Predicting risk of postoperative lung injury in high-risk surgical patients: a multicenter cohort study.

Published

Journal Article

BACKGROUND: Acute respiratory distress syndrome (ARDS) remains a serious postoperative complication. Although ARDS prevention is a priority, the inability to identify patients at risk for ARDS remains a barrier to progress. The authors tested and refined the previously reported surgical lung injury prediction (SLIP) model in a multicenter cohort of at-risk surgical patients. METHODS: This is a secondary analysis of a multicenter, prospective cohort investigation evaluating high-risk patients undergoing surgery. Preoperative ARDS risk factors and risk modifiers were evaluated for inclusion in a parsimonious risk-prediction model. Multiple imputation and domain analysis were used to facilitate development of a refined model, designated SLIP-2. Area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test were used to assess model performance. RESULTS: Among 1,562 at-risk patients, ARDS developed in 117 (7.5%). Nine independent predictors of ARDS were identified: sepsis, high-risk aortic vascular surgery, high-risk cardiac surgery, emergency surgery, cirrhosis, admission location other than home, increased respiratory rate (20 to 29 and ≥30 breaths/min), FIO2 greater than 35%, and SpO2 less than 95%. The original SLIP score performed poorly in this heterogeneous cohort with baseline risk factors for ARDS (area under the receiver operating characteristic curve [95% CI], 0.56 [0.50 to 0.62]). In contrast, SLIP-2 score performed well (area under the receiver operating characteristic curve [95% CI], 0.84 [0.81 to 0.88]). Internal validation indicated similar discrimination, with an area under the receiver operating characteristic curve of 0.84. CONCLUSIONS: In this multicenter cohort of patients at risk for ARDS, the SLIP-2 score outperformed the original SLIP score. If validated in an independent sample, this tool may help identify surgical patients at high risk for ARDS.

Full Text

Duke Authors

Cited Authors

  • Kor, DJ; Lingineni, RK; Gajic, O; Park, PK; Blum, JM; Hou, PC; Hoth, JJ; Anderson, HL; Bajwa, EK; Bartz, RR; Adesanya, A; Festic, E; Gong, MN; Carter, RE; Talmor, DS

Published Date

  • May 2014

Published In

Volume / Issue

  • 120 / 5

Start / End Page

  • 1168 - 1181

PubMed ID

  • 24755786

Pubmed Central ID

  • 24755786

Electronic International Standard Serial Number (EISSN)

  • 1528-1175

Digital Object Identifier (DOI)

  • 10.1097/ALN.0000000000000216

Language

  • eng

Conference Location

  • United States