The eCART score accurately predicted severe adverse events in postoperative patients (AUC 0.79; 95% CI 0.78-0.81), performing significantly better than NEWS and MEWS.
Cohort (n=32,537)
No
Does the eCART score improve the prediction of severe adverse events compared to NEWS and MEWS in postoperative surgical inpatients?
The eCART score is significantly more accurate than both NEWS and MEWS for predicting severe adverse events, including cardiac arrest and death, in postoperative surgical inpatients.
Effect estimate: AUC 0.79 (95% CI 0.78-0.81)
OBJECTIVE: Assess the accuracy of 3 early warning scores for predicting severe adverse events in postoperative inpatients. SUMMARY OF BACKGROUND DATA: Postoperative clinical deterioration on inpatient hospital services is associated with increased morbidity, mortality, and cost. Early warning scores have been developed to detect inpatient clinical deterioration and trigger rapid response activation, but knowledge regarding the application of early warning scores to postoperative inpatients is limited. METHODS: This was a retrospective cohort study of adult patients hospitalized on the wards after surgical procedures at an urban academic medical center from November, 2008 to January, 2016. The accuracies of the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), and the electronic cardiac arrest risk triage (eCART) score were compared in predicting severe adverse events (ICU transfer, ward cardiac arrest, or ward death) in the postoperative period using the area under the receiver operating characteristic curve (AUC). RESULTS: Of the 32,537 patient admissions included in the study, 3.8% (n = 1243) experienced a severe adverse outcome after the procedure. The accuracy for predicting the composite outcome was highest for eCART AUC 0.79 (95% CI: 0.78-0.81), followed by NEWS AUC 0.76 (95% CI: 0.75-0.78), and MEWS AUC 0.75 (95% CI: 0.73-0.76). Of the individual vital signs and labs, maximum respiratory rate was the most predictive (AUC 0.67) and maximum temperature was an inverse predictor (AUC 0.46). CONCLUSION: Early warning scores are predictive of severe adverse events in postoperative patients. eCART is significantly more accurate in this patient population than both NEWS and MEWS.
Bartkowiak et al. (Mon,) conducted a cohort in Postoperative inpatients (n=32,537). electronic cardiac arrest risk triage (eCART) score vs. National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) was evaluated on Severe adverse events (ICU transfer, ward cardiac arrest, or ward death) (AUC 0.79, 95% CI 0.78-0.81). The eCART score accurately predicted severe adverse events in postoperative patients (AUC 0.79; 95% CI 0.78-0.81), performing significantly better than NEWS and MEWS.