Predictors of Survival in Critically Ill Patients With Acute Respiratory Distress Syndrome (ARDS)

An Observational Study

Felix Balzer; Mario Menk; Jannis Ziegler; Christian Pille; Klaus-Dieter Wernecke; Claudia Spies; Maren Schmidt; Steffen Weber-Carstens; Maria Deja


BMC Anesthesiol. 2016;16(108) 

In This Article


The American-European Consensus Conference (AECC) definition was commonly used by clinicians to categorize ARDS patients.[1] But issues regarding reliability of various criteria have emerged, including a poor interobserver reliability of chest radiograph interpretation, confusing acute lung injury (ALI)/ARDS nomenclature and the inconsistency of PaO2/FiO2 ratio due to the effect of positive end-expiratory pressure (PEEP).[2] Those limitations have recently been tackled with the establishment of the Berlin Definition in 2012.[3] Herein, ARDS patients are classified into three independent categories (i.e., mild, moderate and severe ARDS) and additional variables are taken into account. Several factors, such as severity of chest radiograph, a PEEP level above 5 cm H2O, low compliance and poor oxygenation, are now used to define severe ARDS.

The Berlin Definition addresses and clarifies some of the limitations of the AECC definition and is the first to include minimum ventilator settings. The predictive validity for mortality is only slightly better than in the AECC definition. However, it was not designed to serve as a prognostication tool.[2] In the past, other variables of interest, such as the PaO2/FiO2 ratio, the oxygenation index (OI), the influence of co-morbidities and a number of clinical scores (SAPS, SOFA), were screened in ARDS patients to prompt early prediction of outcome and to ensure more efficient resource allocation.[4–6] As the ARDS is, however, a very heterogeneous syndrome with several different causes, all proposed definitions, parameters and variables did not resolve the problem adequately. For a reliable prediction of outcome and mortality in ARDS patients, comparable treatment strategies in respective hospitals are required. However, treatment algorithms applied on ARDS patients may differ significantly between different hospitals (usage of inhalative nitric oxide, ventilator settings, criteria to start lung assist devices) representing different approaches to the "state of the art" in ARDS therapy. These problems may be partly resolved in unicentric studies in specialized hospitals involving sufficiently high numbers of patients.

Outcome prediction in critically ill patients at a given point of time plays a major role (e.g. for appropriate treatment decisions and family communication). In this context, we examined the predictive values of the AECC and Berlin definition and also assessed alternative clinical parameters that are available in routine patient care.