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Record W3176178113 · doi:10.2147/orr.s309995

Trial Tibial Inserts May Result in Different Knee Kinematics from Final Poly Inserts in Total Knee Arthroplasty

2021· article· en· W3176178113 on OpenAlexaff
Sahil Prabhnoor Sidhu, Brent A. Lanting, Paul B. Kelly, Edward M. Vasarhelyi, Ryan Willing

Bibliographic record

VenueOrthopedic Research and Reviews · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsWestern University
Fundersnot available
KeywordsCadaveric spasmInsert (composites)Range of motionKinematicsKnee JointOrthodonticsKnee flexionTotal knee arthroplastyValgusMedicineMaterials scienceSurgeryPhysicsComposite material

Abstract

fetched live from OpenAlex

INTRODUCTION: Trialling is a key step in total knee arthroplasty (TKA) and helps the surgeon assess for adequate balancing, range of motion, and stability. Despite this, there are no studies investigating knee kinematics when using trial versus final polyethylene tibial inserts. MATERIALS AND METHODS: Fourteen fresh frozen cadaveric specimens were cycled in a VIVO joint motion simulator. Using both simple compression and simulated muscle loads, joints were tested after TKA with a trial insert or a final tibial poly insert. Anterior/posterior (AP), internal/external (IE), and varus/valgus (VV) kinematics and laxities were analyzed. RESULTS: Knees with trial poly inserts had significantly greater AP hysteresis (difference between flexion and extension motion) than those with final poly inserts (p=0.001). There was no significant difference in IE (p=0.563) or VV (p=0.580) hysteresis. There was no difference in AP, IE, or VV motion or laxities when considering the flexion path alone. Prosthetic joints followed different paths in flexion versus extension. CONCLUSION: While trial tibial inserts impart valuable information, they may not accurately reproduce the same joint kinematics as final inserts. Balancing of the knee at specific degrees of flexion may depend on the path taken to get there.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.112
GPT teacher head0.378
Teacher spread0.267 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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