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ORIGINAL RESEARCH article

Front. Med.

Sec. Intensive Care Medicine and Anesthesiology

Volume 12 - 2025 | doi: 10.3389/fmed.2025.1553189

Performance of clinical risk assessment tools to predict outcomes among patients assessed at the emergency department with coronavirus disease 2019 infection

Provisionally accepted
Bushra  KurbanBushra Kurban1Adnan  AghaAdnan Agha1Lutfi  KurbanLutfi Kurban2Virgie  GuyVirgie Guy1Javed  YasinJaved Yasin1Fayez  AlshamsiFayez Alshamsi1Mohamed  IsmailMohamed Ismail1,3Omran  BakoushOmran Bakoush1*
  • 1Department of Internal Medicine, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
  • 2Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates
  • 3Department of Endocrinology, Tawam Hospital, Al Ain, United Arab Emirates

The final, formatted version of the article will be published soon.

The coronavirus disease 2019 (COVID-19) pandemic resulted in significant global mortality and morbidity, with emerging mutant strains continuing to potentially precipitate severe respiratory illness. Two clinical assessment tools, namely, the COVID-19 Risk of Complications Score (CRS), based on 13 comorbidities, and the ALKA (age, lactate dehydrogenase, kidney function, and albumin) score have been developed to predict disease severity among patients who are symptomatic at presentation. This study aimed to compare the performance of these two risk-scoring systems in predicting hospital admission, critical illness, and mortality. Methods: This retrospective study included 368 patients diagnosed with COVID-19 at SEHA hospitals in Al Ain over a six-month period. The CRS and ALKA scores were calculated to predict hospital admission, critical illness, and mortality. Predictive ability was assessed using receiver operating characteristic (ROC) curve analysis. Odds ratios (ORs) were calculated to assess the risk of hospital admission, critical illness, and mortality. Results: The mean age of the patients was 51 ± 19.42 years, and 145 (39.4%) of them were male. Among the patients, 162 required inpatient care, 13 required invasive ventilation, and the mortality rate was 4.9% (eight patients). ROC analysis revealed that ALKA outperformed CRS in predicting hospital admission (ALKA area under the curve [AUC] 0.79 vs. CRS AUC 0.71), critical illness (ALKA AUC 0.76 vs. CRS AUC 0.67), and mortality (ALKA AUC 0.96 vs. CRS AUC 0.82). The OR for ALKA outperformed CRS in predicting hospital admission (ALKA 3.12 vs. CRS 1.12), critical illness (ALKA 2.9 vs. CRS 2.01), and mortality (ALKA 6.25 vs. CRS 1.1). Conclusion: Our study demonstrated that ALKA score outperforms CRS in predicting hospital admission, critical illness, and mortality among patients with symptomatic COVID-19 at initial presentation. Further external validation of both tools is required to assess their effectiveness in different healthcare settings.

Keywords: Clinical decision, Comorbidity, COVID-19, Critical Illness, Hospitalization, Mortality, outpatient, Risk Assessment

Received: 03 Jan 2025; Accepted: 04 Aug 2025.

Copyright: © 2025 Kurban, Agha, Kurban, Guy, Yasin, Alshamsi, Ismail and Bakoush. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Omran Bakoush, Department of Internal Medicine, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates

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