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. 2023 Jul 19:16:3053-3065.
doi: 10.2147/IJGM.S419206. eCollection 2023.

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

Irina-Maria Popescu  1 , Madalin-Marius Margan  2 , Mariana Anghel  1 , Alexandra Mocanu  3 , Sorina Maria Denisa Laitin  1 , Roxana Margan  4 , Ionut Dragos Capraru  1 , Alexandra-Andreea Tene  5 , Emanuela-Georgiana Gal-Nadasan  6 , Daniela Cirnatu  5   7 , Gratiana Nicoleta Chicin  5   8 , Cristian Oancea  9 , Andrei Anghel  10
Affiliations

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

Irina-Maria Popescu et al. Int J Gen Med. .

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.

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Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Receiver operating characteristic (ROC) curves illustrating the performance of proposed predictive models in distinguishing high-risk and low-risk patients within the study group dataset.
Figure 2
Figure 2
Receiver operating characteristic (ROC) curves illustrating the performance of proposed predictive models in distinguishing high-risk and low-risk patients within the extended group dataset.
See this image and copyright information in PMC

References

    1. WHO Coronavirus (COVID-19) Dashboard - Overview. 2023. Available from: https://covid19.who.int/. Accessed May 18, 2023.
    1. Kasapçopur Ö. Science and pseudoscience during the COVID-19 pandemic. Turk Pediatri Ars. 2020;55(4):335–336. doi:10.14744/TurkPediatriArs.2020.35902 - DOI - PMC - PubMed
    1. Gao YD, Ding M, Dong X, et al. Risk factors for severe and critically ill COVID-19 patients: a review. Allergy. 2021;76(2):428–455. doi:10.1111/all.14657 - DOI - PubMed
    1. Carpenter CR, Mudd PA, West CP, Wilber E, Wilber ST. Diagnosing COVID-19 in the Emergency Department: a Scoping Review of Clinical Examinations, Laboratory Tests, Imaging Accuracy, and Biases. Acad Emerg Med. 2020;27(8):653–670. doi:10.1111/acem.14048 - DOI - PMC - PubMed
    1. Laza R, Lazureanu VE, Musta VF, et al. COVID-19 Independent Risk Factors for Unfavorable Disease Progression: a Cross-Sectional Study from Romania. Int J Gen Med. 2022;15:2025–2036. doi:10.2147/IJGM.S350920 - DOI