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Risk factors for genital lichen sclerosus in men

2010· article· en· W1869303064 on OpenAlexaff
Milan Bjekić, Jelena Marinković

Bibliographic record

VenueBritish Journal of Dermatology · 2010
Typearticle
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsSKiN Health
Fundersnot available
KeywordsAlopecia areataLichen sclerosusMedicineOdds ratioDermatologyEtiologyVitiligoSex organConfidence intervalFamily historyLogistic regressionPsoriasisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Lichen sclerosus (LS) is an inflammatory disease of the skin and mucous membranes. Its aetiology is still unknown. OBJECTIVES: To determine risk factors for genital LS in men. METHODS: In a case-control study, 73 patients with LS, consecutively diagnosed at the City Dispensary for Skin and Venereal Diseases in Belgrade, were compared with 219 male patients visiting the same institution because of tinea cruris. Univariate and multivariate logistic regression analyses were used for analysis of data collected. RESULTS: According to multivariate logistic regression analysis, risk factors for male LS were as follows: a personal history of genital injury [odds ratio (OR) 28·1, 95% confidence interval (CI) 5·2-150·8], vitiligo (OR 23·1, 95% CI 2·2-240·2), alopecia areata (OR 8·8, 95% CI 1·1-68·5) and hypercholesterolaemia (OR 3·1, 95% CI 1·1-8·2), and a family history of alopecia areata (OR 24·3, 95% CI 2·1-280·7), diseases of the thyroid gland (OR 9·1, 95% CI 2·3-36·2) and other autoimmune diseases (OR 8·6, 95% CI 1·3-58·6). CONCLUSIONS: The results of the present study are in line with the hypothesis that trauma of the penis is a possible trigger of symptoms in genetically predisposed individuals and that personal and family histories of autoimmune disorders are risk factors for male LS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.283
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations46
Published2010
Admission routes1
Has abstractyes

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