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Record W4387542502 · doi:10.1159/000531890

Low-Dose Oral Minoxidil for Alopecia: A Comprehensive Review

2023· review· en· W4387542502 on OpenAlexaff
Aditya Gupta, Mesbah Talukder, Bianca Maria Piraccini, Antonellá Tosti

Bibliographic record

VenueSkin Appendage Disorders · 2023
Typereview
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsMinoxidilHypertrichosisMedicineHair lossSide effect (computer science)DermatologyHydroxycarbamideMale-pattern baldnessScalpPharmacologyInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

Low-dose oral minoxidil (LDOM) has demonstrated a promising safety and efficacy profile in the treatment of various hair disorders, including male androgenetic alopecia (AGA) and female-pattern hair loss (FPHL); however, it lacks FDA approval. The usual LDOM starting dose for male AGA is 1-5 mg/day, depending on physician preference and the patient's condition. For FPHL, it is 0.5-1 mg/day. The maximum dose is generally 5 mg/day. If patients respond well without major side effects, the dose may be gradually increased since the LDOM's efficacy appears to be dose-dependent. Patients may use LDOM long term if the treatment outcome is satisfactory. The common side effects of LDOM are hypertrichosis and cardiovascular symptoms. Females are more prone to hypertrichosis than males. The side effects of LDOM can be categorized as (a) dose-dependent type A side effects (hypertrichosis and cardiovascular symptoms) and (b) idiosyncratic type B side effects (pericardial effusion). Minoxidil acts via multiple pathways. Although minoxidil has a relatively short half-life of around 4 h, its hypotensive effect may last approximately 72 h. Effective treatments for alopecia are limited. Therefore, LDOM could be an important addition to the available therapies for managing some hair disorders, including AGA.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · 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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.080
GPT teacher head0.395
Teacher spread0.315 · 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 designNot applicable
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

Citations38
Published2023
Admission routes1
Has abstractyes

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