Evidence map›Paper›PMID 40217157›Full record

ArticleBMC infectious diseases2025

Exploring the landscape of long COVID: prevalence and associated factors in patients assisted by a telehealth service.

Ana Flávia Avelar Maia Seixas, Milena Soriano Marcolino, Felipe Souza Guimarães, Gustavo Machado Rocha, Aline Carrilho Menezes, Hygor Kleber Cabral Silva, Clareci Silva Cardoso

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ana Flávia Avelar Maia SeixasGrupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS/UFSJ/CNPq, Universidade Federal de São João del-Rei, Divinópolis, Minas Gerais, Brasil. anafamfisio@gmail.com.
Milena Soriano MarcolinoFaculdade de Medicina e Centro de Telessaúde do Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brasil.
Felipe Souza GuimarãesGrupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS/UFSJ/CNPq, Universidade Federal de São João del-Rei, Divinópolis, Minas Gerais, Brasil.
Gustavo Machado RochaGrupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS/UFSJ/CNPq, Universidade Federal de São João del-Rei, Divinópolis, Minas Gerais, Brasil.
Aline Carrilho MenezesGrupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS/UFSJ/CNPq, Universidade Federal de São João del-Rei, Divinópolis, Minas Gerais, Brasil.
Hygor Kleber Cabral SilvaGrupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS/UFSJ/CNPq, Universidade Federal de São João del-Rei, Divinópolis, Minas Gerais, Brasil.
Clareci Silva CardosoGrupo de Pesquisa em Epidemiologia e Avaliação de Novas Tecnologias em Saúde, GPEANTS/UFSJ/CNPq, Universidade Federal de São João del-Rei, Divinópolis, Minas Gerais, Brasil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLong COVID is a condition that occurs in patients with a previous history of COVID-19, and symptoms that cannot be explained by another diagnosis persist.

objectiveTo evaluate the prevalence of long COVID and associated factors in patients treated with a public telehealth service during acute COVID-19.

methodThis was a cross-sectional study involving users of a COVID-19 telehealth service offered during the critical phase of the pandemic, called TeleCOVID-MG. Individuals older than 18 years of age who tested positive for SARS-CoV-2 and were monitored during social isolation were eligible. Prevalence was calculated, and descriptive analysis and group comparisons (patients with and without long COVID symptoms) were performed in addition to logistic regression with odds ratios and 95% confidence intervals.

resultsAmong the 699 patients included in the study, 60.8% were women aged between 30 and 49 years (44.6%) and had a high school education (46.5%). The main comorbidities were hypertension (20.9%), diabetes (8.3%), and heart disease (3.9%). The incidence of long COVID was 26.8% (95% CI: 23.5; 30.1). Cognitive symptoms (49.7%), chronic diarrhea (49.2%), and cough (40.6%) were the most persistent symptoms. Female sex (OR: 2.51), secondary education (OR: 2.13), elementary education (OR: 2.81), monthly income between 600 and 1,000 USD (OR: 5.85), supplementary health assistance (OR: 1.98), anosmia during acute COVID-19 (OR: 4.52) and need for in-person care (OR: 2.44) were factors associated with a higher incidence of long COVID.

conclusionLong COVID affected almost one-third of the study population. Although the COVID-19 pandemic is under control, the virus continues to infect individuals, raising doubts about the long-term complications of the disease.

Indexed as

COVID-19TelemedicineAdultAgedComorbidityCross-Sectional StudiesFemaleHumansMaleMiddle AgedPost-Acute COVID-19 SyndromePrevalenceRisk FactorsSARS-CoV-2Young AdultCOVID-19Long COVIDOutpatientsTelemedicine

Identifiers

PMID40217157
PMCPMC11992846

What OpenQuestion 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 OpenQuestion graph.