Chronic Rupture of the Pectoralis Major: Current Concepts and Various Surgical Repair Techniques – A Mini Review
Bibliographic record
Abstract
Introduction: Various surgical repair techniques, including autograft and allograft reconstructions, have been reported for the management of chronic pectoralis major ruptures, but outcome reporting remains highly heterogeneous. This narrative review aimed to provide a deeper understanding of these techniques, emphasizing the need for larger-scale prospective trials to support evidence-based recommendations for surgeons. Materials and Methods: We conducted a search of PubMed/Medline, Cochrane Library, Embase, and Google Scholar for English-language articles published between 1822 and 2023, using the following keywords: "chronic pectoralis major ruptures," "chronic pectoralis major tears," and "patient outcomes." Results: Overall, more than 60 reported cases were retrieved, along with a few prospective studies and review articles. Based on the compiled literature, most pectoralis major tears tend to arise at the tendo-osseus junction. In the absence of contra-indications such as old age and multiple comorbidities, surgical intervention is considered the golden care standard. The most commonly performed repair techniques include suture anchor fixation, transosseous fixation (TOS), and cortical bone fixation. Among the three techniques, no significant differences in cyclic loading or load-to-failure properties of the constructs were recorded. In chronic cases, in which direct repair is not possible, various autograft and allograft reconstructions were described, with quite heterogeneous outcome reporting, rendering comparative analyses difficult. Conclusion: Currently, no single technique has been established as the gold standard for the treatment of chronic pectoralis major ruptures. The most commonly performed repair techniques include suture anchor fixation, TOS, and cortical bone fixation. In chronic cases where direct repair is not feasible, various autograft and allograft reconstructions are employed. There is a need for larger-scale prospective trials with standardized outcome reporting to develop evidence-based recommendations, providing surgeons with safe and effective guidelines for treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".