Intraoperative traction has a negligible time-dependent influence on patient-reported outcomes after hip arthroscopy: a cohort study
Bibliographic record
Abstract
ABSTRACT The aim of this study is to determine if post-operative patient-reported outcome measures (PROMs) are influenced by hip arthroscopy traction duration. Patients from a local prospective hip arthroscopy database were retrospectively analyzed. Four hip-specific PROMs were utilized: modified Harris Hip Score (mHHS), Hip Outcome Score—Activities of Daily Living (HOS-ADL), Hip Outcome Score—Sports Specific (HOS-SS), and international Hip Outcome Tool (iHOT). PROMs were collected pre-operatively and 6 months, 1 year and 2 years post-operatively. Two cohorts were created based on a cut-off corresponding to the 66th percentile for our patient cohort. Analyses were completed for each PROM at each post-operative interval with univariable statistics. Multivariable statistics were examined to identify the variables that were predictive of achieving post-operative minimal clinically important difference (MCID) at the 2-year follow-up. Overall, 222 patients met the inclusion criteria. The mean age was 32.4 ± 9.4 years, and 116 (52.3%) were female. The average traction time of the study population was 46.1 ± 12.9 min. A total of 145 patients were included in the short traction cohort (65%) with traction times of <50 min (66th percentile). No significant differences were found regarding PROM scores or MCID achievement rates between both cohorts at any post-operative period. In multivariable analyses, achievement of MCID was predicted by a decrease in traction time for all PROMs and pincer-type resection for mHSS, HOS-ADL and iHOT. There was no difference in PROMs and MCID achievement between longer and shorter traction time cohorts. On multivariable analysis, a decrease in traction time is predictive of MCID for all PROM scores and pincer-type resection was predictive of MCID for most PROM scores. Level of evidence: Level III, cohort study
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".