONCLUSIONS: Ultrasound signal processing methods may help quantify lung ultrasound comets. Additional findings include algorithmic lung comet measurement that did not change significantly during single dialysis sessions in these stable outpatients, but were associated with cardiovascular and fluid status parameters.