作者
Sanmay Low, Anantharaman Vathsala, Tanusya Murali Murali, Long Pang, Graeme MacLaren, Wan-Ying Ng, Sabrina Haroon, Amartya Mukhopadhyay, Shir-Lynn Lim, Bee-Hong Tan, Titus Lau, Horng-Ruey Chua
发表日期
2019/12
期刊
BMC nephrology
卷号
20
页码范围
1-11
出版商
BioMed Central
简介
Background
Electronic health records (EHR) detect the onset of acute kidney injury (AKI) in hospitalized patients, and may identify those at highest risk of mortality and renal replacement therapy (RRT), for earlier targeted intervention.
Methods
Prospective observational study to derive prediction models for hospital mortality and RRT, in inpatients aged ≥18 years with AKI detected by EHR over 1 year in a tertiary institution, fulfilling modified KDIGO criterion based on serial serum creatinine (sCr) measures.
Results
We studied 3333 patients with AKI, of 77,873 unique patient admissions, giving an AKI incidence of 4%. KDIGO AKI stages at detection were 1(74%), 2(15%), 3(10%); corresponding peak AKI staging in hospital were 61, 20, 19%. 392 patients (12%) died, and 174 (5%) received RRT. Multivariate logistic …
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S Low, A Vathsala, TM Murali, L Pang, G MacLaren… - BMC nephrology, 2019