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dc.contributor.authorPackington, Rebecca
dc.contributor.authorShaw, Susan
dc.contributor.authorAkani, A
dc.contributor.authorSelby, Nicholas
dc.date.accessioned2021-12-09T11:24:42Z
dc.date.available2021-12-09T11:24:42Z
dc.date.issued2021
dc.identifier.citationAm J Kidney Dis. 2021 Oct 1:S0272-6386(21)00891-X. doi: 10.1053/j.ajkd.2021.08.017. Online ahead of print.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12904/15024
dc.description.abstractRATIONALE & 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.
dc.language.isoenen_US
dc.subjectAKIen_US
dc.subjectCKD Progressionen_US
dc.subjectBiomarkersen_US
dc.subjectCystatin Cen_US
dc.subjectSoluble Tumour Necrosis Factor Receptoren_US
dc.titleBiomarkers During Recovery From AKI and Prediction of Long-term Reductions in Estimated GFR.en_US
dc.typeArticleen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
rioxxterms.versionNAen_US
rioxxterms.versionofrecordDOI: 10.1053/j.ajkd.2021.08.017en_US
rioxxterms.typeJournal Article/Reviewen_US
refterms.panelUnspecifieden_US
refterms.dateFirstOnline2021-10
html.description.abstractRATIONALE & 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.en_US
rioxxterms.funder.project94a427429a5bcfef7dd04c33360d80cden_US


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