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Ann Thorac Surg 1985;40:224-228
© 1985 The Society of Thoracic Surgeons

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Articles

Risk Factors for Severe Bacterial Infections after Valve Replacement and Aortocoronary Bypass Operations: Analysis of 246 Cases by Logistic Regression

From the II. Chirurgische Universitätsklinik, Institut für Statistik und Informatik, and Klinik für Anästhesie und Allg. Intensivmedizin, University of Vienna, Vienna, Austria

Accepted for publication January 29, 1985.

^* Address reprint requests to Dr. Miholic, II. Chirurgische Universitätsklinik, University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria

Risk factors for severe bacterial infections, that is, deep sternal wound infection, pneumonia, septicemia, and prosthetic valve endocarditis, were evaluated in 246 consecutive patients undergoing valve replacement (N = 84) or aortocoronary bypass operation (N = 162). Multiple logistic regression analysis was applied to determine the ability of putative risk factors to predict infection. The risk factors considered were age, sex, diabetes mellitus, duration of cardiopulmonary bypass (CPB), duration of operation, amount of blood restored on the day of operation, repeat thoracotomy for bleeding, intraaortic balloon pumping, reoperation, emergency operation, and the professional status of the surgeon.

Severe infections occurred in similar frequency after valve replacement (8/84; 9.5%) and aortocoronary bypass (11/162; 6.8%). For patients who had a bypass procedure, repeat thoracotomy was the only factor significantly associated with infection (p = 0.0004). However, the classification analysis revealed that this variable alone is too unspecific for a reliable prediction. Univariate analysis indicated that restoration of more than 2,500 ml of blood (p = 0.0001), reoperation (p = 0.0821), duration of operation (p = 0.0061), duration of CPB (p = 0.0318), and intraaortic balloon pumping (p = 0.0281) were associated with infection following valve replacement. A model with three variables emerged from the multiple logistic regression: after correction for blood restoration, reoperation, and duration of CPB, no other variable was of additional predictive value. For patients who underwent valve replacement, the model performed well in predicting complications. The classification analysis revealed a high correspondence between observed and predicted instances of infection: it correctly predicted 75% of the patients with infection and 96% of those without infection.

We conjecture that contamination and tissue traumatization during operation are the critical factors inducing infection in patients having aortocoronary bypass, whereas host resistance compromised by the severity of the underlying disease appears to be more important in patients having cardiac valve replacement.

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