Anatomical study of the innervation of the posterior elbow joint capsule: implications for ultrasound-guided peripheral nerve block and radiofrequency ablation procedures
Bibliographic record
Abstract
INTRODUCTION: Ultrasound-guided peripheral nerve block and radiofrequency ablation have been developed for pain management in various joints including the hip, knee and shoulder, but not the elbow. Precise three-dimensional (3D) localization of the articular branches and landmarks visible on ultrasound are needed. The objectives of this anatomical study were to determine the presence, course, frequency, landmarks and areas innervated by the articular branches supplying the posterior elbow joint. METHODS: In 12 upper extremity specimens, articular branches to the posterior elbow joint were dissected from brachial plexus to termination. Origin, course, frequency, capsular distribution and landmarks were documented. Data were reconstructed into 3D models and a 3D frequency map to visualize spatial relationships between the articular branches, capsule and landmarks. RESULTS: The superior part of the posterior capsule was innervated by the ulnar collateral nerve (92%) and lateral branch to triceps (100%). The lateral part was supplied by the nerve to anconeus (100%) and, when present, branch to extensor carpi ulnaris (58%). The medial part was supplied by the ulnar nerve through direct branches (92%) and branches to forearm flexors (100%). The medial and posterior antebrachial cutaneous nerves supplied the medial and lateral epicondylar areas, respectively (100%, 83%). Common landmarks included the epicondyles, olecranon, olecranon fossa, and margins of triceps. CONCLUSIONS: The 3D data of the articular branches supplying the posterior elbow joint provide an anatomical basis for the development of peripheral nerve block and radiofrequency ablation protocols to treat elbow joint pain. Further anatomical and clinical studies are necessary to identify target sites and evaluate the proposed landmarks in vivo.
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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 | 0.002 |
| 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) | 0.002 | 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".