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Record W4401827147 · doi:10.1016/j.jisako.2024.100307

Osteochondroplasty with or without labral repair is more cost-effective than arthroscopic lavage with or without labral repair for treatment of young adults with femoroacetabular impingement: A cost-utility analysis based on data from a randomized controlled trial

2024· article· en· W4401827147 on OpenAlexafffundabout
Jiajun Yan, Brittany Humphries, Zhenyan Bo, Ling Dai, Nicole Simunovic, Feng Xie, Olufemi R. Ayeni, Mohit Bhandari, Asheesh Bedi, Teppo L. N. Järvinen, Volker Musahl, Douglas Naudie, Matti Seppänen, Gerard P. Slobogean, Lehana Thabane, Andrew Duong, Matthew Skelly, Ajay Shanmugaraj, Sarah Crouch, Sheila Sprague, Diane Heels‐Ansdell, Lisa Buckingham, Tim Ramsay, Petteri Kousa, Sasha Carsen, Hema Choudur, Kelly Johnston, Ivan Wong, Ryland Murphy, Sara Sparavalo, Daniel B. Whelan, Ryan Khan, Gavin Wood, Fiona Howells, Heather Grant, Bryn O Zomar, Michael Pollock, Kevin Willits, Andrew Firth, Stacey Wanlin, Alliya Remtulla, Nicole Kaniki, Étienne L. Belzile, Sylvie Turmel, Uffe Jørgensen, Annie Gam-Pedersen, Raine Sihvonen, Marko Raivio, Pirjo Toivonen, Mari Pirjetta Routapohja

Bibliographic record

VenueJournal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsMcMaster UniversityImpact
FundersCanadian Institutes of Health ResearchTurun Yliopistollinen KeskussairaalaTaysCanadian Orthopaedic FoundationUniversity of PittsburghAmerican Orthopaedic Society for Sports MedicineMcMaster UniversityOdense UniversitetshospitalOttawa Hospital Research InstituteLondon Health Sciences CentreUniversity of OttawaUniversity of TorontoDalhousie UniversityHamilton Health SciencesHelsingin Yliopisto
KeywordsFemoroacetabular impingementMedicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: The objective of this study was 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) from a Canadian public payer perspective. 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, 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, calculated by dividing the difference in costs by the difference in 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 ($955.89 saved 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 in Canada. 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. LEVEL OF EVIDENCE: III.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.013
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.021
GPT teacher head0.314
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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