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Results of multivariate analyses.

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Results_of_multivariate_analyses_/23322242
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Introduction Worldwide, the COVID-19 pandemic has been associated with an overall drop in acute coronary syndrome (ACS) hospitalizations. Additionally, there is a well-known association between ACS and socioeconomic status. This study aims to assess the COVID-19 effect on ACS admissions in France during the first national lockdown and investigate the factors associated with its spatial heterogeneity. Materials and methods In this retrospective study, we used the French hospital discharge database (PMSI) to estimate ACS admission rates in all public and private hospitals in 2019 and 2020. A negative binomial regression explored the nationwide change in ACS admissions during lockdown compared with 2019. A multivariate analysis explored the factors associated with the ACS admission incidence rate ratio (IRR, 2020 incidence rate/2019 incidence rate) variation at the county level. Results We found a significant but geographically heterogeneous nationwide reduction in ACS admissions during lockdown (IRR 0·70 [0·64–0·76]). After adjustment for cumulative COVID-19 admissions and the ageing index, a higher share of people on short-term working arrangements during lockdown at the county level was associated with a lower IRR, while a higher share of individuals with a high school degree and a higher density of acute care beds were associated with a higher ratio. Conclusions During the first national lockdown, there was an overall decrease in ACS admissions. Local provision of inpatient care and socioeconomic determinants linked to occupation were independently associated with the variation in hospitalizations.
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2023-06-07
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