Hip capsular strain varies between ligaments dependent on both hip position- and applied rotational force
Bibliographic record
Abstract
PURPOSE: To noninvasively characterize the ligament strain in the hip capsule using a novel CT-based imaging technique. METHODS: The superior iliofemoral ligament (SIFL), inferior iliofemoral ligament (IIFL), ischiofemoral ligament (IFL) and pubofemoral ligament (PFL) were identified and beaded in seven cadavers. Specimens were mounted on a joint motion simulator within an O-arm CT scanner in - 15°, 0°, 30°, 60°, and 90° of flexion. 3 Nm of internal rotation (IR) and external rotation (ER) were applied and CT scans obtained. Strains were calculated by comparing bead separation in loaded and unloaded conditions. Repeated-measures ANOVA was used to evaluate differences in strain within ligaments between hip positions. RESULTS: For the SIFL, strain significantly decreased in IR at 30° (p = 0.045) and 60° (p = 0.043) versus 0°. For ER, there were no significant position-specific changes in strain (n.s.). For the IIFL, strain decreased in IR and increased in ER with no significant position-specific differences. For the IFL, strain increased with IR and decreased with ER with no significant position-specific differences. Finally, in the PFL there was a significant flexion angle-by-load interaction (p < 0.001; ES = 0.566), with peak strains noted at 60˚, however pair-wise comparisons failed to identify significant differences between positions (n.s.). Strain decreased in ER, with no significant position-specific differences. CONCLUSION: The SIFL and IIFL limit hip external rotation with greater effect in higher flexion angles, while the IFL and PFL limit hip internal rotation. Following hip arthroscopy, consideration should be given to restricting external rotation as traditional capsulotomies cause injury to the SIFL and IIFL.
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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 | 0.001 |
| 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) | 0.001 | 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".