Landmark-Guided and Ultrasound-Guided Approaches for Trochanteric Bursa Injection: A Cadaveric Study
Bibliographic record
Abstract
BACKGROUND: Trochanteric bursa (TB) injection with local anesthetic and corticosteroid is a treatment for patients suffering from greater trochanteric pain syndrome. Both landmark (LM)-guided and ultrasound (US)-guided methods have been used, but their accuracies have not been determined. This study examined the accuracy of these injections with cadaveric dissection. METHODS: Twenty-four hip specimens were randomized to receive TB injections with methylene blue under either LM-guided or US-guided approach. After dissection, the locations of the dye were classified into 3 categories: intrabursal, extrabursal, or combined intrabursal and extrabursal. The presence of dye in the intrabursal space with or without extrabursal leak was considered a successful injection. Accuracy was defined as the percentage of successful injection. RESULTS: The accuracies of the LM-guided and US-guided injection were 0.67 (95% confidence interval 0.35-0.90) and 0.92 (95% confidence interval 0.62-1.00), respectively, with no significant difference. CONCLUSIONS: This is the first cadaveric study examining the accuracy of both the US-guided and LM-guided techniques for TB injection. Future clinical studies are required to compare the outcomes of LM-guided and US-guided greater trochanteric pain syndrome injection.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".