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Their Usefulness and Limitations

Eric B. Rypins, MD; Farrukh Khan, MD; Dawn Collins-Irby, RN; I. James Sarfeh, MD; James T. Ashurst, PhD; Edward A. Stemmer, MD

Arch Surg. 1988;123(3):354-357.

Abstract
• We used multivariate analysis to determine whether survival following perforations of the gastrointestinal tract could be accurately predicted from preoperative data. Of 12 variables tested, four were found to have predictive value. These were age, pulmonary disease, preoperative shock, and the attending surgeon. When these four variables were employed in a logistic regression equation on 42 patients, it correctly predicted which 21 patients died before leaving the hospital. To produce an equation useful for other hospitals, we recalculated it without the attending surgeon variable. Again, the equation was used to predict survival. The correlation of predicted vs observed outcome remained high, and, using a 2x2 ² test, the correlation was significant. We then cross validated the three-variable model on data from a second hospital. The model accurately predicted the new data equally well. We believe that predictive models can identify risk factors in a variety of patient populations and can determine who is likely to benefit from specific treatment modalities.

(Arch Surg 1988;123:354-357)

Author Affiliations
From the Surgical Service, Long Beach (Calif) Veterans Administration Hospital (Drs Rypins, Khan, Sarfeh, and Stemmer and Ms Collins-Irby); and the Department of Surgery (Drs Rypins, Khan, Sarfeh, and Stemmer and Ms Collins-Irby) and the Computing Facility (Dr Ashurst), University of California, Irvine.

Footnotes
Accepted for publication Oct 22, 1986.

Read before the 93rd Annual Meeting of the Western Surgical Association, Rochester, Minn, Nov 19, 1985.

Reprint requests to Department of Surgery, University of California, Irvine Medical Center, 101 The City Drive South, Orange, CA 92668 (Dr Rypins).

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