Effectiveness of the rapid emergency medicine score and the rapid acute physiology score in prognosticating mortality in patients presenting to the emergency department with COVID-19 symptoms

The clinical frailty scale improves risk prediction in older emergency department patients: a comparison with qSOFA, NEWS2, and REMS

Vital signs are essential for monitoring and prognostication in the emergency department (ED); however, they may not fully capture the complexity of frailty in older adults. In this multicenter retrospective study of 932 older patients who visited the EDs of three tertiary university hospitals between August 1 and October 31, 2023, we investigated the prognostic value of the Clinical Frailty Scale (CFS) in older patients in the ED and its potential to improve existing vital sign-based scoring systems. The primary outcomes were hospital admission, intensive care unit (ICU) admission, and in-hospital mortality. The AUROC was used to evaluate and compare the predictive performance of CFS, qSOFA, NEWS2, and REMS scores individually and in combination. Combining the CFS with these scores significantly improved predictive accuracy compared to individual scores alone. For hospital admission, the AUROCs were 0.715 (95% CI 0.685-0.744), 0.723 (95% CI 0.693-0.752), and 0.688 (95% CI 0.657-0.718) for CFS + qSOFA, CFS + NEWS2, and CFS + REMS, respectively. For ICU admission, the AUROCs were 0.730 (95% CI 0.701-0.759), 0.714 (95% CI 0.684-0.743), and 0.707 (95% CI 0.677-0.736), respectively. For in-hospital mortality, the AUROCs were 0.798 (95% CI: 0.771-0.823), 0.774 (95% CI: 0.746-0.801), and 0.819 (95% CI: 0.793-0.843), respectively, indicating excellent performance. Incorporating frailty assessment using the CFS enhances risk stratification in older patients in the ED by complementing vital sign-based scores. This provides a more comprehensive assessment, enabling better informed clinical decisions. This study supports employing routine frailty assessment in the ED and the development of enhanced risk stratification tools that incorporate frailty.

Incorporation of age into patient early warning scores significantly improves mortality prediction

BACKGROUND

Age is a critical factor for the assessment of patients attended by emergency medical services (EMSs). However, how age modifies early warning scores' (EWSs) predictive ability should be unveiled.

AIM

To determine how age influences the performance of EWS [National Early Warning Score 2 (NEWS2), VitalPAC-Early Warning Score (ViEWS), Rapid Acute Physiology Score (RAPS) and modified Rapid Emergency Medicine Score (mREMS)] to predict 2-day mortality. The secondary objective was to determine the performance of EWSs at different age ranges.

DESIGN

A prospective, observational study performed between November 2019 and July 2023.

METHODS

A multicenter, ambulance-based study, considering 38 basic life support units and six advanced life support units referring to four tertiary care hospitals. Eligible patients were adults recruited from among all phone requests for emergency assistance who were later evacuated to emergency departments. The primary outcome was 2-day in-hospital mortality (includes all-cause mortality). The main measures were demographical and vital signs needed for EWS calculation.

RESULTS AND DISCUSSION

A total of 8028 participants fulfilled the inclusion criteria, with 7654 survivors and 374 non-survivors. Among age ranges, the 2-day mortality was 2.8% for the ≤44 years, 3.3% for the 45-64 years, 4.1% for the 65-74 years and 6.7% for the ≥75-year age group. The inclusion of age significantly improved the Area Under the Curve (AUC) in all the scores (P = 0.006 for non-age-adjusted mREMS, P = 0.001 for NEWS2, P = 0.002 for ViEWS, P = 0.028 for RAPS, all compared with their counterparts with age).

CONCLUSION

Our results demonstrated that the incorporation of age into the EWS improved the performance of the scores. These results will allow the EMS to improve patient management and resource optimization by including an easy-to-obtain variable.

Predicting Mortality for COVID-19 Patients Admitted to an Emergency Department Using Early Warning Scores in Poland

COVID-19 disease is characterised by a wide range of symptoms that in most cases resemble flu or cold. Early detection of infections, monitoring of patients' conditions, and identification of patients with worsening symptoms became crucial during the peak of pandemic. The aim of this study was to assess and compare the performance of common early warning scores at the time of admission to an emergency department in predicting in-hospital mortality in patients with COVID-19. The study was based on a retrospective analysis of patients with SARS-CoV-2 infection admitted to an emergency department between March 2020 and April 2022. The prognostic value of early warning scores in predicting in-hospital mortality was assessed using the receiver operating characteristic (ROC) curve. Patients' median age was 59 years, and 52.33% were male. Among all the EWS we assessed, REMS had the highest overall accuracy (AUC 0.84 (0.83-0.85)) and the highest NPV (97.4%). REMS was the most accurate scoring system, characterised by the highest discriminative power and negative predictive value compared to the other analysed scoring systems. Incorporating these tools into clinical practice in a hospital emergency department could provide more effective assessment of mortality and, consequently, avoid delayed medical assistance.

Comparison of seven prehospital early warning scores to predict long-term mortality: a prospective, multicenter, ambulance-based study

The long-term predictive validity of early warning scores (EWS) has not been fully elucidated yet. The aim of the present study is to compare seven prehospital EWS to predict 1-year mortality. A prospective, multicenter, ambulance-based study of adult patients with an acute illness involving six advanced life support units and 38 basic life support units, referring to five emergency departments in Spain. The primary outcome was long-term mortality with a 1-year follow-up. The compared scores included: National Early Warning Score 2, VitalPAC early warning score, modified rapid emergency medicine score (MREMS), Sepsis-related Organ Failure Assessment, Cardiac Arrest Risk Triage Score, Rapid Acute Physiology Score, and Triage Early Warning Score. Discriminative power [area under the receiver operating characteristic curve (AUC)] and decision curve analysis (DCA) were used to compare the scores. Additionally, a Cox regression and Kaplan-Meier method were used. Between 8 October 2019, and 31 July 2021, a total of 2674 patients were selected. The MREMS presented the highest AUC of 0.77 (95% confidence interval, 0.75-0.79), significantly higher than those of the other EWS. It also exhibited the best performance in the DCA and the highest hazard ratio for 1-year mortality [3.56 (2.94-4.31) for MREMS between 9 and 18 points, and 11.71 (7.21-19.02) for MREMS > 18]. Among seven tested EWS, the use of the MREMS presented better characteristics to predict 1-year mortality; however, all these scores present moderate performances.

Evaluation of Short-Term Mortality Prediction Using Initial Lactate and NEWS+L at Admission in COVID-19 Patients

OBJECTIVE

To predict the short-term mortality of the serum lactate level and the National Early Warning Score + lactate (NEWS+L) at the time of first admission to the emergency department in COVID-19 patients.

MATERIALS AND METHODS

This retrospective analysis was performed by screening the data of COVID-19 patients over a 6-month period (from January 15, 2021, to June 15, 2021). The demographic, comorbidities, vital parameters, and lactate values, as well as C- reactive protein (CRP), blood urea nitrogen (BUN), and 28-day mortality data were recorded.

RESULTS

A total of 70 patients were included in our study. The median (25^th - 75th percentile) age was 58 (47.3 - 73.5) years, and 33 (47.1%) patients were female. The mean lactate value was 1.6 (1.2 - 1.98) mmol/L, the mean NEWS was 6 (4-7.75), and the mean NEWS+L was 7.24 ± 2.54. Mortality occurred in 13 (18.2%) of the 70 patients at 28 days. Lactate, NEWS, and NEWS+L had no significant relationship with mortality. None of these parameters was able to predict mortality (P = 0.132, 0.670, and 0.994, respectively).

CONCLUSION

Our findings showed that the NEWS+L, NEWS, and lactate level could not predict short-term mortality in COVID-19 patients at the time of first admission.

Prognostic Value of Physiological Scoring Systems in COVID-19 Patients: A Prospective Observational Study

The objective of this study was to investigate the accuracy of the Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), Rapid Acute Physiology Score (RAPS), Worthing Physiological Scoring System (WPSS), and Revised Trauma Score (RTS) for predicting the inhospital mortality of COVID-19 patients. This diagnostic accuracy study was conducted in Tehran, Iran, from November 15, 2020, to March 10, 2021. The participants consisted of 246 confirmed cases of COVID-19 patients who were admitted to the emergency department. The patients were followed from the point of admission up until discharge from the hospital. The mortality status of patients (survivor or nonsurvivor) was reported at the discharge time, and the receiver operating characteristic curve analysis of each scoring system for predicting inhospital mortality was estimated. The area under the curve of REMS was significantly higher than other scoring systems and in cutoff value of 6 and greater had a sensitivity and specificity of 89.13% and 55.50%, respectively. Among the five scoring systems employed in this study, REMS had the best accuracy to predict the inhospital mortality rate of COVID-19 patients and RAPS had the lowest accuracy for inhospital mortality. Thus, REMS is a useful tool that can be employed in identifying high-risk COVID-19 patients.

C-Reactive Protein-to-Albumin Ratio and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis

C-reactive protein-to-albumin ratio (CAR) is an independent risk factor in cardiovascular, cerebrovascular, and infectious diseases. Through this study, we investigated the CAR values with respect to the severity and mortality of COVID-19 patients. We performed a systematic review and meta-analysis to retrieve studies that evaluated CAR values upon hospital admission in relation to the severity or mortality of COVID-19 patients. We adopted a random-effect model to calculate the pooled mean difference (MD) and their 95% confidence intervals (CI). Quality assessment was appraised using a Newcastle−Ottawa scale and publication bias was assessed using the Begg-test and funnel plot. We equally performed a subgroup analysis using study location and a sensitivity analysis only with studies with low risk of bias. We analyzed 32 studies (n = 12445). Severe COVID-19 patients had higher on-admission CAR values than non-severe COVID-19 patients (MD: 1.69; 95% CI: 1.35−2.03; p < 0.001; I2 = 89%). Non-survivor patients with COVID-19 had higher CAR values than survivor patients (MD: 2.59; 95% CI: 1.95−3.23; p < 0.001; I2 = 92%). In sensitivity analysis, the relationship remained with a decreasing of heterogeneity for severity (MD: 1.22; 95% CI: 1.03−1.40; p < 0.001; I2 = 13%) and for mortality (MD: 2.99; 95% CI: 2.47−3.51; p < 0.001; I2 = 0%). High CAR values were found in COVID-19 patients who developed severe disease or died.

Predictive Ability of the MEWS, REMS, and RAPS in Geriatric Patients With SARS-CoV-2 Infection in the Emergency Department

BACKGROUND

The aim of this study was to compare the ability of the Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), and Rapid Acute Physiology Score (RAPS) to predict 30-d mortality in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection aged 65 y and over.

METHODS

This prospective, single-center, observational study was carried out with 122 volunteers aged 65 y and over with patients confirmed to have SARS-CoV-2 infection according to the reverse transcriptase-polymerase chain reaction (RT-PCR) test, who presented to the emergency department between March 1, 2020, and May 1, 2020. Demographic data, comorbidities, vital parameters, hematological parameters, and MEWS, REMS, and RAPS values of the patients were recorded prospectively.

RESULTS

Among the 122 patients included in the study, the median age was 71 (25th-75th quartile: 67-79) y. The rate of 30-d mortality was 10.7% for the study cohort. The area under the receiver operating characteristic curve values for MEWS, RAPS, and REMS were 0.512 (95% confidence interval [CI]: 0.420-0.604; P = 0.910), 0.500 (95% CI: 0.408-0.592; P = 0.996), and 0.675 (95% CI: 0.585-0.757; P = 0.014), respectively. The odds ratios of MEWS (≥2), RAPS (>2), and REMS (>5) for 30-d mortality were 0.374 (95% CI: 0.089-1.568; P = 0.179), 1.696 (95% CI: 0.090-31.815; P = 0.724), and 1.008 (95% CI: 0.257-3.948; P = 0.991), respectively.

CONCLUSIONS

REMS, RAPS, and MEWS do not seem to be useful in predicting 30-d mortality in geriatric patients with SARS-CoV-2 infection presenting to the emergency department.

Utility of early warning scores to predict mortality in COVID-19 patients: A retrospective observational study

Background:

Coronavirus disease 2019 (COVID19) has evolved as a global pandemic. The patients with COVID-19 infection can present as mild, moderate, and severe disease forms. The reported mortality of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection is around 6.6%, which is lower than that of SARS-CoV and (middle east respiratory syndrome CoV). However, the fatality rate of COVID-19 infection is higher in the geriatric age group and in patients with multiple co-morbidities. The study aimed to evaluate the utility of early warning scores (EWS) to predict mortality in patients with moderate to severe COVID-19 infection.

Methods:

This retrospective study was carried out in a tertiary care institute of Uttarakhand. Demographic and clinical data of the admitted patients with moderate-to-severe COVID-19 infection were collected from the hospital record section and utilized to calculate the EWS-National early warning score (NEWS), modified early warning score (MEWS), Rapid Acute Physiology Score (RAPS), rapid emergency medicine score (REMS), and worthing physiological scoring system (WPS).

Results:

The area under the curve for NEWS, MEWS, RAPS, REMS, and WPS was 0.813 (95% confidence interval [CI]; 0.769–0.858), 0.770 (95% CI; 0.717–0.822), 0.755 (95% CI; 0.705–0.805), 0.892 (95% CI; 0.859–0.924), and 0.892 (95% CI; 0.86–0.924), respectively.

Conclusion:

The EWS at triage can be used for early assessment of severity as well as predict mortality in patients with COVID-19 patients.