Predicting Risk of Postoperative Lung Injury in High-risk Surgical Patients: A Multicenter Cohort Study

• Published in: Anesthesiology (Philadelphia) 2014-05, Vol.120 (5), p.1168-1181
• Main Authors: Kor, Daryl J, Lingineni, Ravi K, Gajic, Ognjen, Park, Pauline K, Blum, James M, Hou, Peter C, Hoth, J Jason, Anderson, Harry L, Bajwa, Ednan K, Bartz, Raquel R, Adesanya, Adebola, Festic, Emir, Gong, Michelle N, Carter, Rickey E, Talmor, Daniel S
• Format: Article
• Language: English
• Subjects: Acute Lung Injury - diagnosis; Acute Lung Injury - epidemiology; Aged; Anesthesia; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy; Biological and medical sciences; Cardiac Surgical Procedures - adverse effects; Cohort Studies; Female; Humans; Male; Medical sciences; Middle Aged; Postoperative Complications - diagnosis; Postoperative Complications - epidemiology; Predictive Value of Tests; Prospective Studies; Respiratory Distress Syndrome, Adult - diagnosis; Respiratory Distress Syndrome, Adult - epidemiology; Risk Factors
• ISSN: 0003-3022; 1528-1175
• DOI: 10.1097/ALN.0000000000000216

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 identifiedsepsis, 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.