S-EPMC6812505 - 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. - OmicsDI

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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.

ABSTRACT: 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 1? [IL-1?], IL-1 receptor antagonist, IL-6, tumor necrosis factor ? [TNF-?], transforming growth factor ?, 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-? (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.

SUBMITTER: Amdur RL

PROVIDER: S-EPMC6812505 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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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.

Amdur Richard L RL Feldman Harold I HI Dominic Elizabeth A EA Anderson Amanda H AH Beddhu Srinivasan S Rahman Mahboob M Wolf Myles M Reilly Muredach M Ojo Akinlolu A Townsend Raymond R RR Go Alan S AS He Jiang J Xie Dawei D Thompson Sally S Budoff Matthew M Kasner Scott S Kimmel Paul L PL Kusek John W JW Raj Dominic S DS

American journal of kidney diseases : the official journal of the National Kidney Foundation 20181210 3

<h4>Rationale & objective</h4>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.<h4>Study design</h4>Observational cohort study.<h4>Setting & participants</h4>2,399 Chronic Renal Insufficiency C ...[more]

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Project description:BACKGROUND:People with advanced chronic kidney disease are at risk for the development of end-stage renal disease (ESRD), but also many other adverse outcomes, including cardiovascular disease (CVD) events and death. Determination of risk factors that explain the variability in prognosis and timing of these adverse outcomes can aid patient counseling and medical decision making. STUDY DESIGN:Prospective research cohort. SETTING & PARTICIPANTS:1,798 participants with estimated glomerular filtration rates (eGFRs)<30mL/min/1.73m2 in the CRIC Study were followed up for a median of 5.5 years. PREDICTORS:Age, race, sex, eGFR, proteinuria, diabetes mellitus, body mass index, ejection fraction, systolic blood pressure, history of CVD, and smoking history. OUTCOMES:ESRD, CVD (congestive heart failure, stroke, myocardial infarction, and peripheral artery disease), and death. RESULTS:Baseline age of the cohort was 60 years, 46% were women, and 46% were African American. Although 52.3% of participants progressed to ESRD during follow-up, the path by which this occurred was variable. For example, predicted 1-year probabilities for a hypothetical 60-year-old white woman with eGFR of 30mL/min/1.73m2, urine protein excretion of 1.8g/d, and no diabetes or CVD (risk characteristics similar to the average participant) were 3.3%, 4.1%, and 0.3%, for first developing CVD, ESRD, and death, respectively. For a 40-year-old African American man with similar characteristics but higher systolic blood pressure, the corresponding 1-year probabilities were 2.4%, 13.2%, and 0.1%. For all participants, the development of ESRD or CVD increased the risk for subsequent mortality, with no differences by patient race or body mass index. LIMITATIONS:The CRIC population was specifically recruited for kidney disease, and the vast majority had seen a nephrologist. CONCLUSIONS:The prognosis and timing of adverse outcomes in chronic kidney disease vary by patient characteristics. These results may help guide the development of personalized approaches for managing patients with advanced CKD.