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Record W4200460102 · doi:10.1016/j.artd.2021.11.005

A Successful Case of TKA With Complex Deformity And Retained Hardware Using Computer Navigation

2021· article· en· W4200460102 on OpenAlexaboutno aff
Jan Cerny, Jan Soukup, Tomáš Novotný

Bibliographic record

VenueArthroplasty Today · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntramedullary rodPeriprostheticFemurSurgeryTotal knee arthroplastyDeformityOsteotomyOsteosynthesisVarus deformityArthroplastyOsteoarthritis

Abstract

fetched live from OpenAlex

We present a case report of a 60-year-old Caucasian female patient, who had undergone a series of procedures for a periprosthetic (after total hip arthroplasty) Vancouver C type diaphyseal fracture of the right femur (reverse distal femoral locking compression plate [LCP] osteosynthesis, then a corrective osteotomy with another distal femoral LCP osteosynthesis). Subsequently, she developed high-grade osteoarthrosis of the right knee, indicated for a total knee arthroplasty. Considering the extent of previous procedures, which had significantly compromised the bone quality of the femur and therefore increased the risk of a refracture after an eventual hardware removal, we decided to retain the LCP plate. We concluded that the optimal solution would be the use of a computer-navigated total knee arthroplasty. This procedure obviated the need for intramedullary guiding, while ensuring optimal joint alignment. No postoperative complications emerged.

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)0.005
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 score0.008
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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