Early Identification of Patients at Risk of Acute Lung Injury

• DOI: 10.1164/rccm.201004-0549oc
• Publication Date: 2010-08-28T03:01:20Z
• Authors: Ognjen Gajic; Ousama Dabbagh; Pauline K. Park; Adebola Adesanya; Steven Y. Chang; Peter Hou; Harry Anderson; J. Jason Hoth; Mark E. Mikkelsen; Nina T. Gentile; Michelle N. Gong; Daniel Talmor; Ednan Bajwa; Timothy R. Watkins; Emir Festic; Murat Yilmaz; Remzi Iscimen; David A. Kaufman; Annette M. Esper; Ruxana Sadikot; Ivor Douglas; Jonathan Sevransky
• Keywords: Identification

Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies.To determine frequency outcome ALI development in validate a prediction score (LIPS).In this prospective multicenter observational cohort study, predisposing conditions modifiers predictive were identified from routine clinical data available during initial evaluation. The discrimination model was assessed with area under receiver operating curve (AUC). death determined after adjustment severity illness conditions.Twenty-two hospitals enrolled 5,584 risk. developed median 2 (interquartile range 1-4) days evaluation 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. varied according (from 3% pancreatitis 26% smoke inhalation). LIPS discriminated who those did not an AUC 0.80 (95% confidence interval, 0.78-0.82). When adjusted conditions, increased in-hospital (odds ratio, 4.1; 95% 2.9-5.7).ALI occurrence varies carries independently poor prognosis. Using routinely data, identifies high course their illness. This will alert clinicians about facilitate testing implementation strategies. Clinical trial registered www.clinicaltrials.gov (NCT00889772).