Canadian Athletic Therapists Association Conference, May 9–11, 2024, Ottawa, Ontario, Canada
Bibliographic record
Abstract
Context: Partial thickness rotator cuff tears (PTRCTs) are complicated because they are not a single entity and represent a spectrum of disease states.Although relatively few natural history and progression studies are available, there is a substantial body of low-level clinical evidence to suggest that most PTRCTs lack self-healing.Optimal treatment of PTRCTs is multifactorial and may be influenced by factors including the patient's age, symptoms, functional deficit, size of tear, tear location (e.g.bursal vs articular), nature of onset (traumatic vs atraumatic), etiology, treatment timeline, concomitant pathologies (i.e.labral tear), comorbidities (i.e.diabetes), risk factors (i.e.smoker), and vocation and avocation activities.Currently, treatment of PTRCTs remains controversial.Methods: A systematic review was conducted to synthesize the high-quality evidence available with respect to nonoperative AND surgical interventions for treating partial-thickness rotator cuff tears.Results: The initial title and abstract screening resulted in 3930 studies after removal of duplicates.After applying inclusion and exclusion criteria, 662 studies were selected for full-text review, of which 34 informed our best evidence synthesis.Discussion: Nonoperative strategies reviewed in this synthesis included injections (i.e., platelet-rich plasma, corticosteroid, prolotherapy, sodium hyaluronate, anesthetic, and atelocollagen), exercise therapy, and physical agents.Operative interventions consisted of debridement, shaving of the tendon and footprint, transtendon repair, and traditional suture anchor repair techniques with and without tear completion.Importance: This scoping review does not suggest superiority of operative over nonoperative methods.Thus, it is our opinion that nonoperative modalities be employed first.Surgery is the most invasive and costly approach, with the highest risk of complications such as infection.Therefore, we feel the simplest and least invasive should usually be considered first.However, other variables such as patient expectation, and treating practitioner bias, or preference may change which modalities are offered and in what sequence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.252 | 0.037 |
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".