The Impact of Pain Tolerance and Grit on Patients with FAI Syndrome: A Prospective Study
Bibliographic record
Abstract
The findings of this cost-utility analysis based on data from the Femoroacetabular Impingement Randomised Controlled Trial (FIRST) trial indicate that over a lifetime time horizon, osteochondroplasty, with or without labral repair, is a costeffective treatment strategy for young adults with FAI.Future research involving real-word data is needed to further validate these findings.Data: Objectives: To conduct a cost-utility analysis of osteochondroplasty with or without labral repair compared to arthroscopic lavage with or without labral repair for femoroacetabular impingement (FAI).Methods: A Markov model was constructed to compare the lifetime quality-adjusted life years (QALYs) and costs of the two treatment strategies.The target population was surgical FAI patients aged 36 years.The primary data source was patient-level data from the Femoroacetabular Impingement Randomised Controlled Trial (FIRST), which evaluated the efficacy of the surgical correction of FAI via arthroscopic osteochondroplasty with or without labral repair compared to arthroscopic lavage with or without labral repair in Canada.Long-term data were extrapolated using a generalized gamma model.The primary outcome was the incremental cost-effectiveness ratio (ICER), calculated by dividing the difference in costs by the difference in quality-adjusted life years (QALYs) between osteochondroplasty and lavage, with or without labral repair.Probabilistic sensitivity analyses and one-way sensitivity analyses were used to characterize uncertainty of model parameters and assumptions.Results: Over a lifetime horizon, osteochondroplasty, with or without labral repair, had a greater expected benefit (0.63 QALYs gained per patient) and lower costs ($955.89saved per patient), as compared with lavage with or without labral repair.Probabilistic sensitivity analyses demonstrated that the probability of osteochondroplasty, with or without labral repair, being cost-effective was 90.5% at a commonly used willingness-to-pay threshold of" $50,000/QALY.Across all one-way sensitivity analyses, osteochondroplasty with or without labral repair remained a cost-effective option.Conclusion: Over a lifetime time horizon, osteochondroplasty, with or without labral repair, is a cost-effective treatment strategy for young adults with FAI.Future research involving real-word data is needed to further validate these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".