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Record W2344226244 · doi:10.1016/j.jsxm.2016.03.093

PS-08-016 Can Intracavernosal Botulinum Toxin Injection Salvage Vascular Erectile Dysfunction Patients Not Responding to Oral and Intracavernous Therapy? A Pilot Study

2016· article· en· W2344226244 on OpenAlexaff
H Ghanem, Islam F. Soliman, Myrurgia A. Abdul‐Hamid, Rany Shamloul

Bibliographic record

VenueThe Journal of Sexual Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineErectile dysfunctionPapaverineBotulinum toxinShim (computing)Intracavernous injectionSurgeryPhentolamineUrologyAnesthesiaSalinePenis

Abstract

fetched live from OpenAlex

Evidence has been arising suggesting that Botulinum toxin type A (BTX-A) injections can relax smooth muscles fibers in the treatment of obesity and Detrusor muscle over-activity. We investigate whether a similar effect on cavernosal smooth muscles would help in the treatment of erectile dysfunction (ED) resistant to oral and intracavernous (IC) therapy, thus avoiding surgical treatment options. 24 patients with vascular ED, who failed treatment with non-surgical options, were randomized into 2 equal treatment and control groups. Ethics committee approval and informed consent were obtained. Both groups underwent penile color Doppler evaluation to confirm a vascular etiology. A trimix solution (PGE1 10 ug + Phentolamine 1 mg + Papaverine 30 mg) was injected IC during the penile Doppler study. The treatment group received a single IC injection of BTX-A 50 units 1 day after the penile Doppler/trimix test. The control group received an IC 1 ml saline injection. Assessment for both groups was done by penile color Doppler exam and erection hardness score (EHS) pre-treatment and 2 weeks after treatment. SHIM, and SEP 1 & 2 were completed before treatment and 4 weeks after treatment.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.277
Teacher spread0.246 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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