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Multicenter Study
. 2016 Nov;125(5):914-928.
doi: 10.1097/ALN.0000000000001343.

Unplanned, Postoperative Intubation in Pediatric Surgical Patients: Development and Validation of a Multivariable Prediction Model

Affiliations
Multicenter Study

Unplanned, Postoperative Intubation in Pediatric Surgical Patients: Development and Validation of a Multivariable Prediction Model

Eric C Cheon et al. Anesthesiology. 2016 Nov.

Abstract

Background: To date, the independent predictors and outcomes of unplanned postoperative intubation (UPI) in pediatric patients after noncardiac surgery are yet to be characterized. The authors aimed to identify the incidence and predictors of this event and evaluated the effect of this event on postoperative mortality.

Methods: Data of 87,920 patients from the American College of Surgeons National Surgical Quality Improvement Program Pediatric database were analyzed and assigned to derivation (n = 58,614; 66.7%) or validation (n = 29,306; 33.3%) cohorts. The derivation cohort was analyzed for the incidence and independent predictors of early UPI. The final multivariable logistic regression model was validated using the validation cohort.

Results: Early UPI occurred with an incidence of 0.2% in both cohorts. Among the 540 patients who experienced a UPI, 178 (33.0%) were intubated within the first 72 h after surgery. The final logistic regression model indicated operation time, severe cardiac risk factors, American Society of Anesthesiologists physical status classification more than or equal to 2, tumor involving the central nervous system, developmental delay/impaired cognitive function, past or current malignancy, and neonate status as independent predictors of early UPI. Having an early UPI was associated with an increased risk of unadjusted, all-cause 30-day mortality, demonstrating an odds ratio of 11.4 (95% CI, 5.8 to 22.4).

Conclusions: Pediatric patients who experienced an early UPI after noncardiac surgery had an increased likelihood of unadjusted 30-day mortality by more than 11-fold. Identification of high-risk patients can allow for targeted intervention and potential prevention of such outcomes.

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