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Record W3064471179 · doi:10.1186/s13063-020-04592-9

Periacetabular osteotomy with or without arthroscopic management in patients with hip dysplasia: study protocol for a multicenter randomized controlled trial

2020· article· en· W3064471179 on OpenAlexafffundabout
Geoffrey Wilkin, Stéphane Poitras, John C. Clohisy, Étienne L. Belzile, Ira Zaltz, George Grammatopoulos, Gerd Melkus, Kawan Rakhra, Tim Ramsay, Kednapa Thavorn, Paul E. Beaulé

Bibliographic record

VenueTrials · 2020
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsCentre hospitalier de l'Université LavalUniversity of OttawaOttawa Hospital
FundersCanadian Orthopaedic Foundation
KeywordsMedicineHip arthroscopyRandomized controlled trialSurgeryPhysical therapyFemoroacetabular impingementHip replacementClinical endpointDysplasiaArthroplastyArthroscopyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hip dysplasia is one of the most common causes of hip arthritis. Its incidence is estimated to be between 3.6 and 12.8% (Canadian Institute for Health Information, Hip and knee replacements in Canada, 2017-2018: Canadian joint replacement registry annual report, 2019; Jacobsen and Sonne-Holm, Rheumatology 44:211-8, 2004). The Periacetabular Osteotomy (PAO) has been used successfully for over 30 years (Gosvig et al., J Bone Joint Surg Am 92:1162-9, 2010), but some patients continue to exhibit symptoms post-surgery (Wyles et al., Clin Orthop Relat Res 475:336-50, 2017). A hip arthroscopy, performed using a small camera, allows surgeons to address torn cartilage inside the hip joint. Although both procedures are considered standard of care treatment options, it is unknown whether the addition of hip arthroscopy improves patient outcomes compared to a PAO alone. To delay or prevent future joint replacement surgeries, joint preservation surgery is recommended for eligible patients. While previous studies found an added cost to perform hip arthroscopies, the cost-effectiveness to Canadian Health care system is not known. METHODS: Patients randomized to the experimental group will undergo central compartment hip arthroscopy prior to completion of the PAO. Patients randomized to the control group will undergo isolated PAO. Patient-reported quality of life will be the primary outcome used for comparison between the two treatment groups as measured by The International Hip Outcome Tool (iHOT-33) (Saberi Hosnijeh et al., Arthritis Rheum 69:86-93, 2017). Secondary outcomes will include the four-square step test and sit-to-stand (validated in patients with pre-arthritic hip pain) and hip-specific symptoms and impairment using the HOOS; global health assessment will be compared using the PROMIS Global 10 Score; health status will be assessed using the EQ-5D-5L and EQ VAS questionnaires (Ganz et al., Clin Orthop Relat Res 466:264-72, 2008) pre- and post-operatively. In addition, operative time, hospital length of stay, adverse events, and health services utilization will be collected. A sub-group of patients (26 in each group) will receive a T1rho MRI before and after surgery to study changes in cartilage quality over time. A cost-utility analysis will be performed to compare costs and quality-adjusted life years (QALYs) associated with the intervention. DISCUSSION: We hypothesize that (1) concomitant hip arthroscopy at the time of PAO to address central compartment pathology will result in clinically important improvements in patient-reported outcome measures (PROMs) versus PAO alone, that (2) additional costs associated with hip arthroscopy will be offset by greater clinical improvements in this group, and that (3) combined hip arthroscopy and PAO will prove to be a cost-effective procedure. TRIAL REGISTRATION: ClinicalTrials.gov NCT03481010 . Registered on 6 March 2020. Protocol version: version 3.

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)0.013
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.053
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0110.005
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0530.007

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 head0.056
GPT teacher head0.382
Teacher spread0.326 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations17
Published2020
Admission routes3
Has abstractyes

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