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Record W2590572877

THE EFFECTS OF TROCHLEAR DESIGN ON SURFACE DAMAGE AND WEAR IN RETRIEVED TOTAL KNEE IMPLANTS USING PROFILOMETRY

2018· article· en· W2590572877 on OpenAlexaff
Jacob Matz, Brent A. Lanting, Matthew G. Teeter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsWestern University
Fundersnot available
KeywordsPatellaPatellofemoral jointMedicineTotal knee arthroplastyMagnificationOrthodonticsProfilometerArthroplastySurgeryMaterials scienceBiomedical engineeringComposite materialPhysicsOptics
DOInot available

Abstract

fetched live from OpenAlex

Introduction Complications related to the patellofemoral joint continue to be a substantial source of patient morbidity, causing anterior knee pain, instability, and dysfunction following total knee arthroplasty. One of the principle factors affecting patellofemoral outcomes may be trochlear design. The optimal design is currently unknown. The purpose of the present study was to study patellofemoral joint contact by analysing areas of wear in retrieved femoral components of three modern designs. Materials and Methods Eighteen retrieved femoral components featuring three different designs (constant radius of rotation, multiple radii of rotation, and multiple radii of rotation with built-in external rotation design) were matched on the basis of time-in-vivo, age, BMI and gender. All implants were cobalt chrome, posterior stabilized, cemented components with fixed bearing design with a resurfaced patella. Trochlear wear and surface damage were assessed using visual inspection, low-magnification light microscopy, and light profilometry. Results Six implants from each group were successfully matched and were used for the topographical analysis. The femoral components were closely matched on the basis of time-in-vivo (TIV) (2.4 years±1.2), age (71.6 years±11.3), and BMI (33.0 kg/m2±7.0). There were 9 males and 9 females in the sample. Infection was the most common reason for revision (n=14) followed by instability (n=3) and loosening (n=1). There were no significant differences in TIV, age, and BMI between the groups (p=0.366, p=0.829, and p=0.586, respectively). When compared with unused, reference components, both the retrieved constant radius implants (p 0.05). Visual inspection of the femoral components showed evidence of damage in all implant types. Modes of damage included scratches, striation, pitting, and delamination. No significant differences between the groups were found with respect to overall damage and wear on visual inspection (p=0.480). However, light profilometry analysis showed significantly increased roughness of multiple radii components compared to constant radius or multiple radii components with built-in external rotation (p<0.05). This was particularly significant in the proximal middle (p=0.045) and medial zones of the trochlea (p=0.017). Conclusions All retrieved femoral components show evidence of damage in the trochlear area. While retrieved constant radius and multiple radii components showed increased wear compared to new components, retrieved components with multiple radii and built-in external rotation did not differ significantly from their new state. Retrieved multiple radii components appeared to have increased roughness compared with constant radius or multiple radii with built-in external rotation, particularly in the proximal zones of the trochlea. The long term effects of increased trochlear roughness requires further investigation and correlation with clinical outcomes. As the volume and patient demands for total knee arthroplasty increase, a greater understanding of the effect of trochlear design on clinical outcomes is warranted.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.033
GPT teacher head0.255
Teacher spread0.222 · 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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