Feasibility of Real-Time Ultrasound for Pudendal Nerve Block in Patients with Chronic Perineal Pain
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Compared with conventional fluoroscopic-guided pudendal nerve block, ultrasonography has potential advantages for visualizing anatomical landmarks such as the internal pudendal artery and nerve, the sacrospinous and sacrotuberous ligaments, and local anesthetic spread. We examined the clinical utility of performing pudendal nerve block under real-time ultrasound guidance. METHODS: Seventeen patients were studied. With the patient lying prone, a 2 to 5 MHz curved array ultrasound probe was placed at the level of the ischial spine to capture the transverse view of the ischial spine, the sacrospinous and sacrotuberous ligaments (SSL and STL), the internal pudendal artery (confirmed with color Doppler), and the pudendal nerve. A 22-gauge needle was advanced under real-time ultrasound guidance to reach the pudendal nerve in the plane between the STL and SSL. Following confirmation of spread of dextrose 5% solution in the interligamentous plane, a mixture of 5 mL 0.25% bupivacaine with 1:200,000 epinephrine and 40 mg Depo-Medrol (Pharmacia & Upjohn, Kalamazoo, MI) was injected. Assessment included the ease of identification of anatomical structures and local anesthetic spread with ultrasound, and the degree of sensory block in the perineum. RESULTS: The ischial spine, SSL, STL, internal pudendal artery, and pudendal nerve were easily identifiable with ultrasound in the majority of patients. Local anesthetic spread was seen as a hypoechoic collection around the nerve and expanding between the STL and SSL. All patients developed perineal sensory block following the procedure. CONCLUSIONS: Pudendal nerve block at the ischial spine level can be reliably performed under real-time ultrasound guidance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".