B. Bartkowiak1, A. M. Snyder1, A. Benjamin2, A. Schneider2, N. M. Twu1, M. M. Churpek1, D. P. Edelson1, K. K. Roggin2 1University Of Chicago,Department Of Medicine,Chicago, IL, USA 2University Of Chicago,Department Of Surgery,Chicago, IL, USA
Introduction: Postoperative clinical deterioration on the wards is associated with increased morbidity, mortality, and cost. Early warning scores (EWSs) have been developed to detect inpatient clinical deterioration and trigger rapid response activation more generally, but little is known about the specific application of EWSs to postoperative inpatients.
Methods: We aimed to assess the accuracy of three general EWSs for predicting severe adverse events (SAE) in postoperative inpatients. We conducted a retrospective cohort study of adult patients hospitalized on the wards following operative procedures at an academic medical center in the United States from 11/2008 to 1/2016. We compared the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), and the electronic Cardiac Arrest Risk Triage (eCART) score. The maximum scores from postoperative ward locations were used for analysis. SAE were defined as ICU transfer, ward cardiac arrest, or ward death in the postoperative period. Accuracy was evaluated using the area under the receiver operating characteristic curve (AUC). Patients with multiple operations were censored at the start of the second procedure.
Results: Of the 30,009 patient admissions included in the study, 4% (n=1,530) experienced a SAE a median of 2 days (IQR; 0.3-5.6) following the procedure. Patients who experienced a SAE reached higher maximum scores during their postoperative stay with the following median (IQR) values: eCART, 58 (12-159) vs 12 (7-23); MEWS, 4 (3-6) vs 3 (2-3); and NEWS, 9 (7-11) vs 6 (4-7). The accuracy for predicting the composite outcome was highest for eCART (AUC 0.80 [CI; 0.79-0.81]), followed by NEWS (AUC 0.77 [CI; 0.75-0.78]), and MEWS (AUC 0.75 [CI; 0.74-0.77]); see figure. Of the individual vital signs and labs, high respiratory rate was the most predictive (AUC 0.70) and high temperature the least (AUC 0.48).
Conclusion: EWSs are predictive of SAEs in postoperative surgical patients. eCART is significantly more accurate in this patient population than both NEWS and MEWS. Future work validating these findings multi-institutionally and determining whether the use of eCART improves the outcomes of high-risk post-operative patients is warranted.
