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Record W2110210123 · doi:10.1517/14656566.2014.873789

Alprostadil for the treatment of impotence

2013· review· en· W2110210123 on OpenAlexaboutno aff
Vishwanath Hanchanale, Ian Eardley

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2013
Typereview
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineErectile dysfunctioncGMP-specific phosphodiesterase type 5SildenafilTadalafilFirst lineIntensive care medicinePharmacologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Erectile dysfunction (ED) affects over 150 million men worldwide. Oral phosphodiesterase-5 (PDE5) inhibitors are currently used as a first-line therapy and a second-line therapy with either intracavernosal (Caverject) or intraurethral (MUSE) alprostadil is required for a few men who show poor response or intolerance to PDE5 inhibitors. AREAS COVERED: This article reviews the pharmacology, pharmacokinetics, medical applications, efficacy and safety of alprostadil in the treatment of men with ED. The goal of this article is to review the currently published clinical data of alprostadil to establish its potential role in managing men, in particular, those who fail to respond to traditional PDE5 inhibitors. Relevant articles and abstracts were reviewed from PUBMED and conference proceedings. EXPERT OPINION: Alprostadil, a synthetic form of prostaglandin E1, is used as second-line therapy in managing men with ED. It has a unique role in men with ED secondary to diabetes and ED secondary to radical pelvic surgery (e.g., radical prostatectomy). In view of these new indications, the role of alprostadil is being redefined. Both intracavernosal and intraurethral alprostadil are approved for use in all countries, and following positive results from recent Phase III trials, topical alprostadil has gained approval in Canada.

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 score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.277
GPT teacher head0.504
Teacher spread0.227 · 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

Citations58
Published2013
Admission routes1
Has abstractyes

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