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Record W4391530799 · doi:10.1080/14656566.2024.2314087

Efficacy and safety of low-dose oral minoxidil in the management of androgenetic alopecia

2024· article· en· W4391530799 on OpenAlexaff
Aditya K. Gupta, Mesbah Talukder, Avner Shemer

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2024
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsMinoxidilMedicineFinasterideDutasterideHair lossDermatologySafety profileMale-pattern baldnessAdverse effectPharmacologyClinical trialInternal medicineScalpProstate cancerProstate

Abstract

fetched live from OpenAlex

INTRODUCTION: Treating alopecia can be challenging. The available treatments are topical minoxidil, low-dose oral minoxidil (LDOM), and 5-α reductase inhibitors like finasteride and dutasteride. Only topical minoxidil and finasteride 1 mg daily are FDA-approved, while the rest are used off-label. Recent research has suggested that oral minoxidil may be a safe and effective treatment for both female androgenetic alopecia (female AGA) and male androgenetic alopecia (male AGA). AREAS COVERED: In this review, we explore the pharmacokinetics, mechanism of action, safety, and efficacy of oral minoxidil. Additionally, we discuss its effectiveness compared to other treatments available for female AGA and male AGA. EXPERT OPINION: LDOM has demonstrated a favorable efficacy and safety profile in several trials. Subsequently, its use for the treatment of male AGA and female AGA is increasing. However, its use remains off-label, and through increased usage, we will get a better idea of the best dosage and monitoring guidelines. LDOM has also been used with some effectiveness in other forms of hair loss.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.028
GPT teacher head0.366
Teacher spread0.338 · 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 designOther design
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

Citations14
Published2024
Admission routes1
Has abstractyes

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