Development and validation of a score for prediction of postoperative respiratory complications

Abstract

Background: Postoperative respiratory failure is associated with increased morbidity and mortality, as well as high costs of hospital care.

Methods: Using electronic anesthesia records, billing data, and chart review, the authors developed and validated a score predicting reintubation in the hospital after primary extubation in the operating room, leading to unplanned mechanical ventilation within the first 3 postoperative days. Using multivariable logistic regression analysis, independent predictors were determined and a score postulated and validated.

Results: In the entire cohort (n = 33,769 surgical cases within 29,924 patients), reintubation occurred in 137 cases (0.41%). Of those, 16%, (n = 22) died subsequently, whereas the mortality in patients who were not reintubated was 0.26% (P < 0.0001). Independent predictors for reintubation were: American Society of Anesthesiologist Score 3 or more, emergency surgery, high-risk surgical service, history of congestive heart failure, and chronic pulmonary disease. A point value of 3, 3, 2, 2, and 1 were assigned to these predictors, respectively, based on their β coefficient in the predictive model. The score yielded a calculated area under the curve of 0.81, whereas each point increment was associated with a 1.7-fold (odds ratio: 1.72 [95% CI, 1.55-1.91]) increase in the odds for reintubation in the training dataset. Using the validation dataset (n = 16,884), the score had an area under the curve of 0.80 and similar estimated probabilities for reintubation.

Conclusion: The authors developed and validated a score for the prediction of postoperative respiratory complications, a simple, 11-point score that can be used preoperatively by anesthesiologists to predict severe postoperative respiratory complications.