Hou, Peter C.

Objective: The Lung Injury Prediction Score identifies patients at risk for acute respiratory distress syndrome in the emergency department, but it has not been validated in non-emergency department hospitalized patients. We aimed to evaluate whether Lung Injury Prediction Score identifies non-emergency department hospitalized patients at risk of developing acute respiratory distress syndrome at the time of critical care contact. Design: Retrospective study. Setting: Five academic medical centers. Patients: Nine hundred consecutive patients (≥ 18 yr old) with at least one acute respiratory distress syndrome risk factor at the time of critical care contact. Interventions: None. Measurements and Main Results: Lung Injury Prediction Score was calculated using the worst values within the 12 hours before initial critical care contact. Patients with acute respiratory distress syndrome at the time of initial contact were excluded. Acute respiratory distress syndrome developed in 124 patients (13.7%) a median of 2 days (interquartile range, 2–3) after critical care contact. Hospital mortality was 22% and was significantly higher in acute respiratory distress syndrome than non-acute respiratory distress syndrome patients (48% vs 18%; p < 0.001). Increasing Lung Injury Prediction Score was significantly associated with development of acute respiratory distress syndrome (odds ratio, 1.31; 95% CI, 1.21–1.42) and the composite outcome of acute respiratory distress syndrome or death (odds ratio, 1.26; 95% CI, 1.18–1.34). A Lung Injury Prediction Score greater than or equal to 4 was associated with the development of acute respiratory distress syndrome (odds ratio, 4.17; 95% CI, 2.26–7.72), composite outcome of acute respiratory distress syndrome or death (odds ratio, 2.43; 95% CI, 1.68–3.49), and acute respiratory distress syndrome after accounting for the competing risk of death (hazard ratio, 3.71; 95% CI, 2.05–6.72). For acute respiratory distress syndrome development, the Lung Injury Prediction Score has an area under the receiver operating characteristic curve of 0.70 and a Lung Injury Prediction Score greater than or equal to 4 has 90% sensitivity (misses only 10% of acute respiratory distress syndrome cases), 31% specificity, 17% positive predictive value, and 95% negative predictive value. Conclusions: In a cohort of non-emergency department hospitalized patients, the Lung Injury Prediction Score and Lung Injury Prediction Score greater than or equal to 4 can identify patients at increased risk of acute respiratory distress syndrome and/or death at the time of critical care contact but it does not perform as well as in the original emergency department cohort.

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