Evidence map›Paper›PMID 37189141›Full record

ArticleBMC health services research2023

Symptoms and risk factors for long COVID in Tunisian population.

Souhir Chelly, Sourour Rouis, Olfa Ezzi, Asma Ammar, Sami Fitouri, Asma Soua, Ines Fathallah, Mansour Njah, Mohamed Mahjoub

Abstract read
In one paragraph

Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Understanding how social determinants of health shape Long COVID outcomes: a rapid review of evidence.Archives of public health = Archives belges de sante publique · 2025
    Pooled it
  2. Long-Term Health Effects of COVID-19 in Tunisia, 2020-2021.International journal of environmental research and public health · 2025
    Article
  3. Article
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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

9 authors.

Souhir ChellyInfection Prevention and Control department, Farhat Hached university hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Sousse, 4000, Tunisia. souhirch@hotmail.fr.
Sourour RouisDepartment of Community and Family Medicine, Faculty of Medicine of Sousse, University of Sousse, Sousse, Tunisia.
Olfa EzziInfection Prevention and Control department, Farhat Hached university hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Sousse, 4000, Tunisia.
Asma AmmarInfection Prevention and Control department, Farhat Hached university hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Sousse, 4000, Tunisia.
Sami FitouriDepartment of Community and Family Medicine, Faculty of Medicine of Sousse, University of Sousse, Sousse, Tunisia.
Asma SouaDepartment of Community and Family Medicine, Faculty of Medicine of Sousse, University of Sousse, Sousse, Tunisia.
Ines FathallahDepartment of Community and Family Medicine, Faculty of Medicine of Sousse, University of Sousse, Sousse, Tunisia.
Mansour NjahInfection Prevention and Control department, Farhat Hached university hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Sousse, 4000, Tunisia.
Mohamed MahjoubInfection Prevention and Control department, Farhat Hached university hospital of Sousse, Faculty of Medicine of Sousse, University of Sousse, Sousse, 4000, Tunisia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has presented various challenges, one of which is the discovery that after the acute episode, around 30% of patients experience persistent symptoms or develop new ones, now known as long COVID. This new disease has significant social and financial impacts. The objective is to determine the prevalence of long COVID in the Tunisian population and identify its predictive factors.

methodsThis was a cross-sectional study conducted among Tunisians who were infected with COVID-19 between March 2020 and February 2022. An online self-administered questionnaire was distributed through social media, radio, and television channels over the course of one month (February 2022). Long COVID was defined as the persistence of existing symptoms or the development of new symptoms within three months after onset, lasting for at least two months, and with no differential diagnosis. We performed univariate and multivariate analyses using binary stepwise logistic regression with a significance level set at 5%.

resultsA total of 1911 patients participated in our study, and the prevalence of long COVID was 46.5%. The two most frequent categories were general and neurological post-COVID syndrome, with a prevalence of 36.7% each. The most commonly observed symptoms were fatigue (63.7%) and memory problems (49.1%). In the multivariate analysis, the predictive factors for long COVID were female gender and age of 60 years or older, while complete anti-COVID vaccination was found to be a protective factor.

conclusionsOur study found that complete vaccination was a protective factor against long COVID, while female gender and age of 60 years or older were identified as the main risk factors. These findings are consistent with studies conducted on other ethnic groups. However, many aspects of long COVID remain unclear, including its underlying mechanisms, the identification of which could guide the development of potential effective treatments.

Indexed as

COVID-19Post-Acute COVID-19 SyndromeCross-Sectional StudiesFemaleHumansMaleMiddle AgedPandemicsRisk FactorsCOVID-19EpidemiologyInfectious diseasesLong COVIDRisk factors

Identifiers

PMID37189141
PMCPMC10184965

What OpenQuestion holds

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LicenceCC BY
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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.