Validation of a tool for estimating clinician recognition of ARDS using data from the international LUNG SAFE study

• Published in: PLOS digital health 2023-08, Vol.2 (8), p.e0000325-e0000325
• Main Authors: Bechel, Meagan A., Madotto, Fabiana, Pah, Adam R., Bellani, Giacomo, Laffey, John G., Pham, Tài, Amaral, Luís A. Nunes, Weiss, Curtis H.
• Format: Article
• Language: English
• Subjects: Computer and Information Sciences; Coronaviruses; COVID-19; Data collection; Documentation; Electronic health records; Engineering and Technology; Hypoxemia; Intensive care; Medicine and Health Sciences; Mortality; Pandemics; Patients; People and Places; Physical Sciences; Respiratory distress syndrome; Respiratory failure; Secondary analysis; Sensitivity analysis; Ventilators
• ISSN: 2767-3170; 2767-3170
• DOI: 10.1371/journal.pdig.0000325

Under-recognition of acute respiratory distress syndrome (ARDS) by clinicians is an important barrier to adoption of evidence-based practices such as low tidal volume ventilation. The burden created by the COVID-19 pandemic makes it even more critical to develop scalable data-driven tools to improve ARDS recognition. The objective of this study was to validate a tool for accurately estimating clinician ARDS recognition rates using discrete clinical characteristics easily available in electronic health records. We conducted a secondary analysis of 2,705 ARDS and 1,261 non-ARDS hypoxemic patients in the international LUNG SAFE cohort. The primary outcome was validation of a tool that estimates clinician ARDS recognition rates from health record data. Secondary outcomes included the relative impact of clinical characteristics on tidal volume delivery and clinician documentation of ARDS. In both ARDS and non-ARDS patients, greater height was associated with lower standardized tidal volume (mL/kg PBW) (ARDS: adjusted β = -4.1, 95% CI -4.5 –-3.6; non-ARDS: β = -7.7, 95% CI -8.8 –-6.7, P