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Record W4392706697 · doi:10.1002/ksa.12121

The tipping point in medial opening wedge high tibial osteotomy relates to the shape of the proximal tibia more than to lower limb alignment correction

2024· article· en· W4392706697 on OpenAlexaboutno aff
Ahmed Mabrouk, Levi Reina Fernandes, Christophe Jacquet, Kristian Kley, Steven Claes, Matthieu Ollivier

Bibliographic record

VenueKnee Surgery Sports Traumatology Arthroscopy · 2024
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHigh tibial osteotomyTibiaTipping point (physics)Wedge (geometry)AnatomyOrthodonticsLower limbMedicineOsteotomySurgeryGeometryMathematicsEngineeringOsteoarthritis

Abstract

fetched live from OpenAlex

PURPOSE: The tipping point (TP) of the knee joint is the centre of rotation of the joint in the coronal plane. This study aimed to define the TP in medial opening wedge high tibial osteotomy (MOWHTO). METHODS: Data from 154 consecutive patients with varus knee malalignment, who underwent MOWHTO between 2017 and 2021, was retrospectively reviewed. The degree of preoperative osteoarthritis (OA), using the Kellgren-Lawrence (KL) grading system, was recorded. Long-leg standing radiographs were used to record the alignment parameters, including the hip-knee-ankle angle (HKA), the mechanical lateral distal femoral angle (mLDFA), the medial proximal tibial angle (MPTA), the joint line convergence angle (JLCA) and the joint line obliquity (JLO) angle. Postoperative Tegner activity scores, Western Ontario and McMaster University Scores and patients' satisfaction were recorded. To define the TP, the relationship of all variables to Δ JLCA (absolute difference between preoperative to postoperative JLCA values) was analysed. Linear regression was employed for Δ JLCA to preoperative JLCA and postoperative and Δ MPTA (absolute difference between preoperative and postoperative values). K-means clustering was used to partition observations into clusters, in which each observation belongs to the cluster with the nearest mean serving as a prototype of the cluster, and analysed if there was any specific threshold influencing Δ JLCA. After defining the TP, further subanalysis of the TP based on the preoperative KL OA grade and analysis of variance of this TP to the KL OA grade was performed. RESULTS: = 0.04, p = 0.7). MPTA > 91.5° was the optimal threshold dividing this series data set between substantial and nonsignificant Δ JLCA. CONCLUSION: In this study, the main predictive factors for intra-articular correction (Δ JLCA) after MOWHTO were the preoperative value of JLCA and the postoperative value of MPTA. A value of 92° for postoperative MPTA is potentially the optimal threshold to predict intra-articular correction. LEVEL OF EVIDENCE: Level IV, retrospective cohort study.

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)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.011
GPT teacher head0.257
Teacher spread0.247 · 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".

Quick stats

Citations12
Published2024
Admission routes1
Has abstractyes

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