PD24-10 EVALUATION OF THE LEARNING CURVE FOR THULIUM LASER TRANSURETHRAL VAPORESECTION OF THE PROSTATE (THUVARP)
Notice bibliographique
Résumé
You have accessJournal of UrologyBenign Prostatic Hyperplasia: Surgical Therapy & New Technology II1 Apr 2016PD24-10 EVALUATION OF THE LEARNING CURVE FOR THULIUM LASER TRANSURETHRAL VAPORESECTION OF THE PROSTATE (THUVARP) Ala'a Sharaf, jo worthington, and Hashim Hashim Ala'a SharafAla'a Sharaf More articles by this author , jo worthingtonjo worthington More articles by this author , and Hashim HashimHashim Hashim More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2016.02.1775AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Transurethral resection of the prostate (TURP) has been the standard operation for voiding LUTS for 40 years with very few changes. It is generally a very successful operation but has well documented risks for the patient. Various laser techniques have become available but none have become widely used in the National Health Service (NHS) because of lengthy training required for surgeons or inferior performance on clinical outcomes. The thulium laser technique (ThuVARP) vaporises and resects the prostate using a surgical technique similar to TURP, facilitating a potentially shorter training period for surgeons. A systematic review of laser technology recently recommended ThuVARP as an acceptable alternative to TURP for the treatment of symptomatic benign prostatic obstruction (BPO). For patients undergoing BPO surgery, NICE clinical guidelines recommended offering TURP or holmium laser enucleation (HoLEP). However, HoLEP is only used in a few centres due to the steep learning curve. The Objective was to assess the surgical learning curve of ThuVARP, as part of a prospective, randomised, multicentre, controlled trial to determine the clinical and cost effectiveness of ThuVARP versus TURP in the NHS (UNBLOCS trial). METHODS The UNBLOCS trial is funded by the NIHR HTA program. Consultant urologists were mentored to perform ThuVARP. All participating surgeons observed the chief investigator performing 1 to 2 cases. The lead surgeon then observed the principal investigators (PIs) performing 2 to 5 cases. The surgeons then performed cases without supervision. Competency was assessed with the Intercollegiate Surgical Curriculum Programme work-based assessments (ISCP-WBA) by an independent assessor and the PIs were signed off once the competency criteria were met. RESULTS A total of 9 surgeons were involved form 6 different centres (3 district general hospitals and 3 tertiary referral centres). All of the surgeons have performed at least 150 TURPs. A mean of 2.1 cases were observed by each surgeon and a mean of 2.2 cases were performed by each surgeon under supervision. A mean of 7 cases were performed by the PIs before being signed off as competent. CONCLUSIONS The study has shown that ThuVARP has a short learning curve not exceeding 12 cases for surgeons already experienced in performing TURPs. Results of the non-inferiority trial are awaited to see if outcomes are comparable to TURP, making it a feasible alternative with a short learning curve. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e515 Advertisement Copyright & Permissions© 2016MetricsAuthor Information Ala'a Sharaf More articles by this author jo worthington More articles by this author Hashim Hashim More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,043 | 0,182 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,005 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,034 | 0,009 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».