Initial Prehospital Rapid Emergency Medicine Score (REMS) as a Predictor of Patient Outcomes

Crowe, Remle P.; Bourn, Scott S.; Fernández, Antonio R. Martínez; Myers, Jennifer

doi:10.1080/10903127.2020.1862944

Cited by 10 publications

(20 citation statements)

References 32 publications

(43 reference statements)

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“…Overall predictive characteristics of first prehospital REMS for ED and in‐hospital patient dispositions were moderate and in line with widely used prehospital screening instruments for conditions such as stroke 31 . As previous authors have reported, 17,32 we found that prehospital REMS demonstrated slightly higher predictive power for ED mortality than ED discharge or hospital admission. Nevertheless, REMS demonstrated good discrimination for predicting ED discharge.…”

Section: Discussionsupporting

confidence: 87%

“…Nevertheless, REMS demonstrated good discrimination for predicting ED discharge. The observed AUROC of 0.72 (95% CI: 0.71–0.73) is comparable to the 0.76 reported for predicting hospital admission in a study using REMS data collected on non‐trauma patients in the ED 17 . This discrimination level is also similar to the AUROC of REMS as a predictor of ED discharge (0.684) among a large cohort of all EMS‐transported patients 17 .…”

Section: Discussionsupporting

confidence: 75%

“…In this retrospective study of over 13,000 confirmed COVID‐19 patients transported to the hospital by EMS, first prehospital REMS was associated with ED and hospital outcomes. Adequate EMS data were present to calculate REMS in 92% of cases, substantially higher than previously reported, 17,24 suggesting that REMS may be a practical tool for use in the prehospital setting. Collectively, these findings suggest utility of REMS in the specific and sometimes complex COVID‐19 patient population.…”

Section: Discussionmentioning

confidence: 67%

“…Total REMS values range from 0 to 26 and higher values are associated with increased mortality 24 . We used the first set of prehospital vital signs as entered by the EMS clinician in the REMS calculation, consistent with prior studies of EMS obtained REMS and hospital disposition 17 …”

Section: Measurementsmentioning

confidence: 99%

“…We limited this analysis to patients diagnosed with COVID‐19 to specifically examine predictive characteristics of REMS in this unique patient population with a novel disease. Prior studies have demonstrated the value of prehospital REMS for predicting hospital outcomes for a general cohort of EMS‐transported patients, suggesting utility even when the EMS suspicion of COVID‐19 may not be confirmed 14,17 . Nevertheless, future research will be required to determine whether REMS is a useful predictor of hospital outcomes for the subset of EMS patients with suspected COVID‐19 with and without confirmation at the hospital after transport.…”

Section: Limitationsmentioning

confidence: 99%

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Initial prehospital Rapid Emergency Medicine Score (REMS) to predict outcomes for COVID‐19 patients

Bourn¹,

Crowe²,

Fernández

et al. 2021

JACEP Open

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Objective The Rapid Emergency Medicine Score (REMS) has not been widely studied for use in predicting outcomes of COVID‐19 patients encountered in the prehospital setting. This study aimed to determine whether the first prehospital REMS could predict emergency department and hospital dispositions for COVID‐19 patients transported by emergency medical services. Methods This retrospective study used linked prehospital and hospital records from the ESO Data Collaborative for all 911‐initiated transports of patients with hospital COVID‐19 diagnoses from July 1 to December 31, 2020. We calculated REMS with the first recorded prehospital values for each component. We calculated area under the receiver operating curve (AUROC) for emergency department (ED) mortality, ED discharge, hospital mortality, and hospital length of stay (LOS). We determined optimal REMS cut‐points using test characteristic curves. Results Among 13,830 included COVID‐19 patients, median REMS was 6 (interquartile range [IQR]: 5‐9). ED mortality was <1% (n = 80). REMS ≥9 predicted ED death (AUROC 0.79). One‐quarter of patients (n = 3,419) were discharged from the ED with an optimal REMS cut‐point of ≤5 (AUROC 0.72). Eighteen percent (n = 1,742) of admitted patients died. REMS ≥8 optimally predicted hospital mortality (AUROC 0.72). Median hospital LOS was 8.3 days (IQR: 4.1‐14.8 days). REMS ≥7 predicted hospitalizations ≥3 days (AUROC 0.62). Conclusion Initial prehospital REMS was modestly predictive of ED and hospital dispositions for patients with COVID‐19. Prediction was stronger for outcomes more proximate to the first set of emergency medical services (EMS) vital signs. These findings highlight the potential value of first prehospital REMS for risk stratification of individual patients and system surveillance for resource planning related to COVID‐19.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 67%

Section: Measurementsmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

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