Management of Greater Trochanteric Pain Syndrome After Total Hip Arthroplasty: Practice Patterns and Surgeon Attitudes
Bibliographic record
Abstract
INTRODUCTION: Greater trochanteric pain syndrome (GTPS) or trochanteric bursitis is described as pain on the lateral side of the hip that does not involve the hip joint and can be elicited clinically by palpation over the greater trochanter. To date, there remains no consensus on clinical guidelines for either diagnosis or management of GTPS. METHODS: To understand the practice patterns, beliefs, and attitudes relating to the management of GTPS after total hip arthroplasty, a survey was developed and completed by Canadian arthroplasty surgeons. The final survey consisted of 23 questions divided into three sections: 1) screening questions; 2) demographic information; and 3) practice patterns, attitudes, and beliefs. RESULTS: Most surgeons use physical examination alone for diagnosis. A detailed analysis indicates that surgeons primarily treat GTPS with oral anti-inflammatories (57.1%), structured physiotherapy (52.4%), and steroid injections (45.2%). Management options are typically nonsurgical and comprise a combination of either unstructured or targeted physiotherapy, corticosteroid injections, or platelet-rich plasma. DISCUSSION: There remains an absence of clinical consensus for the diagnosis and management of GTPS after total hip arthroplasty. Physical examination is most often relied on, regardless of the availability of imaging aids. While common treatments of GTPS were identified, up to one-third of patients fail initial therapy.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".