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.

journal_name

Anesthesiology

journal_title

Anesthesiology

authors

Brueckmann B,Villa-Uribe JL,Bateman BT,Grosse-Sundrup M,Hess DR,Schlett CL,Eikermann M

doi

10.1097/ALN.0b013e318293065c

subject

Has Abstract

pub_date

2013-06-01 00:00:00

pages

1276-85

issue

6

eissn

0003-3022

issn

1528-1175

journal_volume

118

pub_type

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