Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study.
Grosso, Francesca M
BMC Infect Dis
Springer Science and Business Media LLC
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Presanis, A., Kunzmann, K., Grosso, F. M., Jackson, C., Corbella, A., Grasselli, G., Salmoiraghi, M., et al. (2021). Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study.. BMC Infect Dis, 21 (1) https://doi.org/10.1186/s12879-021-06750-z
BACKGROUND: Understanding the risk factors associated with hospital burden of COVID-19 is crucial for healthcare planning for any future waves of infection. METHODS: An observational cohort study is performed, using data on all PCR-confirmed cases of COVID-19 in Regione Lombardia, Italy, during the first wave of infection from February-June 2020. A multi-state modelling approach is used to simultaneously estimate risks of progression through hospital to final outcomes of either death or discharge, by pathway (via critical care or not) and the times to final events (lengths of stay). Logistic and time-to-event regressions are used to quantify the association of patient and population characteristics with the risks of hospital outcomes and lengths of stay respectively. RESULTS: Risks of severe outcomes such as ICU admission and mortality have decreased with month of admission (for example, the odds ratio of ICU admission in June vs March is 0.247 [0.120-0.508]) and increased with age (odds ratio of ICU admission in 45-65 vs 65 + age group is 0.286 [0.201-0.406]). Care home residents aged 65 + are associated with increased risk of hospital mortality and decreased risk of ICU admission. Being a healthcare worker appears to have a protective association with mortality risk (odds ratio of ICU mortality is 0.254 [0.143-0.453] relative to non-healthcare workers) and length of stay. Lengths of stay decrease with month of admission for survivors, but do not appear to vary with month for non-survivors. CONCLUSIONS: Improvements in clinical knowledge, treatment, patient and hospital management and public health surveillance, together with the waning of the first wave after the first lockdown, are hypothesised to have contributed to the reduced risks and lengths of stay over time.
Mixture model, Critical Care, Multi-state Model, Covid-19, Hospital-fatality Risk, Humans, Length of Stay, Risk Factors, Cohort Studies, Communicable Disease Control, Intensive Care Units, Hospitals, COVID-19, SARS-CoV-2
UK Research and Innovation (UKRI-MRC/NIHR/DHSC COVID-19 rapid response call MC_PC_19074)
Medical Research Council (MC_UU_00002/11, MC_UU_00002/10)
External DOI: https://doi.org/10.1186/s12879-021-06750-z
This record's URL: https://www.repository.cam.ac.uk/handle/1810/330482
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/