Innervation of thumb carpometacarpal joint: implications for diagnostic block and denervation procedures
Bibliographic record
Abstract
INTRODUCTION: Osteoarthritis (OA) of the thumb carpometacarpal (CMC) joint is a common disorder that negatively impacts hand function. Denervation of the thumb CMC joint has emerged as a viable treatment option. However, the innervation pattern of the thumb CMC joint is controversial. Therefore, the objective of this study was to identify the articular branches supplying the thumb CMC joint and to document their relationship to anatomical landmarks to provide the foundation for image-guided diagnostic block and denervation procedures. METHODS: In 10 formalin-embalmed upper limb specimens articular branches supplying the thumb CMC joint were dissected from their origin to termination. A frequency map documenting the number of articular branches was generated. The frequency map enabled visualization and comparison of the relative area of innervation of the thumb CMC joint by each articular branch. RESULTS: The thumb CMC joint received innervation from six nerves. These were the deep branch of ulnar nerve (DBUN), dorsal articular nerve (DAN) of the first interosseus space, thenar branch of median nerve (TBMN), palmar cutaneous branch of median nerve (PCBMN), lateral antebrachial cutaneous nerve (LACN) and superficial branch of the radial nerve (SBRN) and/or their branches. Each nerve was found to innervate different aspects of the joint. The DBUN and DAN were found to innervate the posteromedial aspect of the thumb CMC joint, the TBMN and PCBMN anterior/anteromedial aspects, LACN posterolateral/lateral/anterior aspects and SBRN posterolateral/anterolateral aspects. CONCLUSIONS: The thumb CMC joint was innervated by articular branches originating from the SBRN, DAN, LACN, PCBMN, TBMN and DBUN. The documented anatomical relationships provide the foundation to inform selective diagnostic block and denervation of the thumb CMC joint. Further investigations are needed to assess the clinical implications of the current study.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".