Comparison of the National Early Warning Score (NEWS) and the Modified Early Warning Score (MEWS) for predicting admission and in-hospital mortality in elderly patients in the pre-hospital setting and in the emergency department

Abstract

The aim of this study is to evaluate the usefulness of the pre-hospital National Early Warning Score (pNEWS) and the pre-hospital Modified Early Warning Score (pMEWS) for predicting admission and in-hospital mortality in elderly patients presenting to the emergency department (ED). We also compare the value of the pNEWS with that of the ED NEWS (eNEWS) and ED MEWS (eMEWS) for predicting admission and in-hospital mortality. This retrospective, single-centre observational study was carried out in the ED of Jikei University Kashiwa Hospital, in Chiba, Japan, from 1st April 2017 to 31st March 2018. All patients aged 65 years or older were included in this study. The pNEWS/eNEWS were derived from seven common physiological vital signs: respiratory rate, peripheral oxygen saturation, the presence of inhaled oxygen parameters, body temperature, systolic blood pressure, pulse rate and Alert, responds to Voice, responds to Pain, Unresponsive (AVPU) score, whereas the pMEWS/eMEWS were derived from six common physiological vital signs: respiratory rate, peripheral oxygen saturation, body temperature, systolic blood pressure, pulse rate and AVPU score. Discrimination was assessed by plotting the receiver operating characteristic (ROC) curve and calculating the area under the ROC curve (AUC). The median pNEWS, pMEWS, eNEWS and eMEWS were significantly higher at admission than at discharge (p < 0.001). The median pNEWS, pMEWS, eNEWS and eMEWS of non-survivors were significantly higher than those of the survivors (p < 0.001). The AUC for predicting admission was 0.559 for the pNEWS and 0.547 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting admission (p = 0.102). The AUCs for predicting in-hospital mortality were 0.678 for the pNEWS and 0.652 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting in-hospital mortality (p = 0.081). The AUC for predicting admission was 0.628 for the eNEWS and 0.591 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting admission (p < 0.001). The AUC for predicting in-hospital mortality was 0.789 for the eNEWS and 0.720 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting in-hospital mortality (p < 0.001). For admission and in-hospital mortality, the AUC of the eNEWS was significantly greater than that of the pNEWS (p < 0.001, p < 0.001), and the AUC of the eMEWS was significantly greater than that of the pMEWS (p < 0.01, p < 0.05). Our single-centre study has demonstrated the low utility of the pNEWS and the pMEWS as predictors of admission and in-hospital mortality in elderly patients, whereas the eNEWS and the eMEWS predicted admission and in-hospital mortality more accurately. Evidence from multicentre studies is needed before introducing pre-hospital versions of risk-scoring systems.

Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients

“…26 EWSs, which are generally used in the patients with sepsis, trauma, and other critical ills, are such scoring systems and are widely used in hospitals to identify patients who are clinically deteriorating. 17,20,27,28 On the whole, the performance of each EWS was acceptable for screening the COVID-19 patients. However, there are differences in the performance among 5 EWSs.…”

Complexity of nursing care at 24 h from admission predicts in-hospital mortality in medical units: a cohort study

“…Hospital administrators can implement the SIPI measure to identify those patients, units or departments that require a major amount of nursing care, particularly when recommended staffing levels cannot be assured due to lack of resources. Future studies should: assess the association between complexity of nursing care and in-hospital mortality in surgical settings; assess the association between the complexity of nursing care measured by the SIPI score and in-hospital mortality, adjusting for nursing-related variables as staffing, skill mix and education; assess the relationship between complexity of nursing care and widely used early warning scores such as the National Early Warning Score [5]; identify the different levels of nurse staffing according to the complexity of nursing care as measured by the SIPI; assess the association between Diagnosis Related Groups (DRGs) and complexity of nursing care, in order to investigate if the current approach in allocating resources takes into account the demand of nursing care.…”

“…Several studies explored those predictors focusing on patients' clinical characteristics. Comorbidity [4], clinical instability [5] and baseline functional status [6] were found to be strong predictors of inhospital mortality. Other studies focused on the severity of a specific admission disease or condition.…”

Use of the Modified Early Warning Score in intrahospital transfer of patients

“…( 7 ) Recent studies have shown high variability in the accuracy of this score, which has led to uncertainty regarding its use. ( 2 , 4 , 9 , 10 ) Its role in the inter- or intrahospital transfer of patients is even more undefined. Although it has been applied in interhospital pretransfer, ( 11 - 13 ) its use at the time of transfer between sectors of the same hospital has not yet been explored.…”