Prehospital physiological parameters related illness severity scores can accurately discriminate the severe/critical state in adult patients with COVID-19

Abstract

Background Whether the National Early Warning Score 2 (NEWS2) can effectively discriminate the severe/critical state of patients with coronavirus disease 2019 (COVID-19) at the prehospital stage remains unknown. We aimed to assess the performance of NEWS2 in rapidly discriminating severe/critical COVID-19 and its relationship with prehospital medical services. Methods Six illness severity scores of 414 patients were calculated at the prehospital stage. Receiver operating characteristic curves were generated to explore the ability of these scores to discriminate severe/critical patients from mild/moderate patients. A logistic regression analysis was conducted to evaluate independent predictors associated with severe/critical state. Results The age, numbers of comorbidities, prehospital care workload, consumption of medical human resources, and illness severity scores of severe/critical patients were higher than those of mild/moderate patients ( p < 0.05). When NEWS2 scores >2, the sensitivity, specificity, positive predictive value, and negative predictive value were 93.5%, 90.7%, 74.1%, and 98.0%, respectively. The C-statistic of NEWS2 (0.963) was higher than that of quick Sequential Organ Failure Assessment (0.680, p < 0.001), CRB-65 (0.879, p < 0.001), Rapid Acute Physiology Score (0.692, p < 0.001), and Rapid Emergency Medicine Score (0.879, p < 0.001). NEWS2 was positively correlated with the numbers of prehospital treatment measures ( r = 0.732, p < 0.001), numbers of medical staff ( r = 0.615, p < 0.001), and total transport time ( r = 0.595, p < 0.001). Age ≥65 years (OR = 5.43, p = 0.016), hypertension (OR = 5.39, p < 0.001), active malignancy (OR = 5.94, p = 0.005), and NEWS2 scores >2 (OR = 124.88, p < 0.001) were independent predictors to discriminate severe/critical patients. Oxygen saturation (SpO 2 ) (OR =1.87, p < 0.001) was the unique independent predictor to discriminate false positive patients from true positive patients. Conclusions Prehospital NEWS2 can accurately and rapidly discriminate severe/critical COVID-19 during the Omicron variant wave. High levels of NEWS2 indicate an increase in prehospital care workload and consumption of medical human resources.

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

“…Healthcare institutions are in high demand of tools for quick evaluation of patient status severity or resource planning. However, assessments of the severity of the condition often vary, ranging from outcomes like in-hospital death [1][2][3] or need for intensive care [4] to specific health indicators like respiratory distress [5][6][7] or organ failure markers [7,8]. Although there is an essential need to stratify patients according to their disease severity, the diversity in assessments makes it challenging to establish a standardized approach to measure and compare the severity of COVID-19 cases across different healthcare facilities and regions.…”