MP67-12 ASSOCIATION OF BUCCAL MUCOSAL GRAFT HISTOLOGY AND MOUTH ANATOMY TO BULBAR URETHROPLASTY GRAFT TAKE AND FACIAL MORBDITY
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Résumé
You have accessJournal of UrologyTrauma/Reconstruction/Diversion: Urethral Reconstruction (including Stricture, Diverticulum) III (MP67)1 Apr 2019MP67-12 ASSOCIATION OF BUCCAL MUCOSAL GRAFT HISTOLOGY AND MOUTH ANATOMY TO BULBAR URETHROPLASTY GRAFT TAKE AND FACIAL MORBDITY Shyam Sukumar*, Cooper Benson, Debduth Pijush, Carlos Pagan, and Steven Brandes Shyam Sukumar*Shyam Sukumar* More articles by this author , Cooper BensonCooper Benson More articles by this author , Debduth PijushDebduth Pijush More articles by this author , Carlos PaganCarlos Pagan More articles by this author , and Steven BrandesSteven Brandes More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000557007.54803.62AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Buccal mucosal grafts (BMGs) are the standard graft material for urethroplasty. Graft take is dependent on a proper host bed and graft. Quality of BMGs can be variable. A leak on post op voiding cystourethrography (VCUG)is believed to be from poor graft take. The effect of BMG histology or oral health or graft take is unknown. The role of oral health or mouth dimensions on postoperative facial morbidity is unknown. METHODS: Prospective review of 10 patients undergoing augmentation urethroplasty with BMG for bulbar strictures. Pre-op and post-op day 1 and 3 wks, patients completed oral health questionnaires: The Kayser-Jones Brief Oral Health Status Exam (BOHSE), McGill Pain Questionnaire (McGill),Oral Health Impact Profile Questionnaire (OHIP 14), and Oral Patient Reported Outcomes Measures(PROMS). Mouth dimensions and measurements were also obtained. Post-op VCUGs were evaluated for leak at 3 weeks. Histology of harvested BMGs were assessed by staff pathologist (CAP) using calibrated eyepiece to measure thickness of each anatomic layer, and grade the graft by a validated oral mucosal inflammation and ulceration index (Oral Mucositis Index). RESULTS: Mean age 38.7yrs, Q max 6.1 ml/s, IPSS 22, SHIM 17. Types of urethroplasty: Palmintieri double buccal urethroplasty-3, dorsal onlay with ventral inlay-1, combined ventral bulbar BMG with dorsal penile BMG-1, dorsal BMG-2, augmented anastomotic-2, Asopa-1. Mean pre-op oral health scores were low or normal. Mean McGill and Oral PROMS scores at POD 1, 2.1 and 2.0, and at 3 weeks, 17.9 and 17.7, respectively. Mean pre-op mouth dimensions: opening, 4.9 cm (4.5-6.0) and commissure to TMJ length- 4.1 cm (3.5-8). Mean size of BMG harvested = 4.8 x 1.6 cm, and on stretch 5.4 x 2.0 cm; mean delta 9.8% (0-28%)and 18.1%(0-34%),respectively. Patients with the highest pain and oral PROMS scores post op had bilateral BMGs or the smallest mouth opening and shortest length. Mean microscopic thickness of each layer of BMG: epithelium- 692µ(500-1200), lamina propria- 97µ(50-200), and submucosa-1093 µ(400-1900). Average mucositis score 2.9(0-11)and BMG friability - 2 (1-3). The patient with a VCUG leak had the highest mucositis index score, lowest SHIM and thickest submucosa. CONCLUSIONS: Harvested BMG vary in quality as to elasticity, thickness, friability and histology. Smaller mouth dimensions appear to be associated with worse post-operative morbidity and pain. Worse BMG histology as to mucositis and submucosa thickness appear to negatively affect graft take. A larger multi-institutional study is currently underway. Source of Funding: NONE New York, NY; New Orleans , LA; New York, NY© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e972-e972 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Shyam Sukumar* More articles by this author Cooper Benson More articles by this author Debduth Pijush More articles by this author Carlos Pagan More articles by this author Steven Brandes More articles by this author Expand All 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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,166 | 0,032 |
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 ».