PD20-09 ONOBOTULIUMTOXIN A VERSUS KENALOG FOR INTRAVAGINAL TRIGGER POINT INJECTIONS IN THE TREATMENT OF CHRONIC PELVIC PAIN
Bibliographic record
Abstract
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 ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".