Observational studyJSLS : Journal of the Society of Laparoendoscopic Surgeons
A Pain Desensitization Algorithm for Phenotyping and Treating Chronic Pelvic Pain.
Observational study in JSLS : Journal of the Society of Laparoendoscopic Surgeons. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Pathophysiology and potential multimodal therapeutic strategies for IC/BPS.Nature reviews. Urology · 2025Review
- Cervical Tenderness (Parametropathy) is a Diagnostic Tool for the Chronic Pelvic Pain Syndrome.Pain and therapy · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chronic pelvic pain remains challenging for physicians to manage due to central and peripheral sensitization and multiple pain generators including the bladder, pelvic floor, and pudendal nerve. Pain management providers have used nerve blocks for years for diagnosis and treatment. We developed a desensitization algorithm that provides a stepwise approach to improve patients pain scores. Methods: This is a prospective observational cohort study of 182 women aged 15-90 years old with chronic pelvic pain using an algorithm from 2016 to 2018. Treatment started with an Anesthetic Challenge Test of the bladder to guide us through a protocol of intravesical therapy and/or pudendal nerve blocks as a second step. Results: ACT POSITIVE patients, who received intravesical therapy: 84% had a Visual Analog Score pain improvement of at least 50%, 64% improved at least 80% (41% pain-free). Those desiring additional relief that received further Pudendal Blocks: 83% had final improvement of at least 50% (67% pain-free). ACT NEGATIVE patients received Pudendal Blocks with 80% of subjects achieving at least 50% relief, 65% improved at least 80% (35% pain-free). All final groups showed a statistically significance of Conclusion: Management of women with chronic pelvic pain would ideally start with treating a specific diagnosis which, in most cases, is difficult to establish since the majority have more than one pain generator. Our algorithm simplified the approach and reduced the severity of pain scores prior to any further necessary surgical interventions.
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