Derivation and diagnostic accuracy of the surgical lung injury prediction model

Abstract

Background: Acute lung injury (ALI) is a serious postoperative complication with limited treatment options. A preoperative risk-prediction model would assist clinicians and scientists interested in ALI. The objective of this investigation was to develop a surgical lung injury prediction (SLIP) model to predict risk of postoperative ALI based on readily available preoperative risk factors.

Methods: Secondary analysis of a prospective cohort investigation including adult patients undergoing high-risk surgery. Preoperative risk factors for postoperative ALI were identified and evaluated for inclusion in the SLIP model. Multivariate logistic regression was used to develop the model. Model performance was assessed with the area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test.

Results: Out of 4,366 patients, 113 (2.6%) developed early postoperative ALI. Predictors of postoperative ALI in multivariate analysis that were maintained in the final SLIP model included high-risk cardiac, vascular, or thoracic surgery, diabetes mellitus, chronic obstructive pulmonary disease, gastroesophageal reflux disease, and alcohol abuse. The SLIP score distinguished patients who developed early postoperative ALI from those who did not with an area under the receiver operating characteristic curve (95% CI) of 0.82 (0.78-0.86). The model was well calibrated (Hosmer-Lemeshow, P = 0.55). Internal validation using 10-fold cross-validation noted minimal loss of diagnostic accuracy with a mean ± SD area under the receiver operating characteristic curve of 0.79 ± 0.08.

Conclusions: Using readily available preoperative risk factors, we developed the SLIP scoring system to predict risk of early postoperative ALI.

Figures

Figure 1. Frequency of ALI/ARDS by surgical procedure

ALI = acute lung injury; ARDS = acute respiratory distress syndrome.

Figure 2. Receiver operating characteristics curve for predicting early postoperative ALI/ARDS with the SLIP model

ALI = acute lung injury; ARDS = acute respiratory distress syndrome; SLIP = surgical lung injury prediction; AUC = area under the Receiver Operating Characteristics Curve; CI = confidence interval. *The dot on the curve represents the optimal cut-off point which maximizes the Youden index.

Figure 3. Frequency of ALI/ARDS development based on SLIP points

ALI = acute lung injury; ARDS = acute respiratory distress syndrome; SLIP = surgical lung injury prediction.