A 3D comparison of humeral head retroversion by sex and measurement technique
Bibliographic record
Abstract
Background Accurate humeral head reconstruction during shoulder arthroplasty is partially dependent on correctly estimating and replicating native version. The present study evaluated the effects of sex and measurement technique on three-dimensional (3D) humeral version measurements made using the transepicondylar, forearm and flexion–extension axes. Methods Fifty-two full-arm computed tomography scans were converted to 3D models and geometry extracted to define landmarks and coordinate systems. An anatomic humeral head osteotomy plane was used to measure version relative to the three measurement techniques and compare between sexes. Results The measurement technique used had a significant affect ( p < 0.001) on the resulting version measurement. The forearm axis technique consistently resulted in higher measured version compared to either the flexion–extension [mean (SD) males 9° (4°), females 13° (5°), p < 0.001] or the transepicondylar axes [mean (SD) males 8° (4°), females 11° (4°), p < 0.001]. Version in males was 7° greater than females when referencing either the flexion–extension [ p = 0.029; mean (SD) males 37.7° (11°), females 30.4° (13°)] or transepicondylar axes [ p = 0.045; mean (SD) males 39° (11°), females 32° (12°)]. Conclusions The choice of measurement technique can affect the humeral version angle. These results are important because measuring version using the epicondyles pre-operatively, and subsequently the forearm intra-operatively, will result in approximately 10° under-retroverted osteotomy. For example, 0° neutral version cut during reverse arthroplasty measured referencing the forearm results in 10° anteverted osteotomy when referencing the distal humerus.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".