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Prediction of clinical deterioration risk at 8 hours after arrival in emergency department in non‐traumatic patients using trends in modified early warning score level

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AbstractBackgroundImproving the quality of medical care in hospitals is a major priority for all departments. The early warning score (EWS) trend is an effective early risk stratification tool that reflects the changes in patient condition and allows better assessment of deterioration risk.ObjectiveThe aim of this study was to investigate whether utilizing the trend of the modified early warning score (MEWS) level within 4 h of a patient's arrival in the emergency department (ED) could identify patients at risk of clinical deterioration at 8 h after arrival in the ED.MethodsWe conducted a retrospective observational study of non‐trauma patients who had at least two vital sign measurements (Glasgow Coma Scale score, heart rate, blood pressure, respiratory rate, and body temperature) within 8 h of arriving in the ED. The primary outcome was patients who had MEWS ≥ 4 at 8 h after arrival in the ED. We performed multivariate logistic regression analysis using age, sex, MEWS level at arrival in the ED, MEWS level within 4 h after arrival in the ED, and MEWS level trend over time.ResultsAmong the 5825 patients, 680 (11.7%) were at risk of deterioration at 8 h after arrival in the ED. To predict the risk of deteriorating conditions (MEWS ≥ 4), utilizing the MEWS level trend within 4 h of arrival in the ED was more effective in identifying patients at risk of deterioration after 8 h of arrival in the ED compared to using a single MEWS value during the ED stay. The corresponding areas under the receiver operating characteristic curve were 0.756 (95% confidence interval (CI) 0.734–0.778) and 0.846 (95% CI 0.827–0.865), respectively (p < 0.01).ConclusionsThe proposed trend‐based predictive model for MEWS levels can alert healthcare personnel regarding patients at increased risk of deterioration (MEWS ≥ 4), potentially reducing mortality rates during ED stays.
Title: Prediction of clinical deterioration risk at 8 hours after arrival in emergency department in non‐traumatic patients using trends in modified early warning score level
Description:
AbstractBackgroundImproving the quality of medical care in hospitals is a major priority for all departments.
The early warning score (EWS) trend is an effective early risk stratification tool that reflects the changes in patient condition and allows better assessment of deterioration risk.
ObjectiveThe aim of this study was to investigate whether utilizing the trend of the modified early warning score (MEWS) level within 4 h of a patient's arrival in the emergency department (ED) could identify patients at risk of clinical deterioration at 8 h after arrival in the ED.
MethodsWe conducted a retrospective observational study of non‐trauma patients who had at least two vital sign measurements (Glasgow Coma Scale score, heart rate, blood pressure, respiratory rate, and body temperature) within 8 h of arriving in the ED.
The primary outcome was patients who had MEWS ≥ 4 at 8 h after arrival in the ED.
We performed multivariate logistic regression analysis using age, sex, MEWS level at arrival in the ED, MEWS level within 4 h after arrival in the ED, and MEWS level trend over time.
ResultsAmong the 5825 patients, 680 (11.
7%) were at risk of deterioration at 8 h after arrival in the ED.
To predict the risk of deteriorating conditions (MEWS ≥ 4), utilizing the MEWS level trend within 4 h of arrival in the ED was more effective in identifying patients at risk of deterioration after 8 h of arrival in the ED compared to using a single MEWS value during the ED stay.
The corresponding areas under the receiver operating characteristic curve were 0.
756 (95% confidence interval (CI) 0.
734–0.
778) and 0.
846 (95% CI 0.
827–0.
865), respectively (p < 0.
01).
ConclusionsThe proposed trend‐based predictive model for MEWS levels can alert healthcare personnel regarding patients at increased risk of deterioration (MEWS ≥ 4), potentially reducing mortality rates during ED stays.

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