Prediction of Postoperative Pulmonary Complications in a Population-based Surgical Cohort

Abstract

Background Current knowledge of the risk for postoperative pulmonary complications (PPCs) rests on studies that narrowly selected patients and procedures. Hypothesizing that PPC occurrence could be predicted from a reduced set of perioperative variables, we aimed to develop a predictive index for a broad surgical population. Methods Patients undergoing surgical procedures given general, neuraxial, or regional anesthesia in 59 hospitals were randomly selected for this prospective, multicenter study. The main outcome was the development of at least one of the following: respiratory infection, respiratory failure, bronchospasm, atelectasis, pleural effusion, pneumothorax, or aspiration pneumonitis. The cohort was randomly divided into a development subsample to construct a logistic regression model and a validation subsample. A PPC predictive index was constructed. Results Of 2,464 patients studied, 252 events were observed in 123 (5%). Thirty-day mortality was higher in patients with a PPC (19.5%; 95% [CI], 12.5-26.5%) than in those without a PPC (0.5%; 95% CI, 0.2-0.8%). Regression modeling identified seven independent risk factors: low preoperative arterial oxygen saturation, acute respiratory infection during the previous month, age, preoperative anemia, upper abdominal or intrathoracic surgery, surgical duration of at least 2 h, and emergency surgery. The area under the receiver operating characteristic curve was 90% (95% CI, 85-94%) for the development subsample and 88% (95% CI, 84-93%) for the validation subsample. Conclusion The risk index based on seven objective, easily assessed factors has excellent discriminative ability. The index can be used to assess individual risk of PPC and focus further research on measures to improve patient care.