Decreasing hospital burden of COVID-19 during the first wave in Regione Lombardia: an emergency measures context.


Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
03 09 2021
Historique:
received: 01 03 2021
accepted: 12 08 2021
entrez: 4 9 2021
pubmed: 5 9 2021
medline: 9 9 2021
Statut: epublish

Résumé

The aim of this study is to quantify the hospital burden of COVID-19 during the first wave and how it changed over calendar time; to interpret the results in light of the emergency measures introduced to manage the strain on secondary healthcare. This is a cohort study of hospitalised confirmed cases of COVID-19 admitted from February-June 2020 and followed up till 17th July 2020, analysed using a mixture multi-state model. All hospital patients with confirmed COVID-19 disease in Regione Lombardia were involved, admitted from February-June 2020, with non-missing hospital of admission and non-missing admission date. The cohort consists of 40,550 patients hospitalised during the first wave. These patients had a median age of 69 (interquartile range 56-80) and were more likely to be men (60%) than women (40%). The hospital-fatality risk, averaged over all pathways through hospital, was 27.5% (95% CI 27.1-28.0%); and steadily decreased from 34.6% (32.5-36.6%) in February to 7.6% (6.3-10.6%) in June. Among surviving patients, median length of stay in hospital was 11.8 (11.6-12.3) days, compared to 8.1 (7.8-8.5) days in non-survivors. Averaged over final outcomes, median length of stay in hospital decreased from 21.4 (20.5-22.8) days in February to 5.2 (4.7-5.8) days in June. The hospital burden, in terms of both risks of poor outcomes and lengths of stay in hospital, has been demonstrated to have decreased over the months of the first wave, perhaps reflecting improved treatment and management of COVID-19 cases, as well as reduced burden as the first wave waned. The quantified burden allows for planning of hospital beds needed for current and future waves of SARS-CoV-2 i.

Sections du résumé

BACKGROUND
The aim of this study is to quantify the hospital burden of COVID-19 during the first wave and how it changed over calendar time; to interpret the results in light of the emergency measures introduced to manage the strain on secondary healthcare.
METHODS
This is a cohort study of hospitalised confirmed cases of COVID-19 admitted from February-June 2020 and followed up till 17th July 2020, analysed using a mixture multi-state model. All hospital patients with confirmed COVID-19 disease in Regione Lombardia were involved, admitted from February-June 2020, with non-missing hospital of admission and non-missing admission date.
RESULTS
The cohort consists of 40,550 patients hospitalised during the first wave. These patients had a median age of 69 (interquartile range 56-80) and were more likely to be men (60%) than women (40%). The hospital-fatality risk, averaged over all pathways through hospital, was 27.5% (95% CI 27.1-28.0%); and steadily decreased from 34.6% (32.5-36.6%) in February to 7.6% (6.3-10.6%) in June. Among surviving patients, median length of stay in hospital was 11.8 (11.6-12.3) days, compared to 8.1 (7.8-8.5) days in non-survivors. Averaged over final outcomes, median length of stay in hospital decreased from 21.4 (20.5-22.8) days in February to 5.2 (4.7-5.8) days in June.
CONCLUSIONS
The hospital burden, in terms of both risks of poor outcomes and lengths of stay in hospital, has been demonstrated to have decreased over the months of the first wave, perhaps reflecting improved treatment and management of COVID-19 cases, as well as reduced burden as the first wave waned. The quantified burden allows for planning of hospital beds needed for current and future waves of SARS-CoV-2 i.

Identifiants

pubmed: 34479535
doi: 10.1186/s12889-021-11669-w
pii: 10.1186/s12889-021-11669-w
pmc: PMC8414029
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1612

Subventions

Organisme : Medical Research Council
ID : MC_PC_19074
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00002/11
Pays : United Kingdom

Investigateurs

Ambra Castrofino (A)
Gabriele Del Castillo (G)
Lucia Crottogini (L)
Marcello Tirani (M)
Alberto Zanella (A)
Marco Salmoiraghi (M)

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© 2021. The Author(s).

Références

European Center of Disease Control. Timeline of ECDC’s response to COVID-19. https://www.ecdc.europa.eu/en/covid-19/timeline-ecdc-response . Accessed 8 Dec 2020.
Grasselli G, Pesenti A, Cecconi M. Critical care utilization for the COVID-19 outbreak in Lombardy, Italy: early experience and forecast during an emergency response. JAMA. 2020;323(16):1545–6. https://doi.org/10.1001/jama.2020.4031 .
doi: 10.1001/jama.2020.4031 pubmed: 32167538
Welfare Directorate of Regione Lombardia, Protocol G1.2020.0003279, 28 January 2020;
Welfare Directorate of Regione Lombardia, Protocol G1.2020.0005384; 07 February 2020;
Regione Lombardia; Dashboard Covid-19; https://www.regione.lombardia.it/wps/portal/istituzionale/HP/servizi-e-informazioni/cittadini/salute-e-prevenzione/coronavirus/dashboard-covid19 ; Accessed 16 Dec 2020.
Armocida B, Formenti B, Ussai S, Palestra F, Missoni E, The Italian Health System and the COVID-19 challenge. [published online March 25, 2020] The Lancet Public Health; doi: https://doi.org/10.1016/S2468-2667(20)30074-8 .
Jackson CH, Tom BDM, Kirwan PD, Mandal S, Seaman SR, Kunzmann K, et al. A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19. Submitted; 2020.
Welfare Directorate of Regione Lombardia, Regional Decree N° XI/3019; 30 March 2020.
Welfare Directorate of Regione Lombardia, Regional Decree N° VII/18853; 30 September 2004.
Welfare Directorate of Regione Lombardia, Regional Decree N°XI/3114; 07 July 2020.
Larson MG, Dinse GE. A mixture model for the regression analysis of competing risks data. J Royal Stat Soc Series C (Applied Statistics). 1985;34(3):201–11 JSTOR, www.jstor.org/stable/2347464 . Accessed 30 Dec. 2020.
Presanis AM, Kunzmann K, Grosso F, Jackson C, Corbella A, Gramegna M, et al. Risk factors for severe hospital burden during the first wave of COVID-19 disease in Regione Lombardia. In preparation; 2021.
Boëlle P, Delory T, Maynadier X, et al. Trajectories of Hospitalization in COVID-19 patients: an observational study inFrance. J Clin Med. 2020;9(10):3148. https://doi.org/10.3390/jcm9103148 .
doi: 10.3390/jcm9103148 pmcid: 7600846
Rees EM, Nightingale ES, Jafari Y, Waterlow NR, Clifford S, B. Pearson CA, et al. COVID-19 length of hospital stay: a systematic review and data synthesis. BMC Med. 2020;18(1):270. https://doi.org/10.1186/s12916-020-01726-3 .
doi: 10.1186/s12916-020-01726-3 pubmed: 32878619 pmcid: 7467845
O’Brien SM, DeLong ER, Peterson ED. Impact of case volume on hospital performance assessment. Arch Intern Med. 2008;168(12):1277–84. https://doi.org/10.1001/archinte.168.12.1277 .
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Auteurs

Francesca Maria Grosso (FM)

Postgraduate School of Public Health, Department of Biomedical Sciences for Health, Via Pascal 36, University of Milan, Milan, Italy. francesca.grosso@unimi.it.

Anne Margaret Presanis (AM)

MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Robinson way, Cambridge, UK.

Kevin Kunzmann (K)

MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Robinson way, Cambridge, UK.

Chris Jackson (C)

MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Robinson way, Cambridge, UK.

Alice Corbella (A)

MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Robinson way, Cambridge, UK.
Department of Statistics, University of Warwick, Mathematical Sciences Building, Academic Loop Road, Warwick, UK.

Giacomo Grasselli (G)

Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Via Francesco Sforza 28, Milan, Italy.

Aida Andreassi (A)

Welfare General Directorate, Regione Lombardia, Piazza Città di Lombardia 1, Milan, Italy.

Annalisa Bodina (A)

Welfare General Directorate, Regione Lombardia, Piazza Città di Lombardia 1, Milan, Italy.

Maria Gramegna (M)

Welfare General Directorate, Regione Lombardia, Piazza Città di Lombardia 1, Milan, Italy.

Silvana Castaldi (S)

Postgraduate School of Public Health, Department of Biomedical Sciences for Health, Via Pascal 36, University of Milan, Milan, Italy.
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Via Francesco Sforza 28, Milan, Italy.

Danilo Cereda (D)

Welfare General Directorate, Regione Lombardia, Piazza Città di Lombardia 1, Milan, Italy.

Daniela De Angelis (D)

MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Robinson way, Cambridge, UK.

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