Bilateral Suprascapular Nerve Cryoneurolysis for Pain Associated With Glenohumeral Osteoarthritis: A Case Report
Bibliographic record
Abstract
Osteoarthritis is a leading cause of disability, typically treated with exercise, analgesics, injections, or surgeries. Cryoneurolysis is an established technique for the treatment of pain, including osteoarthritis that may provide an alternative for patients in whom surgery is not appropriate and conservative measures have failed. We present our experience with a 78-year-old man with severe pain from bilateral glenohumeral osteoarthritis. Their condition is complicated by several concurrent diagnoses, leaving them ineligible for surgical intervention, despite pharmacologic treatments proving insufficient to manage their pain. As an alternative, bilateral cryoneurolysis of the suprascapular nerve was performed at the suprascapular notch. Pain and disability scores both lessened on the Brief Pain Inventory Score, Disabilities of the Arm Shoulder and Hand (change of 9 points after 170 days) as well as the Shoulder Pain and Disability Index (change of 19 points after 170 days). The patient had improved active and passive range of motion for flexion, abduction, and external rotation of the shoulder. Improvements endured to follow-up at 170 days. There were no negative side effects as a result of the procedure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".