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Record W2599717417

MEDIAL PIVOT IMPLANTS OFFER IMPROVED KNEE STABILITY DURING A STAIR ASCENT TASK COMPARED WITH POSTERIOR-STABILISED IMPLANTS

2018· article· en· W2599717417 on OpenAlexaff
Mario Lamontagne, Erik Kowalski, Geoff Dervin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBicepsVastus medialisMedicineElectromyographyImplantPhysical medicine and rehabilitationBiomechanicsKnee flexionPhysical therapyOrthodonticsSurgeryAnatomy
DOInot available

Abstract

fetched live from OpenAlex

Introduction Patients undergoing a total knee arthroplasty (TKA) are now living longer and partaking in more active lifestyles. They expect a high level of post-operative function and long term durability of their implant. Using electromyography (EMG) analysis helps further explain biomechanical findings by giving insight as to what is occurring at the level of the muscles. Normal biomechanics are not restored post-TKA as patients have reduced knee flexion and weakened quadriceps muscles compared to their healthy peers. Purpose The purpose of this study was to compare muscle activation in TKA patients who received a medial pivot (MP) or posterior stabilized (PS) implant to those of healthy controls (CTRL) during a stair ascent task. Methods A total of 12 patients were assigned to either a MP or PS TKA operated by the same surgeon. Approximately 9 months following surgery, the 12 patients along with 6 CTRL patients completed an EMG analysis during a stair ascent task (Table 1). Wireless EMG electrodes were placed on 4 muscles: vastus medialis (VM), vastus lateralis (VL), biceps femoris long head (BF), and semimembranosus (SM) muscles. All participants completed maximal voluntary contractions (MVICs) during knee flexion and extension while seated with the knee flexed at 60°. Following the MVICs, participants completed 5 trials of a 3-step stair ascent task. TKA patients were instructed to make the first step onto the staircase with their operated limb. EMG data were processed in Matlab. Peak muscle activity (PeakLE EMG) and total muscle activity (iEMG) from each muscle was obtained during stance phase. Data were averaged between left and right limbs for the CTRL group and compared to the operated limb of TKA groups. Non-parametric Kruskal Wallace ANOVA tests were used to test for statistical significance between groups and Wilcoxon rank sum tests were used to identify differences with α=0.05. Results Both TKA groups had significantly greater PeakLE EMG of the quadriceps muscles compared to the CTRL group (Figure 1). PeakLE EMG of the BF and VM muscles were significantly greater in the PS group compared to both CTRL and MP groups. The PS group had significantly greater iEMG of the BF, VL and VM muscles compared to the CTRL group (Figure 2) whereas the PS group had significantly greater iEMG of the SM and VM muscles compared to the MP group. Conclusion The MP group had lower PeakLE EMG for both VM and BF muscles compared to the PS group, indicating that the MP group activates these muscles less to achieve the stair ascent task. BF muscle stabilizes the knee roll-back motion while the VM muscle extends the leg to clear the steps. iEMG for the VM and BF muscles were greater for the PS group indicating that they have to activate their muscles longer and to a greater extent in order to stabilize the joint. This increased stability in MP implants is achieved through the concave aspect on the medial tibial plateau for the femoral condyle to pivot in. This will reduce implant wear, prolonging implant longevity.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0050.000

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 head0.027
GPT teacher head0.231
Teacher spread0.204 · 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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