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Record W2602216816

RETRIEVAL ANALYSIS OF OXIDISED ZIRCONIUM FEMORAL HEADS USED IN PRIMARY TOTAL HIP ARTHROPLASTY

2018· article· en· W2602216816 on OpenAlexaff
Trevor C. Gascoyne, Thomas R. Turgeon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsOrthopaedic Innovation Centre
Fundersnot available
KeywordsFemoral headMagnificationFrettingZirconiumImplantMaterials scienceFemoral neckCorrosionMedicineSurgeryBiomedical engineeringComposite materialMetallurgyOptics
DOInot available

Abstract

fetched live from OpenAlex

Introduction Detailed analysis of retrieved total hip replacements (THRs) is valuable for assessing implant and material successes and failures. Reduction of bearing wear and corrosion and fretting of the head-neck trunnion is essential to implant durability and patient health. This research quantifies and characterizes taper and bearing surface damage on retrieved oxidized zirconium THRs. Methods Initially, 11 retrieved oxidized zirconium femoral heads were examined along with their associated femoral stems. Relevant patient and retrieval data was collected from clinical charts and radiographs. Taper corrosion (Figure 1) and fretting damage (Figure 2) scoring was performed following the Dyrkacz [1] method. A coordinate measuring machine was used to obtain a detailed surface map of the male and female taper surfaces. Taper surface maps were best-fit with an idealized cone followed by volume subtraction to quantify the amount of material removed as a result of fretting and corrosion processes. Scanning electron microscopy was performed on select samples to identify specific damage modes. Unique surface bumps were noted on the articular surface of select femoral heads (Figure 3). Seventeen femoral heads were added to the analysis specifically for identification of these bumps. Articular surfaces were searched under SEM magnification and bumps were identified and counted. Parametric statistical correlations were performed with SAS v9.3. Results Mean patient age was 61 years (Range: 35–95) with mean implantation period being 2.0 years (Range: 0.1–11.4) and mean body mass index of 29 kg/m 2 (Range: 22–46). Revision for infection (n=11), peri-prosthetic fracture (n=5) and dislocation (n=5) were the main reasons for revision. Mean corrosion damage scores were 2.0 and 3.6 (head, neck) while mean fretting damage scores were 8.5 and 5.8 (head, neck). Fretting damage score was weakly correlated with implantation period (p=0.07) while corrosion damage score was not. Mean corrosion and fretting volume measured 0.40 mm 3 and 0.87 mm 3 (head, neck). Volume of corrosion and fretting damage did not correlate with implantation period; however neck volume correlated with inclination angle of the acetabular cup (p The unique surface bumps were identified in 12 of 28 samples, with 3 samples having Conclusion Fretting damage was found to correlate with implantation period, suggesting that is a continuous in vivo process; however, this was not found for corrosion damage. Fretting damage volume correlated with acetabular cup angle; however, this may be coincidence as only 8 samples were included in the analysis. Overall, our corrosion damage scores (2.0–3.6) were lower than previously published values for 28mm & 36mm cobalt-chrome heads (4.5–13.1) [1]. However, our fretting damage scores (5.8–8.5) were higher than previously published (2.8–4.4) [1]. Greater fretting damage on the oxidized zirconium heads may be explained by the softer zirconium alloy compared to that of cobalt-chromium. Further subsurface investigation of the surface bumps is underway using a focused ion beam mill.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.251
Teacher spread0.220 · 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 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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