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Record W3013540815 · doi:10.1097/mou.0000000000000760

Evaluating collagenase Clostridium histolyticum administration protocols in the treatment of Peyronie's disease

2020· review· en· W3013540815 on OpenAlexaff
Drew Phillips, Justin Y.H. Chan, Ryan Flannigan

Bibliographic record

VenueCurrent Opinion in Urology · 2020
Typereview
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicinePeyronie's diseaseClinical trialRandomized controlled trialFood and drug administrationDiseaseIntensive care medicineSurgeryInternal medicinePharmacology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Treatment of Peyronie's disease with collagenase Clostridium histolyticum (CCh) has gained world-wide adoption following the phase III clinical trials IMPRESS I and II. However, the optimal treatment parameters remain largely unknown. Many groups have made modifications to CCh treatment in Peyronie's disease in recent years. This review aims to discuss the variations in CCh treatment reported and associated outcomes. RECENT FINDINGS: Variations in CCh treatment protocols include administering higher CCh doses (0.9 mg) less frequently (q1month), use of home penile modeling, use of angulating penile traction devices, and vacuum therapy devices. Authors have reported different injection techniques to include three-point fans and tunneling techniques. Patient selection has expanded to include and evaluate responses among men with some extent of plaque calcification, and ventral curves. SUMMARY: Since publication of the IMPRESS trials, several variations of CCh treatment have been reported with similar treatment responses to the original trials. However, future studies are required with prospective, randomized comparative designs to identify the optimal treatment strategies for men with Peyronie's disease.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.431
GPT teacher head0.542
Teacher spread0.111 · 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 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

Citations3
Published2020
Admission routes1
Has abstractyes

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