Decision Support Tool for Early Differential Diagnosis of Acute Lung Injury and Cardiogenic Pulmonary Edema in Medical Critically-ill Patients.

Link to article at PubMed

Decision Support Tool for Early Differential Diagnosis of Acute Lung Injury and Cardiogenic Pulmonary Edema in Medical Critically-ill Patients.

Chest. 2011 Oct 26;

Authors: Schmickl CN, Shahjehan K, Li G, Dhokarh R, Kashyap R, Janish C, Alsara A, Jaffe AS, Hubmayr RD, Gajic O

Abstract
Abstract BACKGROUND:At the onset of acute hypoxic respiratory failure, critically-ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis. METHODS:In a population-based retrospective development cohort validated electronic surveillance identified critically-ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post-hoc expert review served as gold standard. RESULTS:Of 332 patients in a development cohort, expert reviewers (kappa 0.86) classified 156 as ALI and 176 as CPE. The validation cohort had 161 patients (ALI=113, CPE=48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy and SpO2/FiO2-ratio. It demonstrated good discrimination (Area under Curve, AUC=0.81, 95%-CI=0.77-0.86) and calibration (Hosmer-Lemeshow, HL p=0.16). Similar performance was obtained in the validation cohort (AUC=0.80, 95%-CI=0.72-0.88; HL p=0.13). CONCLUSIONS:A simple decision support tool accurately classifies acute pulmonary edema reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of ALI and CPE patients into research studies as well as improve and rationalize clinical management and resource utilization.

PMID: 22030803 [PubMed - as supplied by publisher]

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