High-Frequency Accessory and Transcapular Nerve Blocks in the Management of Fibromyalgia: A Case Report
Bibliographic record
Abstract
This is the first case report describing the effect of weekly accessory nerve and transcapular nerve blocks for managing fibromyalgia (FM)-related pain in a 45-year-old female patient. The diagnosis was established using the new American College of Rheumatologist criteria. Following diagnosis, bilateral accessory and transcapular nerve blocks were administered using Xylocaine. In this particular patient, the nerve blocks decreased the numeric rating scale from 9 to 2 after treatment in the same visit, improved the benefits of daily activities, and improved tolerance of physical activities in six months. The patient reported significant improvement in pain, supporting the hypothesis that interventional management, like nerve blocks, may reduce peripheral nociceptive input and mitigate central sensitization, a hallmark of FM. The findings of this case report suggest that targeted nerve blocks can serve as a complementary treatment for FM-related neck and shoulder pain, particularly in cases involving myofascial trigger points in the trapezius and infraspinatus muscles. By integrating accessory and transcapular nerve blocks with existing multidisciplinary management approaches, clinicians can offer more options for pain management for FM patients with neck and shoulder pain. However, future randomized controlled trials are essential for cause-effect relationships and optimizing nerve block treatment protocols to support evidence-based practices and better patient outcomes.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".