Conservative management of an elite ice hockey goaltender with femoroacetabular impingement (FAI): a case report.
Bibliographic record
Abstract
OBJECTIVE: To detail the presentation of an elite male ice hockey goaltender with cam-type femoroacetabular impingement (FAI) and acetabular labral tears. This case will outline the prevalence, clinical presentation, imaging criteria, pathomechanics, and management of FAI, with specific emphasis on the ice hockey goaltender. CLINICAL FEATURES: A 22-year old retired ice hockey goaltender presented to a chiropractor after being diagnosed by an orthopaedic surgeon with MRI confirmed left longitudinal and chondral flap acetabular labral tears and cam-type femoroacetabular impingement (FAI). As the patient was not a candidate for surgical intervention, a multimodal conservative treatment approach including manual therapy, electroacupuncture and rehabilitation exercises were implemented. SUMMARY: FAI is prevalent in ice hockey players, particularly with goaltenders. Both skating and position-dependent hip joint mechanics involved in ice hockey may exacerbate or contribute to acquired and congenital forms of symptomatic FAI. As such, practitioners managing this population must address sport-specific demands in manual therapy, rehabilitation and physical training, to improve functional outcomes and prevent future injury.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".