Cup orientation following posterior approach THA – the effect of different visual aids and pelvic supports
Bibliographic record
Abstract
INTRODUCTION: This study aims to compare cup inclination achieved (1) Using two orientation guides, whilst using the same 3-point pelvic positioner and (2) Using two types of pelvic positioners, whilst measuring intra-operative cup inclination with an inclinometer. MATERIALS AND METHODS: This is a prospective, diagnostic cohort study of a consecutive series of 150 THAs performed through a posterior approach. Two types of 3-point pelvic positioners were used (Stulberg and modified Capello Hip Positioners) and the cup was positioned freehand using one of two orientation guides (mechanical guide or digital inclinometer). Intra-operative inclination was recorded, radiographic cup inclination and anteversion were measured from radiographs. The differences in inclination due to pelvic position (ΔPelvicPosition) and orientation definitions (ΔDefinition) were calculated. Target radiographic inclination and anteversion was 40/20° ± 10°. RESULTS: There was no difference in radiographic cup inclination/ (p = 0.63) using a mechanical guide or digital inclinometer. However, differences were seen in ΔPelvicPosition between the positioners ((Stulberg: 0° ± 5 vs. Capello: 3° ± 6); p = 0.011). Intra-operative inclination at implantation was different between positioners and this led to equivalent cases within inclination/anteversion targets (Stulberg:84%, Capello:80%; p = 0.48). CONCLUSIONS: With the pelvis securely positioned with 3-point supports, optimum cup orientation can be achieved with both alignment guides and inclinometer. Non-optimal cup inclinations were seen when intra-operative inclinations were above 40° and below 32°, or the ΔPelvicPosition was excessive (> 15°; n = 2). We would thus recommend that the intra-operative cup inclination should be centered strictly between 30° and 35° relative to the floor. Small differences exist between different type of pelvic positioners that surgeons need to be aware off and account for.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".