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Record W2765501026 · doi:10.5301/hipint.5000543

Effect of sleeved ceramic femoral heads on titanium ion release

2017· article· en· W2765501026 on OpenAlexaff
Anthony Deny, Janie Barry, Jonathan Hutt, Martin Lavigne, Vincent Massé, Pascal‐André Vendittoli

Bibliographic record

VenueHip International · 2017
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsMedicineTitaniumFemoral headImplantCeramicTotal hip arthroplastyHead (geology)Hip arthroplastySurgeryMaterials scienceDentistryMetallurgy

Abstract

fetched live from OpenAlex

INTRODUCTION: Metal ion release from wear and corrosion at the femoral head-stem taper junction can evoke local adverse reactions to metal debris (ARMD). In a specific large-diameter head (LDH) total hip arthroplasty (THA) system, ceramic femoral heads of 44 to 48 mm are available with a titanium (Ti) adaptor sleeve, while heads of 36- to 40-mm come without sleeves. The hypothesis of this study is that the Ti adaptor sleeve with LDH ceramic-on-ceramic (CoC) bearings will not cause wear or corrosion at the taper junction and, thus, will not generate high whole blood Ti ion levels. METHODS: We compared whole blood Ti levels at minimum 1-year follow-up in 27 patients with unilateral primary LDH CoC THA with head sizes ranging from 36 to 48 mm using a Ti stem and acetabular component. RESULTS: Although Ti ion levels in patients with 36- to 40-mm head diameters without Ti sleeve were found to be statistically significantly higher (2.3 μg/l: 1.6-3.1, SD 0.44) compared to those with a Ti sleeve (1.9 μg/l: 1.6-2.2, SD 0.19) (p = 0.020), the found difference has no clinical importance. No patients presented clinical signs of ARMD, and the clinical results in both groups were similar. CONCLUSIONS: LDH CoC THA Ti levels were low and probably related to unavoidable passive corrosion of implant surfaces. Measurement of Ti in subjects with ceramic LDH, with or without Ti adaptor sleeve, did not disclose undirected signs of trunnionosis.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.564

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.315
Teacher spread0.299 · 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 designObservational
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

Citations14
Published2017
Admission routes1
Has abstractyes

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