Evidence map›Paper›PMID 37921395›Full record

ArticleRevista espanola de salud publica2023

[¿Disminuye la vacunación antigripal el riesgo de COVID-19? Estudio de casos y controles en un centro de Atención Primaria durante el año 2020.]

Lluís Cuixart Costa, Nariman Chahboun El Messaoudi

Abstract readEnglish Abstract
In one paragraph

Article in Revista espanola de salud publica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Lluís Cuixart CostaMédico especialista en Medicina Familiar y Comunitaria; CAP Roger de Flor; EAP Dreta Eixample. Barcelona. España.
Nariman Chahboun El MessaoudiMédica Interna Residente de 4º año de Medicina Familiar y Comunitaria; CAP Roger de Flor; EAP Dreta Eixample. Barcelona. España.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThere are controversies regarding the effect of the influenza vaccine on the risk of suffering from COVID-19. The aim of this paper was to compare the risk of suffering from COVID-19 between vaccinated and unvaccinated patients against influenza.

methodsA retrospective case-control study of patients assigned to an urban CAP (coverage: 44,564 inhabitants) was carried out during 2020. Patients with diagnostic confirmation of COVID-19 (ART, PCR or serology) were defined as cases, and those who have not had said infection, selected by simple random sampling, were defined as controls. The case/control ratio was 1:1. The data sources used were the Khalix health data registry databases and the computerized medical record (E-cap). Data were analyzed with a multivariable logistic regression model.

resultsA total of 4,320 patients were included in the study: 2,160 cases (50%) and 2,160 controls. 18% of the cases and 14.3% of the controls were vaccinated against influenza [OR=1.3 (95% CI: 1.2-1.5; p=0.001)]. Multivariate analysis showed that in patients under eighty years of age, there were no differences between vaccinated and unvaccinated patients [OR=1.02 (95% CI: 0.8-1.3; p=0.8)]; while in those over eighty years of age, there was a lower risk of presenting COVID-19 in vaccinated patients [OR=0.4 (95% CI: 0.3-0.7; p<0.001)].

conclusionsThe adjusted model shows that at ages above than 80 years, flu-vaccinated patients have decreased risk of COVID-19 with statistical significance.

Indexed as

COVID-19Influenza, HumanCase-Control StudiesHumansRetrospective StudiesSpainCOVID-19 (Coronavirus Disease 2019)Flu vaccinesPrimary Care

Identifiers

PMID37921395
PMCPMC11567080

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.