Prediction of Outcome in Acute Renal Failure
作者:
Howard L. Corwin,
Richard S. Teplick,
Martin J. Schreiber,
Leslie S.T. Fang,
Joseph V. Bonventre,
Cecil H. Coggins,
期刊:
American Journal of Nephrology
(Karger Available online 1987)
卷期:
Volume 7,
issue 1
页码: 8-12
ISSN:0250-8095
年代: 1987
DOI:10.1159/000167421
出版商: S. Karger AG
关键词: Acute renal failure;Logistic regression;Multivariate analysis
数据来源: Karger
摘要:
In an attempt to predict outcome in acute renal failure (ARF) we have utilized multiple logistic regression to analyze clinical data from 151 patients with ARF seen over a 15-month period. Recovery of renal function occurred in 60% of patients with a 58% survival. Our analysis demonstrated sepsis, respiratory failure, and oliguria to be the major predictors of nonrecovery of renal function. A logistic equation was generated for prediction of outcome and was validated in a second independent group of patients with ARF. Prediction of outcome could be achieved with a sensitivity of 75% and a specificity of 80%. Maximum sensitivity (100%) was associated with a 17% specificity, while maximum specificity (98%) yielded a sensitivity of 20%.
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