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Concurrent femoral head reduction and periacetabular osteotomies for the treatment of severe femoral head deformities

2018· article· en· W2902787935 on OpenAlexaboutno aff
John C. Clohisy, Cecilia Pascual‐Garrido, Stephen T. Duncan, Gail Pashos, Perry L. Schoenecker

Bibliographic record

VenueThe Bone & Joint Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFemoral headRadiological weaponSurgeryHarris Hip ScoreOsteotomyReduction (mathematics)Arthroplasty

Abstract

fetched live from OpenAlex

AIMS: The aims of this study were to review the surgical technique for a combined femoral head reduction osteotomy (FHRO) and periacetabular osteotomy (PAO), and to report the short-term clinical and radiological results of a combined FHRO/PAO for the treatment of selected severe femoral head deformities. PATIENTS AND METHODS: Between 2011 and 2016, six female patients were treated with a combined FHRO and PAO. The mean patient age was 13.6 years (12.6 to 15.7). Clinical data, including patient demographics and patient-reported outcome scores, were collected prospectively. Radiologicalally, hip morphology was assessed evaluating the Tönnis angle, the lateral centre to edge angle, the medial offset distance, the extrusion index, and the alpha angle. RESULTS: The mean follow-up was 3.3 years (2 to 4.6). The modified Harris Hip Score improved by 33.0 points from 53.5 preoperatively to 83.4 postoperatively (p = 0.03). The Western Ontario McMasters University Osteoarthritic Index score improved by 30 points from 62 preoperatively to 90 postoperatively (p = 0.029). All radiological parameters showed significant improvement. There were no long-term disabilities and none of the hips required early conversion to total hip arthroplasty. CONCLUSION: FHRO combined with a PAO resulted in clinical and radiological improvement at short-term follow-up, suggesting it may serve as an appropriate salvage treatment option for selected young patients with severe symptomatic hip deformities.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.323
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations31
Published2018
Admission routes1
Has abstractyes

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