Pectoralis Major Ruptures: Tear Patterns and Patient Demographic Characteristics
Bibliographic record
Abstract
BACKGROUND: The pectoralis major (PM) is made up of multilaminar muscle segments that form a complex insertion on the proximal humerus; it is composed of an anterior and a posterior tendon layer. The tear patterns and patient characteristics of operatively treated PM ruptures in the general population remain poorly understood. PURPOSE: To comprehensively report the demographic characteristics of patients who are clinically diagnosed with structurally significant PM ruptures and to describe PM tear patterns identified during surgery. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: A retrospective analysis of surgically treated PM tears was performed for a single-surgeon case series between January 1, 2003, and November 1, 2017. Patient demographic characteristics, classification of tear pattern, and treatment (repair/reconstruction) were recorded. RESULTS: A total of 104 surgical cases of PM tendon rupture were identified; 100 patients underwent primary repair and 4 underwent dermal allograft reconstruction. All patients were male, with a mean age of 36.5 ± 9.2 years. Chronic tears (>6 weeks old) accounted for 63.6% of surgical cases, and 96% (n = 100) of tears occurred at or between the musculotendinous junction and tendinous insertion. A partial-thickness, complete-width tear of the posterior tendon layer at this same location was the most common tear pattern identified. CONCLUSION: PM ruptures occurred almost exclusively at or between the musculotendinous junction and tendinous insertion, with predominant involvement of the posterior tendon layer. Chronic tears can be safely treated with primary repair in the vast majority of cases.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".