Ilioinguinal/iliohypogastric Nerve Blocks as a Treatment for Pelvic Pain in a Gynecologic Population [4R]
Bibliographic record
Abstract
INTRODUCTION: Ilioinguinal/iliohypogastric nerve blocks (IINBs) are a simple, minimally invasive option for managing pain associated with ilioinguinal/iliohypogastric neuropathy (IIN). This study assessed the safety and efficacy of IINBs in women with IIN associated pelvic pain. METHODS: A retrospective chart review of patients who received IINBs at The Ottawa Hospital between January 1st, 2012 and July 13th, 2017 by a single physician was performed. Patient demographics, history, examination findings, and block data were extracted. Chi-square and Mann-Whitney U tests explored differences in patient characteristics between women with and without effective response to IINBs. RESULTS: Amongst 106 meeting inclusion criteria, 381 IINBs were performed. Most women had a history of chronic pain (n=97,90%), endometriosis (n=69,65%), and/or lower abdominal surgery (n=95,90%). On examination, 56 women (53%) had tenderness within the IIN distribution, 59(56%) had point tenderness, 20(19%) had a positive Carnett’s sign, 21(20%) had allodynia, and/or 7(7%) had hyperalgesia. Data regarding effectiveness was available for 301/381 blocks. Of these, the majority (n=227,75%) greatly improved pain, 11%(n=33) somewhat improved pain, 10%(n=31) had no effect, and 3%(n=10) worsened pain. Sixty women (57%) had at least one block which greatly improved pain. Five women (5%) reported complications which could be directly related to blocks. No significant differences in patient characteristics were observed between women with and without effective response to IINBs. CONCLUSION: Ilioinguinal/iliohypogastric nerve blocks may provide pain relief for women with complex pelvic pain and features of central sensitization with a low rate of adverse events. Future prospective studies on IINB safety and efficacy are warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".