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Record W2038347355 · doi:10.1016/j.sexol.2011.08.014

Sexual dysfunction after surgical treatment of Peyronie's disease; Review article

2011· article· en· W2038347355 on OpenAlexaff
Raed Almannie, Serge Carrier

Bibliographic record

VenueSexologies · 2011
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsMcGill UniversityRoyal Victoria Regional Health CentreRoyal Victoria Hospital
Fundersnot available
KeywordsPeyronie's diseaseMedicineErectile dysfunctionIncidence (geometry)DiseaseSexual dysfunctionSurgeryPatient satisfactionInternal medicine

Abstract

fetched live from OpenAlex

To determine the incidence of sexual dysfunction following surgical repair of Peyronie's disease. Literature review was done on surgical treatment of Peyronie's disease and its complications. Surgical treatment of peyronie's disease could result in different forms of sexual dysfunction including penile shortening, residual curve, erectile dysfunction, and altered sensation. The incidence of these complications depends on the type of surgical approach, with grafting procedures having the highest incidence. Treatment of sexual dysfunction following surgical treatment of peyronie's disease is similar to non-peyronie's patients in most cases. Patient satisfaction is affected by many factors with realistic expectations being the most important. Sexual dysfunction following surgical treatment of peyronie's disease is not a rare event, especially after grafting procedures. Physicians should be aware of the incidence of these complications and their treatments, this is important for preoperative counselling of patients. Improper counselling can lead to unrealistic expectation, which in turn affect patient satisfaction. We recommend standardisation of the definitions of these complications.

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)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.092
GPT teacher head0.315
Teacher spread0.223 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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