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Medial Quadriceps Tendon Femoral Ligament Reconstruction After Patellectomy: A Treatment for a Dislocating Quadriceps Tendon

2017· article· en· W2909837983 on OpenAlexaff
Laurie A. Hiemstra, Bevan Frizzell, Sarah Kerslake

Bibliographic record

VenueJAAOS Global Research and Reviews · 2017
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsBanff Centre
Fundersnot available
KeywordsMedicineQuadriceps tendonMedial patellofemoral ligamentTendonSurgeryPatella

Abstract

fetched live from OpenAlex

The medial quadriceps tendon femoral ligament (MQTFL) reconstruction is an alternative to the patellar bony fixation of the medial patellofemoral ligament reconstruction for the treatment of lateral patellofemoral dislocation. We describe the first report of a unique application of this technique in a patient with a previous patellectomy to treat a dislocating quadriceps tendon. An active 59-year-old Caucasian man presented 25 years after patellectomy with a dislocating quadriceps tendon and significant dysfunction. Stabilization of the knee extensor mechanism with an MQTFL reconstruction and retensioning of the quadriceps complex by tibial tubercle distalization provided stability and improved function. Extensor tendon instability is a rare complication after patellectomy that can cause significant pain and dysfunction. Successful stabilization of the quadriceps mechanism through an MQTFL reconstruction can provide excellent patient satisfaction and functional results. This technique may have implications for patellofemoral instability surgeries and in cases of knee extensor dysfunction after total knee arthroplasty.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.175
GPT teacher head0.402
Teacher spread0.227 · 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 designCase report
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

Citations4
Published2017
Admission routes1
Has abstractyes

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