Evidence map›Paper›PMID 37113876›Full record

ArticleAnnals of medicine and surgery (2012)2023

Cross-sectional study of COVID-19 infection in patients with rheumatic diseases in a sample of a Damascene population, Syria.

Naram Khalayli, Maysoun Kudsi

Open access · diamondAbstract read
In one paragraph

Article in Annals of medicine and surgery (2012), 2023. 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
0.2field-weighted citation impact, top 52% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Naram KhalayliDamascus University, Damascus, Syrian Arab Republic.ORCID 0000-0001-7161-979X
Maysoun KudsiDamascus University, Damascus, Syrian Arab Republic.
Damascus University · SY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus infections have been responsible since 2019 for respiratory illnesses with varying severity worldwide. Worst outcomes from coronavirus (COVID-19) have been reported in older patients andthose with comorbidities like rheumatic diseases. Some drugs used for treating rheumatic diseases are used in patients with COVID-19. Based on the limited data, rheumatic diseases do not seem to affect the disease course of COVID-19. We aimed to analyze the course of COVID-19 infections in patients with rheumatic diseases. Methods: A self-reported questionnaire was distributed online and to patients admitted with respiratory involvement. Data included demographic information, clinical presentation, severity, comorbidities, and laboratory parameters. Cases were matched by age, sex, the month of admission, and COVID-19 respiratory injury for patients with rheumatic diseases and patients without rheumatic diseases. Results: Twenty-two patients (4.4%) had rheumatic diseases before the COVID-19 infection. There were no differences in the use of treatment for COVID-19 infections in previous or present therapy or comorbidities. We found no significant difference in the duration of COVID-19 symptoms before admission, duration of hospital stay, or chest Xray Brixia score between the two groups. The lymphocyte count was lower in the patient group, while lactate dehydrogenase, ferritin, and D-dimer concentrations were higher compared to the control group. Thrombotic events were similar in rate. Conclusion: The poorer outcome from COVID-19 infections in patients with rheumatic diseases is related to older age and the presence of comorbidities rather than the rheumatic disease type or its treatment.

Indexed as

COVID-19inflammatory markersmusculoskeletalpneumoniarheumatic diseases

Identifiers

PMID37113876
PMCPMC10129248
OpenAlexW4361286440

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.