Evidence map›Paper›PMID 35603234›Full record

ArticleJournal of preventive medicine and hygiene2021

Weight of risk factors for mortality and short-term mortality displacement during the COVID-19 pandemic.

Matteo Astengo, Federico Tassinari, Chiara Paganino, Simona Simonetti, Domenico Gallo, Daniela Amicizia, Maria Francesca Piazza, Andrea Orsi, Giancarlo Icardi, Filippo Ansaldi

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Article in Journal of preventive medicine and hygiene, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Matteo AstengoA.Li.Sa. Liguria Health Authority, Genoa, Italy.
Federico TassinariA.Li.Sa. Liguria Health Authority, Genoa, Italy.
Chiara PaganinoA.Li.Sa. Liguria Health Authority, Genoa, Italy.
Simona SimonettiDepartment of Health Sciences, University of Genoa, Genoa, Italy.
Domenico GalloA.Li.Sa. Liguria Health Authority, Genoa, Italy.
Daniela Amicizia
Maria Francesca PiazzaA.Li.Sa. Liguria Health Authority, Genoa, Italy.
Andrea Orsi
Giancarlo Icardi
Filippo Ansaldi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: We conducted a population-based cohort study to estimate mortality before, during and after the COVID-19 peak and to compare mortality in 2020 with rates reported in previous years, with a view to helping decision makers to apply containment measures for high-risk groups. Methods: All deaths were collected between 2015 and 2020 from municipal registry database. In 2020, weeks 1-26 were stratified in three periods: before, during and after the COVID mortality peak. The Poisson Generalized Linear regression Model showed the "harvesting effect". Three logistic regressions for 8 dependent variables (age and comorbidities) and a t-test of differences described all-cause mortality risk factors in 2019 and 2020 and differences between COVID and non-COVID patients. Results: A total of 47,876 deaths were collected. All-cause deaths increased by 38.5% during the COVID peak and decreased by 18% during the post-peak period in comparison with the average registered during the control period (2015-19), with significant mortality displacement in 2020. Except for chronic renal injuries in subjects aged 45-64 years, diabetes and chronic cardiovascular diseases in those aged 65-84 years, and neuropathies in those aged > 84 years, the weight of comorbidities in deaths was similar or lower in COVID subjects than in non-COVID subjects. Discussions: Surprisingly, the weight of comorbidities in death, compared to weight in non-COVID subjects allows you to highlight some surprising results such as COPD, IBD and Cancer. The excess mortality that we observed in the entire period were modest in comparison with initial estimates during the peak, owing to the mild influenza season and the harvesting effect starting from the second half of May.

Indexed as

COVID-19Cohort StudiesHumansPandemicsRisk FactorsSARS-CoV-2ComorbiditiesCOVID-19Harvesting effectMortality displacementRisk factorSARS-CoV-2

Identifiers

PMID35603234
PMCPMC9104669

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.