Developing Prediction Models for COVID-19 Outcomes: A Valuable Tool for Resource-Limited Hospitals

Irina-Maria Popescu; Madalin-Marius Margan; Mariana Anghel; Alexandra Mocanu; Sorina Maria Denisa Laitin; Roxana Margan; Ionut Dragos Capraru; Alexandra-Andreea Tene; Emanuela-Georgiana Gal-Nadasan; Daniela Cirnatu; Gratiana Nicoleta Chicin; Cristian Oancea; Andrei Anghel

doi:10.2147/IJGM.S419206

Developing Prediction Models for COVID-19 Outcomes: A Valuable Tool for Resource-Limited Hospitals

Int J Gen Med. 2023 Jul 19:16:3053-3065. doi: 10.2147/IJGM.S419206. eCollection 2023.

Authors

Affiliations

¹ Department of Infectious Diseases, Discipline of Epidemiology, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.
² Department of Functional Sciences, Discipline of Public Health, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.
³ Department of Infectious Diseases, Discipline of Infectious Diseases, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.
⁴ Department of Functional Sciences, Discipline of Physiology, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.
⁵ Regional Center of Public Health Timisoara, Timisoara, Romania.
⁶ Department of Balneology, Medical Rehabilitation and Rheumatology, Discipline of Medical Rehabilitation, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.
⁷ Department of Medicine, "Vasile Goldis" Western University, Faculty of Medicine, Arad, Romania.
⁸ Department of Epidemiology, Infectious Diseases and Preventive Medicine, "Vasile Goldis" Western University, Faculty of Medicine, Arad, Romania.
⁹ Center for Research and Innovation in Precision Medicine of Respiratory Disease, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.
¹⁰ Department of Biochemistry and Pharmacology, Discipline of Biochemistry, "Victor Babes" University of Medicine and Pharmacy, Timisoara, Romania.

Abstract

Purpose: Coronavirus disease is a global pandemic with millions of confirmed cases and hundreds of thousands of deaths worldwide that continues to create a significant burden on the healthcare systems. The aim of this study was to determine the patient clinical and paraclinical profiles that associate with COVID-19 unfavourable outcome and generate a prediction model that could separate between high-risk and low-risk groups.

Patients and methods: The present study is a multivariate observational retrospective study. A total of 483 patients, residents of the municipality of Timișoara, the biggest city in the Western Region of Romania, were included in the study group that was further divided into 3 sub-groups in accordance with the disease severity form.

Results: Increased age (cOR=1.09, 95% CI: 1.06-1.11, p<0.001), cardiovascular diseases (cOR=3.37, 95% CI: 1.96-6.08, p<0.001), renal disease (cOR=4.26, 95% CI: 2.13-8.52, p<0.001), and neurological disorder (cOR=5.46, 95% CI: 2.71-11.01, p<0.001) were all independently significantly correlated with an unfavourable outcome in the study group. The severe form increases the risk of an unfavourable outcome 19.59 times (95% CI: 11.57-34.10, p<0.001), while older age remains an independent risk factor even when disease severity is included in the statistical model. An unfavourable outcome was positively associated with increased values for the following paraclinical parameters: white blood count (WBC; cOR=1.10, 95% CI: 1.05-1.15, p<0.001), absolute neutrophil count (ANC; cOR=1.15, 95% CI: 1.09-1.21, p<0.001) and C-reactive protein (CRP; cOR=1.007, 95% CI: 1.004-1.009, p<0.001). The best prediction model including age, ANC and CRP achieved a receiver operating characteristic (ROC) curve with the area under the curve (AUC) = 0.845 (95% CI: 0.813-0.877, p<0.001); cut-off value = 0.12; sensitivity = 72.3%; specificity = 83.9%.

Conclusion: This model and risk profiling may contribute to a more precise allocation of limited healthcare resources in a clinical setup and can guide the development of strategies for disease management.

Keywords: ANC; CRP; risk profiling; unfavourable outcome.