Biomarkers During Recovery From AKI and Prediction of Long-term Reductions in Estimated GFR

医学 肾功能 期限(时间) 内科学 肌酐 重症监护医学 泌尿科 物理 量子力学
作者
Michelle Wilson,Rebecca Packington,Helen Sewell,Rebecca Leanne Bartle,Eibhlin McCole,Mary Jo Kurth,Ciarán Richardson,Sue Shaw,Aleli Akani,Rosamonde E. Banks,Nicholas M. Selby
出处
期刊:American Journal of Kidney Diseases [Elsevier BV]
卷期号:79 (5): 646-656.e1 被引量:22
标识
DOI:10.1053/j.ajkd.2021.08.017
摘要

The effects of acute kidney injury (AKI) on long-term kidney function, cardiovascular disease, and mortality are well documented. We aimed to identify biomarkers for the estimation of risk of new or worsening chronic kidney disease (CKD) following AKI.Prospective cohort study.Adults from a single clinical center who experienced AKI between May 2013 and May 2016 and survived until 3 years after the hospitalization during which AKI occurred. Participants included those with and without preexisting CKD.Panel of 11 plasma biomarkers measured 3 months after hospitalization.Kidney disease progression, defined as a≥25% decrease in estimated glomerular filtration rate (eGFR) combined with worsening CKD stage, assessed 3 years after the occurrence of AKI.Associations between biomarkers and kidney disease progression were evaluated in multivariable logistic regression models. Importance of predictor variables was assessed by constructing multiple decision trees, with penalized least absolute shrinkage and selection operator logistic regression for variable selection used to produce multivariable models.A total of 500 patients were studied. Soluble tumor necrosis factor receptor (sTNFR) 1, sTNFR2, cystatin C, neutrophil gelatinase-associated lipocalin, 3-month eGFR, and urinary albumin-creatinine ratio were independently associated with kidney disease progression and were more important than AKI severity or duration. A multivariable model containing sTNFR1, sTNFR2, cystatin C, and eGFR discriminated between those with and without kidney disease progression (area under the curve, 0.79 [95% CI, 0.70-0.83]). Optimizing the cutoff point to maximize utility as a "rule-out" test to identify those at low risk increased the sensitivity of the model to 95% and its negative predictive value to 92%.Lack of external validation cohort. Analyses limited to patients who survived for 3 years after AKI. Mixed population of patients with and without baseline CKD.A panel of plasma biomarkers measured 3 months after discharge from a hospitalization complicated by AKI provides a potential opportunity to identify patients who are at very low risk of incident or worsening CKD. Further study is required to determine its clinical utility through independent prospective validation.
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