Literature DB >> 3578381

Prediction of outcome in acute renal failure.

H L Corwin, R S Teplick, M J Schreiber, L S Fang, J V Bonventre, C H Coggins.   

Abstract

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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Year:  1987        PMID: 3578381     DOI: 10.1159/000167421

Source DB:  PubMed          Journal:  Am J Nephrol        ISSN: 0250-8095            Impact factor:   3.754


  2 in total

1.  Outcome prediction of acute renal failure in medical intensive care.

Authors:  J H Schaefer; F Jochimsen; F Keller; K Wegscheider; A Distler
Journal:  Intensive Care Med       Date:  1991       Impact factor: 17.440

Review 2.  Prediction Models and Their External Validation Studies for Mortality of Patients with Acute Kidney Injury: A Systematic Review.

Authors:  Tetsu Ohnuma; Shigehiko Uchino
Journal:  PLoS One       Date:  2017-01-05       Impact factor: 3.240

  2 in total

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