Prognostic value of three rapid scoring scales and combined predictors for the assessment of patients with coronavirus disease 2019

Comparison of eight prehospital early warning scores in life-threatening acute respiratory distress: a prospective, observational, multicentre, ambulance-based, external validation study

BACKGROUND

A myriad of early warning scores (EWSs) exist, yet there is a need to identify the most clinically valid score to be used in prehospital respiratory assessments to estimate short-term and midterm mortality, intensive-care unit admission, and airway management in life-threatening acute respiratory distress.

METHODS

This is a prospective, observational, multicentre, ambulance-based, external validation study performed in 44 ambulance services and four hospitals across three Spanish provinces (ie, Salamanca, Segovia, and Valladolid). We identified adults (ie, those aged 18 years and older) discharged to the emergency department with suspected acute respiratory distress. The primary outcome was 2-day all-cause in-hospital mortality, for all the patients or according to prehospital respiratory conditions, including dyspnoea, chronic obstructive pulmonary disease (COPD), COVID-19, other infections, and other conditions (asthma exacerbation, haemoptysis, and bronchoaspirations). 30-day mortality, intensive-care unit admission, and invasive and non-invasive mechanical ventilation were secondary outcomes. Eight EWSs, namely, the National Early Warning Score 2, the Modified Rapid Emergency Medicine Score, the Rapid Acute Physiology Score, the Quick Sequential Organ Failure Assessment Score, the CURB-65 Severity Score for Community-Acquired Pneumonia, the BAP-65 Score for Acute Exacerbation of COPD, the Quick COVID-19 Severity Index, and the Modified Sequential Organ Failure Assessment (mSOFA), were explored to determine their predictive validity through calibration, clinical net benefit as determined through decision curve analysis, and discrimination analysis (area under the curve of the receiver operating characteristic [AUROC], compared with Delong's test).

FINDINGS

Between Jan 1, 2020, and Nov 31, 2022, 902 patients were enrolled. The global 2-day mortality rate was 87 (10%); in proportion to various respiratory conditions, the rates were 35 (40%) for dyspnoea, nine (10%) for COPD, 13 (15%) for COVID-19, 28 (32%) for other infections, and two (2%) for others conditions. mSOFA showed the best calibration, a higher net benefit, and the best discrimination (AUROC 0·911, 95% CI 0·86-0·95) for predicting 2-day mortality, and its discrimination was statistically significantly more accurate (p<0·0001) compared with the other scores. The performance of mSOFA for predicting 2-day mortality was higher than the other scores when considering the prehospital respiratory conditions, and was also higher for the secondary outcomes, except for non-invasive mechanical ventilation.

INTERPRETATION

Our results showed that mSOFA outperformed other EWSs. The inclusion of mSOFA in prehospital decision making will entail a quick identification of patients in acute respiratory distress at high risk of deterioration, allowing prioritisation of resources and patient care.

FUNDING

Gerencia Regional de Salud, Public Health System of Castilla y León (GRS Spain).

TRANSLATION

For the Spanish translation of the abstract see Supplementary Materials section.

Modified Early Warning Score: Clinical Deterioration of Mexican Patients Hospitalized with COVID-19 and Chronic Disease

The objective was to evaluate the Modified Early Warning Score in patients hospitalized for COVID-19 plus chronic disease.

METHODS

Retrospective observational study, 430 hospitalized patients with COVID-19 and chronic disease. Instrument, Modified Early Warning Score (MEWS). Data analysis, with Cox and logistic regression, to predict survival and risk.

RESULTS

Of 430 patients, 58.6% survived, and 41.4% did not. The risk was: low 53.5%, medium 23.7%, and high 22.8%. The MEWS score was similar between survivors 3.02, p 0.373 (95% CI: -0.225-0.597) and non-survivors 3.20 (95% CI: -0.224-0.597). There is a linear relationship between MEWS and mortality risk R 0.920, ANOVA 0.000, constant 4.713, and coefficient 4.406. The Cox Regression p 0.011, with a risk of deterioration of 0.325, with a positive coefficient, the higher the risk, the higher the mortality, while the invasive mechanical ventilation coefficient was negative -0.757. By providing oxygen and ventilation, mortality is lower.

CONCLUSIONS

The predictive value of the modified early warning score in patients hospitalized for COVID-19 and chronic disease is not predictive with the MEWS scale. Additional assessment is required to prevent complications, especially when patients are assessed as low-risk.

Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department

Background

The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological score (WPS), early warning score (EWS), rapid acute physiology score (RAPS), rapid emergency medicine score (REMS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA).

Materials and methods

A cohort study was conducted using data obtained from electronic medical records of 6,429 confirmed SARS-COV2 patients presenting to the ED. Logistic regression models were fitted on the original severity-of-illness scores to assess the models' performance using the Area Under the Curve for ROC (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models' performance. Bootstrap samples with multiple imputations were used for internal validation.

Results

The mean age of the patients was 64 years (IQR:50-76) and 57.5% were male. The WPS, REMS, and NEWS models had AUROC of 0.714, 0.705, and 0.701, respectively. The poorest performance was observed in the RAPS model, with an AUROC of 0.601. The BS for the NEWS, qSOFA, EWS, WPS, RAPS, and REMS was 0.18, 0.09, 0.03, 0.14, 0.15, and 0.11 respectively. Excellent calibration was obtained for the NEWS, while the other models had proper calibration.

Conclusion

The WPS, REMS, and NEWS have a fair discriminatory performance and may assist in risk stratification for SARS-COV2 patients presenting to the ED. Generally, underlying diseases and most vital signs are positively associated with mortality and were different between the survivors and non-survivors.

How to cite this article

Rahmatinejad Z, Hoseini B, Reihani H, Hanna AA, Pourmand A, Tabatabaei SM, et al. Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department. Indian J Crit Care Med 2023;27(6):416-425.

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.

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.

Neurological Prognostic Factors in Hospitalized Patients with COVID-19

We aimed to search whether neurological symptoms or signs (NSS) and the MEWS (Modified Early Warning Score) score were associated with in-hospital mortality or oxygen requirement during the first 14 days of hospitalization in COVID-19 patients recruited at the University Hospital in Krakow, Poland. The detailed clinical questionnaires on twenty NSS were either filled out by patients prospectively or retrospectively assessed by neurologists based on daily medical records. NSS were considered high or low-risk if they were associated with increased or decreased mortality in the univariable analysis. This cohort study included 349 patients with COVID-19 (median age 64, interquartile range (51–77), women 54.72%). The presence of high-risk NSS (decreased level of consciousness, delirium, seizures, and symptoms of stroke or transient ischemic attack) or its combination with the absence of low-risk NSS (headache, dizziness, decreased mood, and fatigue) increased the risk of in-hospital mortality in SARS-CoV-2 infection 3.13 and 7.67-fold, respectively. The presence of low-risk NSS decreased the risk of in-hospital mortality in COVID-19 patients more than 6-fold. Death in patients with SARS-CoV-2 infection, apart from NSS, was predicted by older age, neoplasm, and higher MEWS scores on admission. High-risk NSS or their combination with the absence of low-risk NSS increased the risk of oxygen requirement during hospitalization in COVID-19 patients 4.48 and 1.86-fold, respectively. Independent predictors of oxygen therapy during hospitalization in patients with SARS-CoV-2 infection were also older age, male sex, neoplasm, and higher MEWS score on admission.

Multiple Approaches at Admission Based on Lung Ultrasound and Biomarkers Improves Risk Identification in COVID-19 Patients

BACKGROUND

Risk stratification of COVID-19 patients is fundamental to improving prognosis and selecting the right treatment. We hypothesized that a combination of lung ultrasound (LUZ-score), biomarkers (sST2), and clinical models (PANDEMYC score) could be useful to improve risk stratification.

METHODS

This was a prospective cohort study designed to analyze the prognostic value of lung ultrasound, sST2, and PANDEMYC score in COVID-19 patients. The primary endpoint was in-hospital death and/or admission to the intensive care unit. The total length of hospital stay, increase of oxygen flow, or escalated medical treatment during the first 72 h were secondary endpoints.

RESULTS

a total of 144 patients were included; the mean age was 57.5 ± 12.78 years. The median PANDEMYC score was 243 (52), the median LUZ-score was 21 (10), and the median sST2 was 53.1 ng/mL (30.9). Soluble ST2 showed the best predictive capacity for the primary endpoint (AUC = 0.764 (0.658-0.871); p = 0.001), towards the PANDEMYC score (AUC = 0.762 (0.655-0.870); p = 0.001) and LUZ-score (AUC = 0.749 (0.596-0.901); p = 0.002). Taken together, these three tools significantly improved the risk capacity (AUC = 0.840 (0.727-0.953); p ≤ 0.001).

CONCLUSIONS

The PANDEMYC score, lung ultrasound, and sST2 concentrations upon admission for COVID-19 are independent predictors of intra-hospital death and/or the need for admission to the ICU for mechanical ventilation. The combination of these predictive tools improves the predictive power compared to each one separately. The use of decision trees, based on multivariate models, could be useful in clinical practice.

Prognostic value of three rapid scoring scales and combined predictors for the assessment of patients with coronavirus disease 2019

Aim

To explore the factors affecting mortality in patients with COVID‐19 and to verify the predictive value of the three rapid scoring scales MEWS, RAPS and REMS.

Design

Cross‐sectional observational study.

Methods

Kaplan–Meier and Cox survival analyses were performed to identify the risk factors associated with COVID‐19‐related death. A ROC curve analysis was used to evaluate the abilities of the three scoring scales to predict the prognosis of COVID‐19 patients.

Results

Age, low blood oxygen saturation level and decreased lymphocyte count were the high risk factors for COVID‐19‐related mortality. The analysis of the abilities of the three scales to predict the prognosis of COVID‐19 patients: The AUC of 0.641 for the RAPS (p = .065). The MEWS (AUC = 0.705, p = .007), compared with RAPS, the NRI was 0.371(p = .03), and the IDI = 0.092 (p = .046); The REMS (AUC = 0.841, p < .001), compared with MEWS, the NRI was 0.227(p = .12), and the IDI=0.09(p = .047); The Combining Predictor (AUC = 0.878, p < .001), compared with REMS, the NRI was 0.25(p = .113), and the IDI=0.02(p = .598).

Conclusion

Patients with an old age, low blood oxygen saturation level and decreased lymphocyte count were at a high risk of COVID‐19‐related mortality. Moreover, our analysis revealed that the REMS had a better prognostic ability than the MEWS and RAPS when applied to COVID‐19 patients. Our findings suggest that the REMS can be used as a rapid scoring tool for the early assessment of COVID‐19 severity.