PD20-09 ONOBOTULIUMTOXIN A VERSUS KENALOG FOR INTRAVAGINAL TRIGGER POINT INJECTIONS IN THE TREATMENT OF CHRONIC PELVIC PAIN
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Résumé
You have accessJournal of UrologySexual Function/Dysfunction: Female (PD20)1 Apr 2019PD20-09 ONOBOTULIUMTOXIN A VERSUS KENALOG FOR INTRAVAGINAL TRIGGER POINT INJECTIONS IN THE TREATMENT OF CHRONIC PELVIC PAIN Jamie Bartley*, Laura Nguyen, Deborah Hasenau, Jason Gilleran, Larry Sirls, Esther Han, Lauren Tenneyson, and Kenneth Peters Jamie Bartley*Jamie Bartley* More articles by this author , Laura NguyenLaura Nguyen More articles by this author , Deborah HasenauDeborah Hasenau More articles by this author , Jason GilleranJason Gilleran More articles by this author , Larry SirlsLarry Sirls More articles by this author , Esther HanEsther Han More articles by this author , Lauren TenneysonLauren Tenneyson More articles by this author , and Kenneth PetersKenneth Peters More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555741.75359.15AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Chronic pelvic pain in women is often due to pelvic muscle dysfunction and hypertonicity. In this study we compared outcomes of patients with chronic pelvic pain undergoing transvaginal trigger point injections (TPI) with triamcinolone (steroid) vs. onabotulinumtoxinA (Botox). METHODS: A prospective double-blind study was conducted. Patients were randomized (1:1) to receive in-office pelvic floor muscle injections with either a mixture of triamcinolone and ropivacaine followed by saline or injections of ropivacaine followed by a mixture of Botox 200 units and saline. Three bilateral injections were performed on each side of the pelvic floor. Statistical analysis compared the treatment groups at baseline and 1-month, 3-month and 6-month post-injection. RESULTS: Twenty-one patients underwent TPI (11 steroid, 10 Botox). Primary diagnosis included myalgia, urinary system related symptoms, muscle spasms, and chronic pelvic pain. There was no statistical difference in baseline demographics or prior treatment. The median pre-injection pain score for the Steroid group was lower than the Botox group (5 (range: 4-7) vs 6 (range: 5-8), respectively; p= 0.015). At 1 month, there was no difference in median Numerical Rating Scale (NRS) pain scores between groups; Steroid: 5 (range 3-8, n=10) vs. Botox: 4.5 (range 2-7, n=9); p = 0.82. The change in median NRS scores between 1 month and baseline was no different between groups (Steroid: -1 (range -2 to +3) vs. Botox: -2 (range -4 to 0); p = 0.072. The numbers for 3 and 6 months were too small for comparison but are presented in Table 1. There is no difference between groups at baseline or at one month follow up on Brief Pain Inventory (BPI) measures or GRA measures. 90% (Steroid) and 89% (Botox) at 1month and 100% at 3 and 6 months (both groups) would recommend the same TPI to a friend. Regardless of the initial treatment received, approximately 40% of the patients from each group elected to receive steroid TPI at 1-month follow-up. CONCLUSIONS: There was no difference in NRS pain scores at 1 month in patients that received TPI with triamcinolone compared to Botox. Patients in both groups would recommend TPI equally to a friend. Source of Funding: Allergan and Beaumont, Department of Urology, Philanthropy Lansing, MI; Hamilton, Canada; Royal Oak, MI© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e380-e381 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jamie Bartley* More articles by this author Laura Nguyen More articles by this author Deborah Hasenau More articles by this author Jason Gilleran More articles by this author Larry Sirls More articles by this author Esther Han More articles by this author Lauren Tenneyson More articles by this author Kenneth Peters 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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,001 |
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 ».