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Risk Factors for Short-term All-cause Mortality in Patients with End Stage Renal Disease: a Scoping Review

Overview
Journal BMC Nephrol
Publisher Biomed Central
Specialty Nephrology
Date 2024 Feb 27
PMID 38413903
Authors
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Abstract

Objectives: There is a lack of prognostic information to guide the prediction of short-term all-cause mortality in patients with end-stage renal disease (ESRD). The aim was to review the risk factors that influenced the risk of short-term all-cause mortality in patients with ESRD.

Methods: MEDLINE, Embase, PubMed, CINAHL, the Cochrane Library and Web of Science databases were searched for articles published between 2000 and 2020. Articles describing risk factors predicting short-term mortality (≤ 3 years) in patients with ESRD were included. Four reviewers independently performed title, abstract, full text screening and data extraction. Assessment of risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool checklist.

Results: 20,840 articles were identified and 113 papers were included for this review. Of the 113 papers, 6.2% included only peritoneal dialysis (PD) patients, 67.3% included only hemodialysis (HD) patients, 20.4% included both PD and HD patients, with the remaining papers featuring patients on conservative management or awaiting renal transplant. Risk factors were categorised into 13 domains: 1)demographics/ lifestyle, 2) comorbidities 3)intradialytic blood pressure, 4)biomarkers, 5)cardiovascular measurements, 6)frailty status, 7)medications, 8)treatment related indicators, 9)renal related parameters, 10)health status, 11)cause of ESRD, 12)access to healthcare care/ information and, 13)proxy measures for poor health. C-reactive protein(CRP), age, and functional status were observed to have higher percentage of instances of being significantly associated with all-cause mortality.

Conclusion: Commonly examined risk factors observed from this review may be used to build a general prognostic model for patients with ESRD, with specific treatment related risk factors added on to enhance the accuracy of the models.

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