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Record W2803980094 · doi:10.4055/cios.2018.10.2.167

Is Immediate Postoperative Mechanical Axis Associated with the Revision Rate of Primary Total Knee Arthroplasty? A 10-Year Follow-up Study

2018· article· en· W2803980094 on OpenAlexaboutno aff
Ju-Kwon Park, Jong‐Keun Seon, Kyu‐Jin Cho, Namhoon Lee, Eun Kyoo Song

Bibliographic record

VenueClinics in Orthopedic Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
FundersChonnam National University
KeywordsMedicineOsteoarthritisProsthesisTotal knee arthroplastySurgeryArthroplastyOxford knee scoreSurvival rateRadiography

Abstract

fetched live from OpenAlex

BACKGROUND: Achieving neutral limb alignment during total knee arthroplasty (TKA) has been considered an important determinant in the long-term prosthesis survival. The purpose of this study was to evaluate the association between the immediate postoperative mechanical alignment of the lower limb and the rate of revision TKA by comparing an acceptable mechanical axis group (within ± 3° from neutral alignment) and an outlier group (> 3° deviation from neutral alignment). METHODS: Between 2000 and 2006, clinical and radiographic data of 334 primary TKAs were retrospectively reviewed to determine the 10-year Kaplan-Meier survival rate. Patients were divided into acceptable and outlier groups according to the mechanical axis checked postoperatively within a month. Clinical outcomes were assessed using Hospital for Special Surgery, Knee Society Score, and Western Ontario and McMaster Universities Osteoarthritis Index score preoperatively and at the final follow-up. Postoperative complications and revision rates were also evaluated. RESULTS: = 0.25). CONCLUSIONS: Restoration of neutral limb alignment is a factor that can result in a lower revision rate and higher longevity in TKA. However, there were no significant differences in clinical outcomes between the two groups.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.301
Teacher spread0.268 · 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

Citations50
Published2018
Admission routes1
Has abstractyes

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