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.

journal_name

Anesthesiology

journal_title

Anesthesiology

authors

Kor DJ,Warner DO,Alsara A,Fernández-Pérez ER,Malinchoc M,Kashyap R,Li G,Gajic O

doi

10.1097/ALN.0b013e31821b5839

subject

Has Abstract

pub_date

2011-07-01 00:00:00

pages

117-28

issue

1

eissn

0003-3022

issn

1528-1175

journal_volume

115

pub_type

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