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Record W4413788472 · doi:10.47391/jpma.11052

Association of dermatological manifestations with infertility: a systematic review of literature

2025· review· en· W4413788472 on OpenAlexaff
Muhammad Saleem, Samra Azhar, Muntaha Durrani, S. Fatima, Maha Niazi, Muhammad Atif

Bibliographic record

VenueJournal of the Pakistan Medical Association · 2025
Typereview
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsAlberta Health ServicesMisericordia Community HospitalAlberta HealthUniversity of Alberta Hospital
Fundersnot available
KeywordsInfertilityAssociation (psychology)MedicineDermatologySystematic reviewMEDLINEPsychologyBiologyPregnancyPsychotherapistGenetics

Abstract

fetched live from OpenAlex

OBJECTIVE: To compile and analyse current literature to provide a comprehensive evidence related to the potential links between dermatological manifestations of skin disorders and infertility. Methods: The systematic review comprised literature search up to December 31, 2022, on Pubmed, Medline, Excerpta Medica dataBASE and Global Health databases. All original and published studies in the English language reporting on the dermatological manifestations in humans, associated with or contributing to infertility both in females and males were included. Quality assessment was performed independently by two reviewers using the Joanna Briggs Institute critical appraisal tools. RESULTS: There were 10 studies comprising 268,570 subjects. Significant positive association between skin manifestations and infer tility were found in the studies reporting on the dermatological manifestations of polycystic ovarian syndrome, dermatomyositis, atopic dermatitis and leprosy (p<0.05), while the study reporting on the association between skin manifestation of systemic sclerosis did not report a significant result (p>0.05). Conclusion: There was a potential association between cutaneous manifestations of various dermatological disorders and infer tility.

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)0.004
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.327
Teacher spread0.316 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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