Code blue outcomes: Relation to the modified early warning score
Cerasale M, Starakiewicz P, Parikh M, Stanley S, Mohtadi O. CODE BLUE OUTCOMES: RELATION TO THE MODIFIED EARLY WARNING SCORE. 2017;Journal of Hospital Medicine. 2017; 12 (suppl 2).
J Hosp Med
Background: The Modified Early Warning Score (MEWS) is a physiological scoring system developed to identify patients in early stages of clinical deterioration and prevent delays in proper care. It consists of systolic blood pressure, heart rate, respiratory rate, temperature and level of consciousness. Higher MEWS are associated with greater mortality and need for intensive care. The relation of the MEWS to outcomes of in-hospital patient arrests, or codes, has not been extensively evaluated. If a clear relationship is established, it would provide a crucial tool in assisting doctors, patients, and families in goals of care discussions and clinical decisions. The intent of this study was to assess the relationship between the pre-code MEWS and the post-code outcome of patients on general inpatient units. Methods: This study sample included all adult general practice unit inpatients sustaining an arrest, classified as requiring CPR and/or intubation at a 802-bed tertiary care, urban, teaching hospital from July 2014 through June 2015. Data extracted included MEWS variables at 4 hours (hr) and 24hr before an event. Time windows of 2-6hr and 20-28hr were used for the 4hr and 24hr windows respectively. For missing points, the closest retrospective value was taken, even if outside the desired range. Level of consciousness (Alert, Verbal, Pain, Unresponsive) was inferred based on the nursing, therapy, nutritional notes or if the recorded pain score was >0. The primary outcome was survival to hospital discharge. Univariate and multiple binary logistic regression models were used to assess the relationship between patient status at discharge and pre-code MEWS, adjusted for age, Charlson Comorbidity Index (CCI), and gender. Results: A total of 216 patients experienced arrests during the study period. At discharge, 53.1% of patients survived. Baseline demographics and MEWS are summarized in Table 1 for each outcome group. The odds ratio of death for the MEWS at 4hr was 0.89 (95% CI 0.75-1.07; p-value 0.24) (Figure 1). In a binary logistic regression model using 4hr MEWS, CCI, age, and gender, the outcome of death was not associated with the 4hr MEWS, but was with age (OR 0.98, 95% CI 0.96-1, p = 0.041). Conclusions: The MEWS has been associated with acute patient decompensation in the hospital, but in our study population, we did not find a relationship between the MEWS and patient survival at discharge following a code, even when adjusting for age and comorbidities. Events during the actual code event are known to affect survival, but were not evaluated in our study, which may contribute the negative result.