A risk adjustment method for newborns undergoing noncardiac surgery.

Objective: To develop a risk adjustment method for in-hospital mortality in newborns undergoing noncardiac surgery.

Summary Of Background Data: Understanding variation in outcomes is critical to guide quality improvement. Reliable outcome assessments need risk adjustment to allow comparisons.

Methods: Infants or=20 cases in the data set were placed into 4 risk categories by in-hospital mortality rates. Clinical variables were added to the model to better predict mortality; areas under the receiver-operator characteristic (ROC) curves were compared. The final model was validated in the KID 2003 database.

Results: Among 6103 eligible cases in the KID 2000, 5117 (83.8%) could be assigned to a risk category. Mortality rates were 0.2% in risk category 1, 2.5% in category 2, 6.4% in 3, and 18.4% in 4. The odds of mortality increased in each risk category relative to category 1 (P < 0.001 for each). In multivariable models adjusting for risk category, the clinical variables most predictive of in-hospital death were serious respiratory conditions and necrotizing enterocolitis. The area under the ROC curve for the full model including clinical risk factors was 0.92 in the KID 2000. The model was validated using data for KID 2003 and showed excellent discrimination (ROC = 0.90).

Conclusion: This validated method provides a means of risk adjustment in groups of newborns undergoing noncardiac surgery, and should allow for comparative analyses of in-hospital mortality.