The Frank Stinchfield Award: Dislocation in Revision THA: Do Large Heads (36 and 40 mm) Result in Reduced Dislocation Rates in a Randomized Clinical Trial?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Dislocation after revision THA is a common complication. Large heads have the potential to decrease dislocation rate, but it is unclear whether they do so in revision THA. QUESTIONS/PURPOSES: We therefore determined whether a large femoral head (36 and 40 mm) resulted in a decreased dislocation rate compared to a standard head (32 mm). METHODS: We randomized 184 patients undergoing revision THA to receive either a 32-mm head (92 patients) or 36- and 40-mm head (92 patients) and stratified patients by surgeon. The two groups had similar baseline demographics. The primary end point was dislocation. Quality-of-life (QOL) measures were WOMAC and SF-36. The mean followup for dislocation was 5 years (range, 2-7 years); the mean followup for QOL was 2.2 years (range, 1.6-4 years). RESULTS: In the 36- and 40-mm head group, the dislocation rate was 1.1% (one of 92) versus 8.7% (eight of 92) for the 32-mm head. There was no difference in QOL outcomes between the two groups. CONCLUSIONS: Our observations confirm a large femoral head (36 or 40 mm) reduces dislocation rates in patients undergoing revision THA at short-term followup. We now routinely use large heads with a highly crosslinked polyethylene acetabular liner in all revision THAs. LEVEL OF EVIDENCE: Level I, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.056 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it