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Differences in the Clinical Severity Scores of Hospitalized Covid-19 Patients Across Different Phases of an Epidemic Wave in Iran: A Secondary Analysis Publisher



L Mounesan LEILA ; S Gharibzadeh SAFOORA ; M Parsaeian MAHBOUBEH ; Mm Gouya Mohamamd MEHDI ; S Eybpoosh SANA ; A Hosseini A ; L Haghjou LEILA ; Aa Haghdoost Aliakbar AKBAR ; Es Mostafavi Ehasn S
Authors

Source: Medical Journal of the Islamic Republic of Iran Published:2024


Abstract

Background: To reduce the clinical burden of COVID-19, healthcare providers, and policymakers need a clear understanding of the illness severity during epidemic waves. This study aimed to identify the clinical severity of patients with COVID-19 during different stages of an epidemic wave (pre-peak, peak, post-peak) in four provinces in Iran. Methods: We conducted a secondary analysis of the data on COVID-19 patients admitted to hospitals (25, 382 cases), which were recorded in the Medical Care Monitoring Center. Data included adult patients (≥18 years) who were hospitalized due to COVID-19 infection, confirmed by a positive SARS-CoV-2 RT-PCR test. No exclusion criteria were applied. A pairwise comparison method was used to evaluate clinical severity. Then, based on univariable and multivariable linear regression models, the severity scores of patients were compared during various stages of an epidemic wave. Results: The findings showed that the level of severity of the disease was higher during and after the peak in the total population. The means (SD) of severity scores were 0.16 (0.25), 0.18 (0.26), and 0.19 (0.26) before, during and after the peak, respectively. Besides, age and the underlying disease had a positive and significant relationship with disease severity. Conclusion: During the middle and late phases of the COVID-19 epidemic wave, hospitals are seeing patients with more severe illnesses than in the early stages. Enhancing hospital preparedness is essential to avert excess deaths and critical cases. Moreover, it is important to maintain ongoing monitoring of clinical symptoms during the recovery phase to support individual patients, guide public health policy, and enhance scientific understanding of epidemic recovery processes. © 2024 Elsevier B.V., All rights reserved.
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