A simple clinical predictive index for objective estimates of mortality in acute lung injury* (original) (raw)

2009, Critical Care Medicine

A cute lung injury (ALI) is a devastating cause of respiratory failure associated with significant morbidity and mortality (1, 2). Despite the wealth of existing knowledge about risk factors for death in this syndrome, providers remain unable to determine which patients with ALI will ultimately die during their hospital stay. The majority of patients with ALI who die do so in the context of a decision to forgo life-sustaining treatment driven in large part by patient preferences (3-5). Prognostication in the intensive care unit (ICU) is an important part of communication with surrogates, and often plays a role in the decision to forgo lifesustaining treatment (6, 7). Incapacitated patients rely on surrogates, such as their family members, to represent their wishes during ICU care, and surrogates often rely on clinician estimates of the likelihood of survival and functional recovery from acute illness when deciding whether to forgo life-sustaining treatment for their loved ones (7). Documented cognitive and noncognitive biases held by physicians may overly influence their prognostic estimates for a given patient and have the potential to misrepresent true risk of death (8-11). Objective prognostic models, such as the Acute Physiology Assessment and Chronic Health Evaluation (APACHE) III score (12) and Simplified Acute Physiology Score III (13), can provide estimated probabilities of death for an individual patient in the ICU. How-Objective: We sought to develop a simple point score that would accurately capture the risk of hospital death for patients with acute lung injury (ALI). Design: This is a secondary analysis of data from two randomized trials. Baseline clinical variables collected within 24 hours of enrollment were modeled as predictors of hospital mortality using logistic regression and bootstrap resampling to arrive at a parsimonious model. We constructed a point score based on regression coefficients. Setting: Medical centers participating in the Acute Respiratory Distress Syndrome Clinical Trials Network (ARDSnet). Patients: Model development: 414 patients with nontraumatic ALI participating in the low tidal volume arm of the ARDSnet Acute Respiratory Management in ARDS study. Model validation: 459 patients participating in the ARDSnet Assessment of Low tidal Volume and elevated End-expiratory volume to Obviate Lung Injury study. Model Validation: 459 patients participating in the ARDSnet Assessment of Low tidal Volume and elevated End-expiratory volume to Obviate Lung Injury trial. Interventions: None. Measurements and Main Results: Variables comprising the prognostic model were hematocrit <26% (1 point), bilirubin >2 mg/dL (1 point), fluid balance >2.5 L positive (1 point), and age (1 point for age 40-64 years, 2 points for age >65 years). Predicted mortality (95% confidence interval) for 0, 1, 2, 3, and 4؉ point totals was 8% (5% to 14%), 17% (12% to 23%), 31% (26% to 37%), 51% (43% to 58%), and 70% (58% to 80%), respectively. There was an excellent agreement between predicted and observed mortality in the validation cohort. Observed mortality for 0, 1, 2, 3, and 4؉ point totals in the validation cohort was 12%, 16%, 28%, 47%, and 67%, respectively. Compared with the Acute Physiology Assessment and Chronic Health Evaluation III score, areas under the receiver operating characteristic curve for the point score were greater in the development cohort (0.72 vs. 0.67, p ‫؍‬ 0.09) and lower in the validation cohort (0.68 vs. 0.75, p ‫؍‬ 0.03). Conclusions: Mortality in patients with ALI can be predicted using an index of four readily available clinical variables with good calibration. This index may help inform prognostic discussions, but validation in nonclinical trial populations is necessary before widespread use.