Acute respiratory distress syndrome (ARDS) results in substantial mortality but remains underdiagnosed in clinical practice. For this reason, automated “sniffer” systems that analyse electronic records have been developed to assist clinicians with ARDS diagnosis. However, a new systematic review found that these sniffer tools had moderate to high predictive value in their derivation cohorts, indicating that published literature had potential for high risks of bias in study design, particularly with regard to patient selection and reference standard application. Among 480 studies identified, nine met inclusion criteria, evaluating six unique ARDS sniffer tools. Eight studies were derivation and/or temporal validation designs, with one also evaluating the effects of implementing a tool in clinical practice. A single study performed an external validation of previously published ARDS sniffer tools.

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