Radiographic Study of Humeral Stem in Shoulder Arthroplasty After Lesser Tuberosity Osteotomy or Subscapularis Tenotomy
Bibliographic record
Abstract
Lesser tuberosity osteotomy (LTO) and subscapularis tenotomy (ST) are used for takedown of the subscapularis during shoulder arthroplasty. LTO offers the theoretical but unproven benefit of improved healing and function of the subscapularis. However, humeral stem subsidence and loosening may be greater when osteotomy is performed, which may compromise functional outcomes. Our hypothesis is that no difference in proximal collar press-fit humeral stem subsidence or loosening exists, with no impairment of functional outcomes using the LTO technique. Radiographs of 39 shoulders from 35 patients who underwent shoulder arthroplasty with a minimum of 1 year of radiographic follow-up were included in the study cohort. All patients received the same press-fit implant (Bigliani-Flatow; Zimmer Biomet). We collected data including demographic information; radiographic measurements, including humeral-acromial distance (HAD); subsidence; subluxation index; the presence of lucent lines >2 mm; and functional outcome scores using the Western Ontario Osteoarthritis of the Shoulder Index, the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire, and the Constant score. Subsidence was 2.8 ± 3.1 mm for LTO vs 2.5 ± 3.1 mm for ST (P = .72). HAD did not differ between the LTO and ST groups preoperatively (9.5 ± 2.4 mm vs 10.9 ± 2.7 mm, P = .11). The first postoperative and final follow-up films for HAD for the LTO and ST groups showed a statistically significant difference (first postoperative film, 11.9 ± 3.7 mm vs 15.9 ± 4.5 mm, P = .005; final follow-up film, 11.8 ± 3.2 mm vs 14.5 ± 3.9 mm, P = .03). We identified no differences in subsidence, lucent lines >2 mm, posterior subluxation, and Constant, and DASH functional outcome scores for patients undergoing total shoulder arthroplasty via the LTO vs ST techniques with the same proximal collar press-fit humeral stem at short-term follow-up.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".