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Record W2921008494 · doi:10.1111/jdv.15548

Finasteride for androgenetic alopecia is not associated with sexual dysfunction: a survey‐based, single‐centre, controlled study

2019· article· en· W2921008494 on OpenAlexaff
Robert S. Haber, Aditya Gupta, Edwin S. Epstein, Jessie Carviel, Kelly A. Foley

Bibliographic record

VenueJournal of the European Academy of Dermatology and Venereology · 2019
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsFinasterideSexual dysfunctionMedicineLibidoPopulationDecreased LibidoUrologyGynecologyClinical psychologyInternal medicineProstate

Abstract

fetched live from OpenAlex

BACKGROUND: The occurrence of sexual dysfunction side-effects associated with finasteride use in men with androgenetic alopecia (AGA) is thought to be less prevalent than is publicized. There is a need to investigate sexual dysfunction among finasteride users with population-based controls. OBJECTIVE: To evaluate the presence of sexual dysfunction in men using finasteride or not using finasteride. METHOD: Adult men visiting a dermatologist's office for any reason were asked to complete a survey including a modified version of the Arizona Sexual Experience Scale (ASEX) to assess the presence of sexual dysfunction with and without finasteride use. RESULTS: Data from 762 men aged 18-82 were collected: 663 finasteride users and 99 non-finasteride users. There were no significant differences between finasteride users and non-user controls in reporting sexual dysfunction using the ASEX. Regression analysis indicated that self-reporting libido loss and reduced sexual performance, not finasteride use, predict a higher ASEX score. CONCLUSION: The use of finasteride does not result in sexual dysfunction in men with AGA. These data are consistent with other large survey-based controlled studies.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.045
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.029
GPT teacher head0.259
Teacher spread0.230 · 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

Citations25
Published2019
Admission routes1
Has abstractyes

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