Evaluation of the Effectiveness and Safety of Ultrasound-Guided Percutaneous Carpal Tunnel Release
Bibliographic record
Abstract
OBJECTIVE: The looped thread carpal tunnel release (TCTR) procedure is a minimally invasive percutaneous technique performed under ultrasound (US) to transect the transverse carpal ligament in patients with carpal tunnel syndrome. Study objectives were to evaluate the accuracy of identifying key US landmarks, safety, effectiveness, and technical difficulty of TCTR. DESIGN: Fourteen lightly embalmed cadaveric distal forearm-hand specimens were subject to US identification of key landmarks, TCTR procedure, and post-TCTR dissection. Outcome measures of interest were (1) correspondence between key landmarks (median nerve and 4 bony pillars of transverse carpal ligament) identified on US and anatomical structures exposed by dissection, (2) percentage of the transverse carpal ligament transected and location of the transection, (3) frequency of damage to adjacent structures, (4) time to complete procedure, and (5) operator assessment of technical difficulty of each TCTR procedure (0 = extremely easy, 10 = extremely difficult). RESULTS: (1) Skin markings delineating the position of US-visualized landmarks corresponded almost perfectly to anatomical dissection. (2) Nine (64.2%) of 14 specimens had complete division of the transverse carpal ligament. In the remaining 5 specimens, an average of 68.8% of the ligament was transected. (3) No adjacent structures were damaged. (4) Time to complete the procedure was on average 9.9 ± 4.6 minutes. (5) Average procedural difficulty was 4.3/10. CONCLUSIONS: Thread carpal tunnel release is potentially a safe, quick, and effective procedure to transect the transverse carpal ligament. Future clinical investigation is recommended.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".