Evidence map›Paper›PMID 38190050›Full record

ArticleJournal of epidemiology and global health2024

Cutaneous Leishmaniasis Hampers COVID-19: A Controlled Cross-Sectional Study in High-Burden Endemic Areas of Iran.

Mehdi Bamorovat, Iraj Sharifi, Mehdi Shafiei Bafti, Setareh Agha Kuchak Afshari, Mohammad Reza Aflatoonian, Ali Karamoozian, Abdollah Jafarzadeh, Raheleh Amirzadeh, Ahmad Khosravi, Zahra Babaei and 3 more

Open access · goldAbstract read
In one paragraph

Article in Journal of epidemiology and global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. 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

13 authors at 2 institutions in 1 country.

Mehdi BamorovatLeishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran. mehdimorovat@ymail.com.ORCID http://orcid.org/0000-0002-4900-4278
Iraj SharifiLeishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran. iraj.sharifi@yahoo.com.ORCID http://orcid.org/0000-0002-6894-6834
Mehdi Shafiei BaftiInstitute for Studies in Medicine History, Persian and Complementary Medicine, Iran University of Medical Sciences, Tehran, Iran.
Setareh Agha Kuchak AfshariMedical Mycology and Bacteriology Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Mohammad Reza AflatoonianLeishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Ali KaramoozianResearch Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Abdollah JafarzadehDepartment of Immunology, Kerman University of Medical Sciences, Kerman, Iran.
Raheleh AmirzadehResearch Center for Social Determinants of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Ahmad KhosraviLeishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Zahra BabaeiLeishmaniasis Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Farzane SafaDeputy for Health, Kerman University of Medical Sciences, Kerman, Iran.
Fatemeh SharifiResearch Center for Tropical and Infectious Diseases, Kerman University of Medical Sciences, Kerman, Iran.
Amireh HeshmatkhahDadbin Health Clinic, Kerman University of Medical Sciences, Kerman, Iran.
Kerman University of Medical Sciences · IRIran University of Medical Sciences · IR

Funding

Kerman University of Medical Sciences 400000704
6 · The paper itself

Abstract

introductionEmerging infectious diseases such as SARS-CoV-2 can cause pandemics and create a critical risk for humans. In a previous pilot study, we reported that the immunological responses induced by cutaneous leishmaniasis (CL) could decrease the incidence and severity of COVID-19. In this large-scale case-control study, we assessed the possible relationship between mortality and morbidity of COVID-19 in healed CL persons suffering scars compared to cases without CL history.

methodsThis controlled cross-sectional study was conducted between July 2020 and December 2022 in the endemic and high-burden areas of CL in southeastern Iran. In the study, 1400 previous CL cases with scars and 1,521,329 subjects who had no previous CL were analyzed. We used R 4.0.2 to analyze the data. Firth's bias reduction approach corresponding to the penalization of likelihood logistic regression by Jeffreys was also employed to influence the variables in the dataset. Also, a Bayesian ordinal logistic regression model was performed to explore the COVID-19 severity in both case and referent groups.

resultsThe occurrence and severity rate of COVID-19 in CL scar cases are significantly less than in the non-CL control group, while in the CL scar subjects, patients with critical conditions and mortality were not observed. The morbidity (OR = 0.11, CI 0.06-0.20 and P < 0.001) and severity of COVID-19 in previous cases with CL scars were significantly diminished than that in the control group (credible interval - 2.57, - 1.62).

conclusionsThe results represented a durable negative relationship between cured CL and COVID-19 incidence and severity. Additional studies seem necessary and should be designed to further validate the true impact and underlying mechanistic action of CL on COVID-19.

Indexed as

COVID-19Leishmaniasis, CutaneousAdolescentAdultAgedBayes TheoremCase-Control StudiesCicatrixCross-Sectional StudiesEndemic DiseasesFemaleHumansIncidenceIranMaleMiddle AgedCOVID-19Cross-protectionCutaneous leishmaniasisSeverityTrained innate immunity

Identifiers

PMID38190050
PMCPMC11043327
OpenAlexW4390673308

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.