Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Time of Effect Onset in Treating Overactive Bladder or Non Obstructive Urinary Retention by Sacral Neuromodulation

Maastricht University Medical Center · 2014
ClinicalTrials.gov · Datasets · License: Public Domain · 2014
Open Source ↗
na
Sacral neuromodulation (SNM) is a minimally invasive secondary treatment for overactive bladder syndrome (OAB) or for non-obstructive urinary retention (NOR), when refractory to conservative treatment. Success rates range from 70 to 80%, and good long-term results are reported. The working mechanism of SNM is not completely understood, and the only prognostic factor for good response to this treatment is a successful test stimulation period. There is no consensus on the duration of this test stimulation period. The experience in our clinic during test stimulation period is that for responders it takes up to one week to achieve maximal effect, after the system is turned 'on'. On the other hand the investigators notice that after turning the neuromodulation system 'off', it will take a few hours for symptoms to return to the baseline situation. The fact is: no information concerning the so called "time of onset" and "time of offset" (or popular called: wash-in / wash-out) of sacral neuromodulation is available in current literature.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 830603
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive