Paper 17: Does Higher Quality CAM Resection Correlate with Better Patient-Reported Outcomes?
Bibliographic record
Abstract
Objectives: The relationships between CAM resection quality and patient-reported outcomes (PROs) are unknown in the literature. This study aimed to investigate the correlation of CAM resection quality with patient’s self-reported International Hip Outcome Tool (iHOT) scores collected annually post-surgery. Methods: A retrospective analysis was conducted including patients who underwent primary hip arthroscopy for femoroacetabular impingement (FAI) between 2012 and 2019. Inclusion criteria were pre-operative radiographic signs of CAM-type impingement (alpha angle > 55 °) and post-operative plain radiographs. Exclusion criteria were radiographic signs of a pincer or mixed impingement, history of femoral neck or proximal femur fracture, and treatment of concomitant hip pathologies. The following data were collected: demographic information, radiographic findings, and iHOT scores. CAM resection quality data were categorized based on findings from three plain radiographs (anteroposterior (AP) pelvis, frog leg lateral, and 45° Dunn views). High quality resections were defined as those post-operative alpha angle <55°. Results: This study included 148 participants who underwent CAM resection. From Frog leg views, 88% of patients had high-quality resections and presented superior post-operative iHOT scores compared to the 12% of patients with poor resection quality during the 1-year to 5-year follow-up period. Likewise, from Dunn views 82% of patients with a high-quality CAM resection displayed a similar trend in post-operative iHOT scores compared to 18% of patients with poor resection quality on Dunn views. However, this positive association between resection quality and post-operative iHOT scores was not evident in AP imaging. With AP views, 82% of patients with high-quality resections did not show a significant difference in iHOT scores compared to 18% of patients with poor resection quality. Conclusions: This study found that high quality CAM resection from arthroscopic surgery correlated with better iHOTs up to 5-years post-surgery from the Dunn and frog leg radiographic imaging views.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".