Identifying Patients at Risk of Developing Acute Lung Injury at the Time of Hospital Admission:Toward the Prevention of Acute Lung Injury (ALI)

Acute lung injury (ALI) is an example of a critical care syndrome with limited treatment options once the condition is fully established.Not surprisingly, many treatments targeting the mechanisms identified in preclinical studies have failed to improve patient outcomes.The most likely reason could be due to inadequate and delayed recognition of patients at risk and the subsequent development of the full blown syndrome.ALI/ARDS usually develops during the first hours of ICU admission, and often is the very reason for ICU admission.

Clinical prediction models have been extensively used in the clinical practice to identify patients at high risks who may benefit from specific interventions. However, no such tool exists to predict the development of ALI in patients at risk. We have recently developed an ALI prediction model (Lung Injury Prediction Score:LIPS)which incorporates demographic, environmental and clinical characteristics at the time of, and before, hospital admission. If validated, this model will serve to find the population of patients at high risk of ALI in whom future prevention trials will be conducted. By determining not only patients at high risk but also the attributable burden of ALI/ARDS in contemporary cohorts of patients at risk, our findings will facilitate the prioritization of preventive strategies and future clinical trials.