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Objective:  For patients at risk for out-of-hospital cardiac arrest (OHCA) after Emergency Medical Services (EMS) arrival, outcomes may be mitigated by identifying impending arrests and intervening before they occur. Tools such as the Modified Early Warning Score (MEWS) have been developed to determine the risk of arrest, but involve relatively complicated algorithms that can be impractical to compute in the prehospital environment. A simple count of abnormal vital signs, the "EMS Modified Early Warning Score" (EMEWS), may represent a more practical alternative. We sought to compare to the ability of MEWS and EMEWS to identify patients at risk for EMS-witnessed OHCA. Methods:  We conducted a retrospect analysis of the 2018 ESO Data Collaborative database of EMS encounters. Patients without cardiac arrest before EMS arrival were categorized into those who did or did not have an EMS-witnessed arrest. MEWS was evaluated without its temperature component (MEWS-T). The performance of MEWS-T and EMEWS in predicting EMS witnessed arrest was evaluated by comparing receiver-operating characteristic curves. Results:  Of 369,064 included encounters, 4,651 were EMS witnessed arrests. MEWS-T demonstrated an area under the curve (AUC) of 0.79 (95% CI: 0.79 − 0.80), with 86.8% sensitivity and 51.0% specificity for MEWS-T ≥ 3. EMEWS demonstrated an AUC of 0.74 (95% CI: 0.73 − 0.75), with 81.3% sensitivity and 53.9% specificity for EMEWS ≥ 2. Conclusions:  EMEWS showed a similar ability to predict EMS-witnessed cardiac arrest compared to MEWS-T, despite being significantly simpler to compute. Further study is needed to evaluate whether the implementation of EMEWS can aid EMS clinicians in anticipating and preventing OHCA.

The EMS Modified Early Warning Score (EMEWS): A Simple Count of Vital Signs as a Predictor of Out-of-Hospital Cardiac Arrests