Investigating the Association between COVID-19 Prognosis and Demographic and Clinical Features, Underlying Diseases, and Drug and Supplement Use in Patients Hospitalized in Zabol, Iran: A Single-Center Retrospective Study

نویسندگان

1 Department of Pharmacology and Toxicology, Faculty of Pharmacy, Zabol University of Medical Sciences, Zabol, Iran

2 Pharmacology Research Center, Zahedan University of Medical Sciences, Zahedan, Iran

3 Department of Exercise Physiology, Faculty of Physical Education and Sport Sciences, Central Tehran Branch, Islamic Azad University, Tehran, Iran

4 Department of Epidemiology & Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

5 Department of Pharmacology and Toxicology, Faculty of Pharmacy, Zabol University of Medical Sciences, Zabol, Iran

6 Pharmacology Research Center, Zahedan University of Medical Sciences, Zahedan, Iran

7 Pharmacology Research Center, Zahedan University of Medical Sciences, Zahedan, Iran

doi
10.61186/iem.9.2.167
چکیده

Backgrounds: The primary goal of this study was to identify the potential association between COVID-19 prognosis and demographic and clinical features, underlying diseases, and drug and supplement use in patients admitted to Amir al-Momenin hospital in Zabol. Materials & Methods: This retrospective study surveyed the electronic health records of 848 COVID-19 patients hospitalized in a tertiary referral hospital in southeastern Iran from the beginning of the COVID-19 outbreak until the end of February 2021. Univariate and multiple analytical tests including unconditional and penalized logistic regressions were used for statistical analysis. Findings: Out of a total of 848 patients, 371 (43.75%) patients were female, and 477 (56.25%) patients were male. Age, underlying pulmonary and cardiovascular diseases, and loss of consciousness predicted a higher mortality rate. On the contrary, a negative chest X-ray was associated with a lower risk of death. Conclusion: Identifying predisposing factors of mortality in COVID-19 patients will help physicians provide more intensive care to those at higher risk of death by classifying patients based on risk factors and underlying diseases.

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