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Record W2041166850 · doi:10.1007/s00167-014-3345-2

Patient‐specific instrumentation improved mechanical alignment, while early clinical outcome was comparable to conventional instrumentation in TKA

2014· article· en· W2041166850 on OpenAlexfundaboutno aff
Werner Anderl, Leo Pauzenberger, Roman Kölblinger, Gabriele Kiesselbach, Georg Brandl, Brenda Laky, Bernhard Kriegleder, Philipp R. Heuberer, Eva Schwameis

Bibliographic record

VenueKnee Surgery Sports Traumatology Arthroscopy · 2014
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
FundersUniversity of OxfordMcMaster University
KeywordsWOMACMedicineOsteoarthritisOxford knee scoreVisual analogue scaleRadiographyTotal knee arthroplastyProspective cohort studyArthroplastyNuclear medicineSurgeryPathology

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this prospective study was to compare early clinical outcome, radiological limb alignment, and three-dimensional (3D)-component positioning between conventional and computed tomography (CT)-based patient-specific instrumentation (PSI) in primary mobile-bearing total knee arthroplasty (TKA). METHODS: Two hundred ninety consecutive patients (300 knees) with severe, debilitating osteoarthritis scheduled for TKA were included in this study using either conventional instrumentation (CVI, n = 150) or PSI (n = 150). Patients were clinically assessed before and 2 years after surgery according to the Knee-Society-Score (KSS) and the visual-analog-scale for pain (VAS). Additionally, the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) and the Oxford-Knee-Score (OKS) were collected at follow-up. To evaluate accuracy of CVI and PSI, hip-knee-ankle angle (HKA) and 3D-component positioning were assessed on postoperative radiographs and CT. RESULTS: Data of 222 knees (CVI: n = 108, PSI: n = 114) were available for analysis after a mean follow-up of 28.6 ± 5.2 months. At the early follow-up, clinical outcome (KSS, VAS, WOMAC, OKS) was comparable between the two groups. Mean HKA-deviation from the targeted neutral mechanical axis (CVI: 2.2° ± 1.7°; PSI: 1.5° ± 1.4°; p < 0.001), rates of outliers (CVI: 22.2%; PSI: 9.6%; p = 0.016), and 3D-component positioning outliers were significantly lower in the PSI group. Non-outliers (HKA: 180° ± 3°) showed better clinical results than outliers at the 2-year follow-up. CONCLUSIONS: CT-based PSI compared with CVI improves accuracy of mechanical alignment restoration and 3D-component positioning in primary TKA. While clinical outcome was comparable between the two instrumentation groups at early follow-up, significantly inferior outcome was detected in the subgroup of HKA-outliers. LEVEL OF EVIDENCE: Prospective comparative study, Level II.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.036
GPT teacher head0.312
Teacher spread0.276 · 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

Citations87
Published2014
Admission routes2
Has abstractyes

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