Non-COVID-19 hospitalization and mortality during the COVID-19 pandemic in Iran: a longitudinal assessment of 41 million people in 2019-2022.
Autor: | Razimoghadam M; Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran., Yaseri M; Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran., Rezaee M; Department of Orthopedics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.; National Center for Health Insurance Research, Tehran, Iran., Fazaeli A; Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran., Daroudi R; Department of Health Management, Policy and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. rdaroudi@sina.tums.ac.ir. |
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Jazyk: | angličtina |
Zdroj: | BMC public health [BMC Public Health] 2024 Feb 05; Vol. 24 (1), pp. 380. Date of Electronic Publication: 2024 Feb 05. |
DOI: | 10.1186/s12889-024-17819-0 |
Abstrakt: | Background: During a COVID-19 pandemic, it is imperative to investigate the outcomes of all non-COVID-19 diseases. This study determines hospital admissions and mortality rates related to non-COVID-19 diseases during the COVID-19 pandemic among 41 million Iranians. Method: This nationwide retrospective study used data from the Iran Health Insurance Organization. From September 23, 2019, to Feb 19, 2022, there were four study periods: pre-pandemic (Sept 23-Feb 19, 2020), first peak (Mar 20-Apr 19, 2020), first year (Feb 20, 2020-Feb 18, 2021), and the second year (Feb 19, 2021-Feb 19, 2022) following the pandemic. Cause-specific hospital admission and in-hospital mortality are the main outcomes analyzed based on age and sex. Negative binomial regression was used to estimate the monthly adjusted Incidence Rate Ratio (IRR) to compare hospital admission rates in aggregated data. A logistic regression was used to estimate the monthly adjusted in-hospital mortality Odds Ratio (OR) for different pandemic periods. Results: During the study there were 6,522,114 non-COVID-19 hospital admissions and 139,679 deaths. Prior to the COVID-19 outbreak, the standardized hospital admission rate per million person-month was 7115.19, which decreased to 2856.35 during the first peak (IRR 0.40, [0.25-0.64]). In-hospital mortality also increased from 20.20 to 31.99 (OR 2.05, [1.97-2.13]). All age and sex groups had decreased admission rates, except for females at productive ages. Two years after the COVID-19 outbreak, the non-COVID-19 hospital admission rate (IRR 1.25, [1.13-1.40]) and mortality rate (OR 1.05, [1.04-1.07]) increased compared to the rates before the pandemic. The respiratory disease admission rate decreased in the first (IRR 0.23, [0.17-0.31]) and second years (IRR 0.35, [0.26-0.47] compared to the rate before the pandemic. There was a significant reduction in hospitalizations for pneumonia (IRR 0.30, [0.21-0.42]), influenza (IRR 0.04, [0.03-0.06]) and COPD (IRR 0.39, [0.23-0.65]) during the second year. There was a significant and continuous rise in the hematological admission rate during the study, reaching 186.99 per million person-month in the second year, reflecting an IRR of 2.84 [2.42-3.33] compared to the pre-pandemic period. The mortality rates of mental disorders (OR 2.15, [1.65-2.78]) and musculoskeletal (OR 1.48, [1.20-1.82), nervous system (OR 1.42, [1.26-1.60]), metabolic (OR 1.99, [1.80-2.19]) and circulatory diseases (OR 1.35, [1.31-1.39]) increased in the second year compare to pre-pandemic. Myocardial infarction (OR 1.33, [1.19-1.49]), heart failure (OR 1.59, [1.35-1.87]) and stroke (OR 1.35, [1.24-1.47]) showed an increase in mortality rates without changes in hospitalization. Conclusions: In the era of COVID-19, the changes seem to have had a long-term effect on non-COVID-19 diseases. Countries should prepare for similar crises in the future to ensure medical services are not suspended. (© 2024. The Author(s).) |
Databáze: | MEDLINE |
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