Document Detail

Predicting Risk of Postoperative Lung Injury in High-risk Surgical Patients: A Multicenter Cohort Study.
MedLine Citation:
PMID:  24755786     Owner:  NLM     Status:  In-Data-Review    
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.
Daryl J Kor; Ravi K Lingineni; Ognjen Gajic; Pauline K Park; James M Blum; Peter C Hou; J Jason Hoth; Harry L Anderson; Ednan K Bajwa; Raquel R Bartz; Adebola Adesanya; Emir Festic; Michelle N Gong; Rickey E Carter; Daniel S Talmor
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Anesthesiology     Volume:  120     ISSN:  1528-1175     ISO Abbreviation:  Anesthesiology     Publication Date:  2014 May 
Date Detail:
Created Date:  2014-04-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  1300217     Medline TA:  Anesthesiology     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1168-81     Citation Subset:  AIM; IM    
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