Effect of the chronic medication use on outcome measures of hospitalized COVID-19 patients: Evidence from big data

Mohammad-Reza Malekpour; Mohsen Abbasi-Kangevari; Ali Shojaee; Sahar Saeedi Moghaddam; Seyyed-Hadi Ghamari; Mohammad-Mahdi Rashidi; Alireza Namazi Shabestari; Mohammad Effatpanah; Mohammadmehdi Nasehi; Mehdi Rezaei; Farshad Farzadfar

doi:10.3389/fpubh.2023.1061307

Effect of the chronic medication use on outcome measures of hospitalized COVID-19 patients: Evidence from big data

Front Public Health. 2023 Feb 24:11:1061307. doi: 10.3389/fpubh.2023.1061307. eCollection 2023.

Authors

Mohammad-Reza Malekpour¹, Mohsen Abbasi-Kangevari¹, Ali Shojaee², Sahar Saeedi Moghaddam^{1

3}, Seyyed-Hadi Ghamari¹, Mohammad-Mahdi Rashidi¹, Alireza Namazi Shabestari^{4

5}, Mohammad Effatpanah^{5

6}, Mohammadmehdi Nasehi^{5

7}, Mehdi Rezaei^{5

8}, Farshad Farzadfar^{1

9}

Affiliations

¹ Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
² Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
³ Kiel Institute for the World Economy, Kiel, Germany.
⁴ Department of Geriatric Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
⁵ National Center for Health Insurance Research, Iran Health Insurance Organization, Tehran, Iran.
⁶ Department of Pediatrics, Imam Khomeini Hospital Complex, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
⁷ Pediatric Neurology Department, Mofid Children Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁸ Department of Orthopedics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
⁹ Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Abstract

Background: Concerns about the role of chronically used medications in the clinical outcomes of the coronavirus disease 2019 (COVID-19) have remarkable potential for the breakdown of non-communicable diseases (NCDs) management by imposing ambivalence toward medication continuation. This study aimed to investigate the association of single or combinations of chronically used medications in NCDs with clinical outcomes of COVID-19.

Methods: This retrospective study was conducted on the intersection of two databases, the Iranian COVID-19 registry and Iran Health Insurance Organization. The primary outcome was death due to COVID-19 hospitalization, and secondary outcomes included length of hospital stay, Intensive Care Unit (ICU) admission, and ventilation therapy. The Anatomical Therapeutic Chemical (ATC) classification system was used for medication grouping. The frequent pattern growth algorithm was utilized to investigate the effect of medication combinations on COVID-19 outcomes.

Findings: Aspirin with chronic use in 10.8% of hospitalized COVID-19 patients was the most frequently used medication, followed by Atorvastatin (9.2%) and Losartan (8.0%). Adrenergics in combination with corticosteroids inhalants (ACIs) with an odds ratio (OR) of 0.79 (95% confidence interval: 0.68-0.92) were the most associated medications with less chance of ventilation therapy. Oxicams had the least OR of 0.80 (0.73-0.87) for COVID-19 death, followed by ACIs [0.85 (0.77-0.95)] and Biguanides [0.86 (0.82-0.91)].

Conclusion: The chronic use of most frequently used medications for NCDs management was not associated with poor COVID-19 outcomes. Thus, when indicated, physicians need to discourage patients with NCDs from discontinuing their medications for fear of possible adverse effects on COVID-19 prognosis.

Keywords: Anatomical Therapeutic Chemical; COVID-19; big data; frequent pattern mining; non-communicable diseases; pandemic.

MeSH terms

Big Data
COVID-19*
Humans
Iran
Outcome Assessment, Health Care
Retrospective Studies
SARS-CoV-2