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Record W4386307535 · doi:10.1089/derm.2023.0191

Prayer-Related Dermatoses in Muslims

2023· review· en· W4386307535 on OpenAlexvenueno aff
Yousef Salem, Syed Minhaj Rahman, Mojahed Shalabi, Aamir Hussain

Bibliographic record

VenueDermatitis · 2023
Typereview
Languageen
FieldMedicine
TopicDermatological diseases and infestations
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePrayerDermatologyTraditional medicineReligious studies

Abstract

fetched live from OpenAlex

Prayer rituals are an integral part of the daily lives of Muslims worldwide. This comprehensive review aims to explore the common dermatoses associated with prayer among Muslims and provide insights for dermatologists to facilitate accurate diagnosis and reduce unnecessary investigations. A systematic literature search returned 367 published articles, of which 21 met the inclusion criteria. Friction-induced dermatitis was the most frequently reported dermatosis, primarily affecting the forehead, knees, dorsum of the feet, and lateral malleoli. Friction-related marks often present as hyperpigmented lichenified plaques, and are more common in elderly individuals and males. Cases of contact dermatitis and fungal infections were also reported. Allergic contact dermatitis was linked to perfume application before Friday prayers, whereas fungal infections were attributed to increased water retention between toe webs, possibly related to communal ablution and prayer areas. Awareness of these prayer-related dermatoses enables dermatologists to provide holistic care for diverse populations and targeting specific interventions with respect for patients' religious beliefs. For example, Muslim patients with symptomatic frictional dermatoses may benefit from use of padded prayer rugs, especially diabetic patients whose lesions carry an increased risk of progressing to neuropathic ulcers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.082
GPT teacher head0.383
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2023
Admission routes1
Has abstractyes

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