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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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