The ability of COVID-19 to compromise the respiratory system has generated a substantial proportion of critically ill patients in need of invasive mechanical ventilation (IMV). The objective of this paper was to analyze the prognostic ability of the pulse oximetry saturation/fraction of inspired oxygen ratio (SpO2/FiO2) and the ratio of SpO2/FiO2 to the respiratory rate–ROX index–as predictors of IMV in an emergency department in confirmed COVID-19 patients. A multicenter, retrospective cohort study was carried out in four provinces of Spain between March and November 2020. The discriminative power of the predictive variable was assessed through a prediction model trained using a derivation sub-cohort and evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) on the validation sub-cohort. A total of 2040 patients were included in the study. The IMV rate was 10.1%, with an in-hospital mortality rate of 35.3%. The performance of the SpO2/FiO2 ratio was better than the ROX index–AUC = 0.801 (95% CI 0.746–0.855) and AUC = 0.725 (95% CI 0.652–0.798), respectively. In fact, a direct comparison between AUCs resulted in significant differences (p = 0.001). SpO2 to FiO2 ratio is a simple and promising non-invasive tool for predicting risk of IMV in patients infected with COVID-19, and it is realizable in emergency departments.

Introduction: In cases of mass-casualty incidents (MCIs), triage represents a fundamental tool for the management of and assistance to the wounded, which helps discriminate not only the priority of attention, but also the priority of referral to the most suitable center.Hypothesis/Problem: The objective of this study was to evaluate the capacity of different prehospital triage systems based on physiological parameters (Shock Index [SI], Glasgow-Age-Pressure Score [GAP], Revised Trauma Score [RTS], and National Early Warning Score 2 [NEWS2]) to predict early mortality (within 48 hours) from the index event for use in MCIs.Methods: This was a longitudinal prospective observational multi-center study on patients who were attended by Advanced Life Support (ALS) units and transferred to the emergency department (ED) of their reference hospital. Collected were: demographic, physiological, and clinical variables; main diagnosis; and data on early mortality. The main outcome variable was mortality from any cause within 48 hours.Results: From April 1, 2018 through February 28, 2019, a total of 1,288 patients were included in this study. Of these, 262 (20.3%) participants required assistance for trauma and injuries by external agents. Early mortality within the first 48 hours due to any cause affected 69 patients (5.4%). The system with the best predictive capacity was the NEWS2 with an area under the curve (AUC) of 0.891 (95% CI, 0.84-0.94); a sensitivity of 79.7% (95% CI, 68.8-87.5); and a specificity of 84.5% (95% CI, 82.4-86.4) for a cut-off point of nine points, with a positive likelihood ratio of 5.14 (95% CI, 4.31-6.14) and a negative predictive value of 98.7% (95% CI, 97.8-99.2).Conclusion: Prehospital scores of the NEWS2 are easy to obtain and represent a reliable test, which make it an ideal system to help in the initial assessment of high-risk patients, and to determine their level of triage effectively and efficiently. The Prehospital Emergency Medical System (PhEMS) should evaluate the inclusion of the NEWS2 as a triage system, which is especially useful for the second triage (evacuation priority).

Early warning scores (EWSs) help prevent and recognize and thereby act as the first signs of clinical and physiological deterioration. The objective of this study is to evaluate different EWSs (National Early Warning Score 2 (NEWS2), quick sequential organ failure assessment score (qSOFA), Modified Rapid Emergency Medicine Score (MREMS) and Rapid Acute Physiology Score (RAPS)) to predict mortality within the first 48 h in patients suspected to have Coronavirus disease 2019 (COVID-19). We conducted a retrospective observational study in patients over 18 years of age who were treated by the advanced life support units and transferred to the emergency departments between March and July of 2020. Each patient was followed for two days registering their final diagnosis and mortality data. A total of 663 patients were included in our study. Early mortality within the first 48 h affected 53 patients (8.3%). The scale with the best capacity to predict early mortality was the National Early Warning Score 2 (NEWS2), with an area under the curve of 0.825 (95% CI: 0.75–0.89). The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients presented an area under the curve (AUC) of 0.804 (95% CI: 0.71–0.89), and the negative ones with an AUC of 0.863 (95% CI: 0.76–0.95). Among the EWSs, NEWS2 presented the best predictive power, even when it was separately applied to patients who tested positive and negative for SARS-CoV-2.

The objective of this study was to assess whether the use of prehospital lactate (pLA) can increase the prognostic accuracy of the National Early Warning Score 2 (NEWS2) to detect the risk of death within 48 h. A prospective, multicenter study in adults treated consecutively by the emergency medical services (EMS) included six advanced life support (ALS) services and five hospitals. Patients were assigned to one of four groups according to their risk of mortality (low, low-medium, medium, and high), as determined by the NEWS2 score. For each group, the validity of pLA in our cohort was assessed by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. In this study, 3081 participants with a median age of 69 years (Interquartile range (IQR): 54–81) were included. The two-day mortality was 4.4% (137 cases). The scale derived from the implementation of the pLA improved the capacity of the NEWS2 to discriminate low risk of mortality, with an AUC of 0.910 (95% CI: 0.87–0.94; p < 0.001). The risk stratification provided by the NEWS2 can be improved by incorporating pLA measurement to more accurately predict the risk of mortality in patients with low risk.