Humeral head subluxation in Walch type B shoulders varies across imaging modalities
Bibliographic record
Abstract
Background The Walch type B pattern of glenohumeral osteoarthritis is characterized by posterior humeral head subluxation (PHHS). At present, it is unknown whether the percentage of subluxation measured on axillary radiographs is consistent with measurements on 2-dimensional (2D) axial or 3-dimensional (3D) volumetric computed tomography (CT). The purpose of this study was to evaluate PHHS across imaging modalities (radiographs, 2D CT, and 3D CT). Methods A cohort of 30 patients with Walch type B shoulders underwent radiography and standardized CT scans. The cohort comprised 10 type B1, 10 type B2, and 10 type B3 glenoids. PHHS was measured using the scapulohumeral subluxation method on axillary radiographs and 2D CT. On 3D CT, PHHS was measured volumetrically. PHHS was statistically compared between imaging modalities, with P ≤ .05 considered significant. Results The mean PHHS value for the entire group was 69% ± 24% on radiographs, 65% ± 23% with 2D CT, and 74% ± 24% with 3D volumetric CT. PHHS as measured on complete axillary radiographs was not significantly different than that measured on 2D CT ( P = .941). Additionally, PHHS on 3D volumetric CT was 9.5% greater than that on 2D CT ( P < .001). There were no significant differences in PHHS between the type B1, B2, and B3 groups with 2D or 3D CT measurement techniques ( P > .102). Conclusion Significant differences in PHHS were found between measurement techniques ( P < .035). A 9.5% difference in PHHS between 2D and 3D CT can be mostly accounted for by the linear (2D) vs. volumetric (3D) measurement techniques (a linear 80% PHHS value is mathematically equivalent to a volumetric PHHS value of 89.6%). Surgeons should be aware that subluxation values and therefore thresholds vary across different imaging modalities and measurement techniques.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".