MétaCan
Menu
Back to cohort
Record W4404650597 · doi:10.1016/j.fjurol.2024.102716

Management of male posterior urethral stenosis following trauma and prostatic treatments, techniques and results

2024· review· en· W4404650597 on OpenAlexaboutno aff
L. Freton, François-Xavier Madec, Mathieu Fourel, B. Peyronnet, P. Neuville, F. Marcelli, N. Morel Journel, G. Karsenty

Bibliographic record

VenueThe French Journal of Urology · 2024
Typereview
Languageen
FieldMedicine
TopicUrological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Posterior Urethral Stenosis (PUS) is a surgical challenge. The aim of this article is to summarize current knowledge on the management of PUS. A comprehensive literature review was conducted using the PubMed database, covering the period from 2020 to 2023. To supplement this review, recommendations from the American Urological Association (AUA), European Association of Urology (EAU), and Canadian Urological Association (CUA), along with several key reference surgical guides, were incorporated. The collected data was then summarized by etiology to provide a detailed analysis. Pelvic Fracture Urethral Injury (PFUI) is a frequent complication of pelvic fractures. Treatments are well-established, including early realignment and excision-primary-anastomosis (EPA). Stenosis following treatment for benign prostatic hyperplasia (BPH) presents specific challenges due to the high risk of urinary incontinence. The management of post-prostatectomy stenoses stenosis depends on the stricture's location and may involve endoscopic treatment or complex reconstruction. Stenosis following radiotherapy presents additional complexity due to poor tissue quality. The impact on urinary and sexual function varies by etiology and must be considered when choosing a treatment approach. The management of PUS must consider the precise location and etiology of the stenosis. Treatment options vary from endoluminal techniques to open or robot-assisted reconstructions, chosen based on the patient's goals and overall health condition. Special attention must be given to the potential impact on urinary and sexual function. Les sténoses de l’urètre postérieur (SUP) constituent un défi chirurgical. Cet article vise à synthétiser les connaissances actuelles sur la prise en charge des SUP. Une revue exhaustive de la littérature a été effectuée en utilisant la base de données PubMed pour entre 2020 et 2023. Les recommandations de l’AUA, de l’EAU, de la CUA et plusieurs ouvrages de référence ont été utilisés pour compléter cette revue. Une synthèse par étiologie a été réalisée. Les SUP post-traumatique du bassin représentent une complication fréquente des fractures pelviennes. Les traitements sont bien codifiés : réalignement précoce, urétroplastie/résection-anastomose. Les sténoses post-traitement de l’hypertrophie bénigne de prostate, posent des défis particuliers en raison du risque élevé d’incontinence urinaire. La gestion des sténoses postprostatectomie radicale dépend de la localisation et peut inclure des traitements endoscopiques ou des reconstructions complexes. Les sténoses post-traitement physique présentent une complexité supplémentaire due à la faible qualité des tissus. L’impact sur la fonction urinaire et sexuelle varie en fonction de l’étiologie et doit être impérativement pris en compte dans le choix du traitement. La prise en charge d’une SUP doit tenir compte de la localisation exacte de la sténose et de son étiologie. Les options thérapeutiques vont des techniques endoluminales aux reconstructions ouvertes ou robot-assistées, choisies en fonction des objectifs du patient et de son état de santé général. Il faudra avoir une attention particulière aux impacts fonctionnels sur les fonctions urinaire et sexuelle.

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)0.005
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.041
GPT teacher head0.336
Teacher spread0.295 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe French Journal of UrologySame topicUrological Disorders and TreatmentsFrench-language works237,207