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Record W6989164629

Adverse Cutaneous Reactions Following COVID-19 Vaccination Among Patients with Pre-Existing Urticaria: A Cross-Sectional Study at a Tertiary Care Center in Saudi Arabia

2025· article· en· W6989164629 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldMedicine
TopicUrticaria and Related Conditions
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsExacerbationTertiary careVaccinationAdverse effectAntihistamineUniversity hospitalLogistic regression
DOInot available

Abstract

fetched live from OpenAlex

Ashwag Asiri,1 Hend M Alotaibi,2 Nouf Ali Alotaibi,3 Alfahdah Abdullah Alsaleem4 1Department of Child Health, College of Medicine, King Khalid University, Abha, Saudi Arabia; 2Department of Dermatology, College of Medicine, King Saud University, Riyadh, Saudi Arabia; 3Department of Family Medicine, King Fahad Medical City, Riyadh, Saudi Arabia; 4Department of Pediatrics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi ArabiaCorrespondence: Ashwag Asiri, Department of Child Health, College of Medicine, King Khalid University, P.O. Box 62527, Abha, Saudi Arabia, Email asalasiri@kku.edu.saPurpose: To investigate the incidence, characteristics, and associated factors of cutaneous adverse reactions to COVID-19 vaccines among adult patients with pre-existing urticaria in Saudi Arabia.Patients and Methods: A cross-sectional study enrolled 190 adult patients (≥ 18 years) with urticaria attending allergy/dermatology clinics at King Khalid University Hospital, Riyadh (November 2021–April 2022). Data on demographics, urticaria characteristics, vaccination status, cutaneous reactions, and comorbidities were collected via questionnaire. Statistical analyses included descriptive statistics, Chi-square/Fisher exact tests, Cochran’s test, and binary logistic regression.Results: Participants were predominantly female (87.4%), with chronic spontaneous urticaria (97.9%); 78.9% used regular antihistamines. Reactions occurred after dose 1 (22.7%), dose 2 (26.2%), and dose 3 (31.0%). Among symptomatic individuals, onset was typically < 24h, resolving in 1– 3 days for ~50%. Common reactions included injection site reactions (13.1– 16.3%), pruritus (7.8– 10.5%), and urticaria exacerbation (3.9– 9.1%). Urticaria exacerbation decreased significantly after dose 3 (p=0.030). Regular antihistamine use was associated with fewer reactions after dose 1 (adjusted OR 0.4, p=0.028). Female gender, asthma/atopy, and autoimmune disease were associated with specific reactions. Adjusted vaccine type showed no significant association.Conclusion: Cutaneous reactions post-COVID-19 vaccination in urticaria patients are relatively common but generally mild and transient. Decreasing urticaria exacerbations after dose 3 is reassuring. Regular antihistamine use may offer some protection, particularly after the first dose. Findings support vaccine safety and aid patient counseling.Plain Language Summary: Understanding how COVID-19 vaccines affect people with existing skin allergies is 41 crucial for public health. Our study focused on patients with urticaria (chronic hives) 42 who received COVID-19 vaccines. We found that while many patients experienced 43 mild skin reactions after vaccination, these reactions were generally temporary and 44 manageable. Most reactions occurred within 24 hours of vaccination and resolved within 45 a few days. Importantly, patients who regularly took antihistamine medications were 46 less likely to develop reactions. This research provides reassurance that COVID-19 47 vaccines can be safely administered to people with pre-existing urticaria, although some 48 may experience temporary symptoms. These findings help both healthcare providers 49 and patients make informed decisions about vaccination.Keywords: COVID-19, vaccine, urticaria, cutaneous adverse reaction, antihistamine, Saudi Arabia, cross-sectional study

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.077
GPT teacher head0.491
Teacher spread0.414 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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