Poor performance of the modified early warning score for predicting mortality in critically ill patients presenting to an emergency department

Abstract

BACKGROUND: This study was undertaken to validate the use of the modified early warning score (MEWS) as a predictor of patient mortality and intensive care unit (ICU)/ high dependency (HD) admission in an Asian population. METHODS:The MEWS was applied to a retrospective cohort of 1 024 critically ill patients presenting to a large Asian tertiary emergency department (ED) between November 2006 and December 2007. Individual MEWS was calculated based on vital signs parameters on arrival at ED. Outcomes of mortality and ICU/HD admission were obtained from hospital records. The ability of the composite MEWS and its individual components to predict mortality within 30 days from ED visit was assessed. Sensitivity, specificity, positive and negative predictive values were derived and compared with values from other cohorts. A MEWS of ≥4 was chosen as the cut-off value for poor prognosis based on previous studies. RESULTS:A total of 311 (30.4%) critically ill patients were presented with a MEWS ≥4. Their mean age was 61.4 years (SD 18.1) with a male to female ratio of 1.10. Of the 311 patients, 53 (17%) died within 30 days, 64 (20.6%) were admitted to ICU and 86 (27.7%) were admitted to HD. The area under the receiver operating characteristic curve was 0.71 with a sensitivity of 53.0% and a specifi city of 72.1% in addition to a positive predictive value (PPV) of 17.0% and a negative predictive value (NPV) of 93.4% (MEWS cut-off of ≥4) for predicting mortality. CONCLUSION:The composite MEWS did not perform well in predicting poor patient outcomes for critically ill patients presenting to an ED.

Application of the National Early Warning Score (NEWS) as a stratification tool on admission in an Italian acute medical ward: A perspective study

“…We investigated the reliability of NEWS cut‐offs for specific patient groups, as some concerns on its validity were raised in the literature . Debate raised about the accuracy of EWS performance in different races and patient subpopulations . For this reason, modifications of NEWS have been suggested by some authors to improve specificity whilst identifying the sickest patients …”

“…16 Debate raised about the accuracy of EWS performance in different races and patient subpopulations. 27 For this reason, modifications of NEWS have been suggested by some authors to improve specificity whilst identifying the sickest patients. 18,28 Our analysis evidenced that a number of cardiac conditions might cause acute worsening without generating higher NEWS scores on admission, as unplanned transfers owing to sudden cardiac events occurred mainly for low and medium category of risk.…”

The modified south African triage scale system for mortality prediction in resource-constrained emergency surgical centers: a retrospective cohort study

“…Different risk scoring systems for the triage of emergency patients have been described [13–19], but their performances outside the contexts and settings used in their validations cannot be warranted [20]. Furthermore, several of these models were designed to be used in a non-surgical ED and cannot be used in our surgical settings.…”

Global Critical Care: Moving Forward in Resource-Limited Settings

“…Region-specific equations or adaptations for resource-limited settings can improve performance and facilitate implementation [55][56][57][58][59]. Risk assessment tools, such as the Modified Early Warning Score, which might help triage critically patients and allocate resources [54] have shown conflicting results when applied in resource-limited settings and need additional modifications and validation [60,61].…”

“…In one ICU in Tanzania, an observational study showed that detection of vital sign derangements infrequently led to treatment modifications [80] and led the authors to conclude that nursing-based vital signs-directed clinical response protocols may not improve outcomes in resource-limited setting. Early warning systems have been shown to be predictive in some [54] but not all settings [60,61], underscoring the need for further development and validation in resource-limited settings.…”