Sonographic Appearance of the Posterior Interosseous Nerve at the Wrist
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to determine whether sonography can identify the distal posterior interosseous nerve at the wrist. METHODS: On the basis of previous anatomic descriptions, high-resolution musculoskeletal sonography was used in an attempt to identify the distal posterior interosseous nerve in the wrists of 20 unembalmed cadaveric specimens (11 male and 9 female; ages 54-98 years). High-frequency scanning (17-5 MHz) of the fourth dorsal extensor compartment revealed a small (1-3 mm) hypoechoic structure located on the compartment floor, presumed to represent the posterior interosseous nerve. Electronic calipers measured the distance between Lister's tubercle and this structure, as well as the structure's radial-ulnar width and volar-dorsal height. The presumed posterior interosseous nerves of 10 specimens were then injected with diluted colored latex using sonographic guidance. Subsequent dissection definitively identified the sonographically visualized and injected structure. RESULTS: Dissection revealed latex within the posterior interosseous nerve in all 10 injected specimens, thus confirming that the sonographically visualized structure represented the distal posterior interosseous nerve. The nerve was identified sonographically in all 20 examined specimens, was located an average of 4.88 mm (range, 2.10-10.0 mm) ulnar to Lister's tubercle, and had an average width and height of 2.35 mm (range, 1.20-3.50 mm) and 1.01 mm (range, 0.80-1.40 mm), respectively. CONCLUSIONS: High-resolution sonography can reliably identify the distal posterior interosseous nerve within the fourth dorsal extensor compartment. Clinicians should consider formal evaluation of the posterior interosseous nerve in patients presenting with dorsal wrist pain syndromes. Future investigations should explore the potential role of sonographically guided percutaneous procedures directed at the posterior interosseous nerve.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".