Biomarkers During Recovery From AKI and Prediction of Long-term Reductions in Estimated GFR
| Autor: | Mary Jo Kurth, Aleli Akani, Rebecca Packington, Helen Sewell, Rebecca Bartle, Rosamonde E. Banks, Ciaran Richardson, Eibhlin McCole, Michelle Wilson, Nicholas M. Selby, Sue Shaw |
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| Rok vydání: | 2021 |
| Předmět: |
Adult
Male medicine.medical_specialty Population Renal function urologic and male genital diseases Logistic regression Lipocalin-2 Internal medicine medicine Humans Prospective Studies Cystatin C Renal Insufficiency Chronic education Prospective cohort study education.field_of_study biology business.industry Acute kidney injury Acute Kidney Injury medicine.disease female genital diseases and pregnancy complications Nephrology Creatinine Cohort biology.protein Disease Progression Female business Biomarkers Kidney disease Glomerular Filtration Rate |
| Zdroj: | American journal of kidney diseases : the official journal of the National Kidney Foundation. 79(5) |
| ISSN: | 1523-6838 |
| Popis: | Rationale & Objective : 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 estimating the risk of new or worsening chronic kidney disease (CKD) following AKI. Study Design Prospective cohort study. Setting & Participants Adults from a single clinical center who developed 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 pre-existing CKD. Predictors Panel of 11 plasma biomarkers measured 3-months after hospitalisation. Outcome Kidney disease progression, defined as a ≥25% decline in eGFR combined with a decline in CKD stage, assessed three years after the occurrence of AKI. Analytical approach 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 penalised Lasso logistic regression for variable selection used to produce multivariable models. Results A total of 500 patients were studied. Soluble tumour necrosis factor receptor 1 (sTNFR1), sTNFR2, cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), three-month eGFR and urine albumin:creatinine ratio (ACR) 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 (AUC 0.79, 95% CI 0.7-0.83). Optimising the cut-point to maximise 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%. Limitations Lack of external validation cohort. Analyses limited to patients surviving for 3 years after AKI. Mixed population of patients with and without baseline CKD. Conclusions A panel of plasma biomarkers measured 3-months after discharge from a hospitalization complicated by AKI provides 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. |
| Databáze: | OpenAIRE |
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