Carpal tunnel volume distribution and morphology changes with flexion-extension and radial-ulnar deviation wrist postures
Bibliographic record
Abstract
Non-neutral wrist postures have been reported to cause decreased carpal tunnel volume (CTV) contributing to impingement of the median nerve and development of carpal tunnel syndrome. Recent analysis found CTV did not change with ±20° flexion-extension (FE), however, CTV decreased with ulnar deviation over the range of -5° to 15° radial-ulnar deviation (RUD). These findings suggest CTV may be too coarse of a measure to reflect the effects of slight non-neutral postures, or that volume is conserved and redistributed due to changes in tunnel morphology with posture. The objective of this study was to assess volume distribution along the length of the carpal tunnel and to quantify regional morphology changes with deviated wrist postures in both FE and RUD. Analysis was performed on a dataset of computed tomography scans collected on ten cadaveric specimens (5 male, 5 female, mean age = 80.7 ± 10.9 years) over a range of FE and RUD postures. The carpal tunnel of each scan was divided into four quartiles of equal length along the tunnel to quantify volume distribution. Volume within the carpal tunnel was seen to redistribute with both FE and RUD. Decreased volume in the distal aspect of the tunnel with flexion and proximal aspect of the tunnel with ulnar deviation may contribute to localized compression of the medial nerve. Measures of mean cross-sectional area, width and depth by quartile provided an indication of the morphology changes associated volume redistribution. Morphology analysis also revealed twisting between the proximal and distal aspects of the tunnel which increased with flexion and ulnar deviation and may further contribute to strain on the median 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".