Evidence map›Paper›PMID 40155409›Full record

ArticleScientific reports2025

Identifying risk factors and predicting long COVID in a Spanish cohort.

Antonio Guillén-Teruel, Jose L Mellina-Andreu, Gabriel Reina, Enrique González-Billalabeitia, Ramón Rodriguez-Iborra, José Palma, Juan A Botía, Alejandro Cisterna-García

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Antonio Guillén-TeruelDepartment of Information and Communication Engineering, University of Murcia, Murcia, 30100, Spain.
Jose L Mellina-AndreuDepartment of Information and Communication Engineering, University of Murcia, Murcia, 30100, Spain.
Gabriel ReinaServicio de Microbiología, Clínica, Universidad de Navarra, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Navarra, Spain.
Enrique González-BillalabeitiaDepartment of Medical Oncology, Hospital Universitario, 12 de Octubre, Madrid, Spain.
Ramón Rodriguez-IborraSubdirección General de Tecnologías de la Información, Servicio Murciano de Salud, Murcia, Spain.
José PalmaDepartment of Information and Communication Engineering, University of Murcia, Murcia, 30100, Spain.
Juan A BotíaDepartment of Information and Communication Engineering, University of Murcia, Murcia, 30100, Spain.
Alejandro Cisterna-GarcíaDepartment of Information and Communication Engineering, University of Murcia, Murcia, 30100, Spain. alejandro.cisterna@um.es.

Funding

Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia 21259/FPI/19Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia 22308/FPI/23Spanish Council of Science and Innovation ID2022-136306OB-I00
6 · The paper itself

Abstract

Many studies have investigated symptoms, comorbidities, demographic factors, and vaccine effects in relation to long COVID (LC-19) across global populations. However, a number of these studies have shortcomings, such as inadequate LC-19 categorisation, lack of sex disaggregation, or a narrow focus on certain risk factors like symptoms or comorbidities alone. We address these gaps by investigating the demographic factors, comorbidities, and symptoms present during the acute phase of primary COVID-19 infection among patients with LC-19 and comparing them to typical non-Long COVID-19 patients. Additionally, we assess the impact of COVID-19 vaccination on these patients. Drawing on data from the Regional Health System of the Region of Murcia in southeastern Spain, our analysis includes comprehensive information from clinical and hospitalisation records, symptoms, and vaccination details of over 675126 patients across 10 hospitals. We calculated age and sex-adjusted odds ratios (AOR) to identify protective and risk factors for LC-19. Our findings reveal distinct symptomatology, comorbidity patterns, and demographic characteristics among patients with LC-19 versus those with typical non-Long COVID-19. Factors such as age, female sex (AOR = 1.39, adjusted p < 0.001), and symptoms like chest pain (AOR > 1.55, adjusted p < 0.001) or hyposmia (AOR > 1.5, adjusted p < 0.001) significantly increase the risk of developing LC-19. However, vaccination demonstrates a strong protective effect, with vaccinated individuals having a markedly lower risk (AOR = 0.10, adjusted p < 0.001), highlighting the importance of vaccination in reducing LC-19 susceptibility. Interestingly, symptoms and comorbidities show no significant differences when disaggregated by type of LC-19 patient. Vaccination before infection is the most important factor and notably decreases the likelihood of long COVID. Particularly, mRNA vaccines offer more protection against developing LC-19 than viral vector-based vaccines (AOR = 0.48). Additionally, we have developed a model to predict LC-19 that incorporates all studied risk factors, achieving a balanced accuracy of 73% and ROC-AUC of 0.80. This model is available as a free online LC-19 calculator, accessible at ( LC-19 Calculator ).

Indexed as

COVID-19AdultAgedAged, 80 and overCohort StudiesComorbidityCOVID-19 VaccinesFemaleHospitalizationHumansMaleMiddle AgedRisk FactorsSARS-CoV-2SpainVaccinationCOVID-19 VaccinesCOVID-19LC-19Long COVIDSARS-CoV-2Vaccines

Identifiers

PMID40155409
PMCPMC11953293

What Socratic holds

Textmetadata
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 Socratic graph.