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Record W2990543460 · doi:10.1007/s00167-019-05776-w

Deviations in femoral joint lines using calipered kinematically aligned TKA from virtually planned joint lines are small and do not affect clinical outcomes

2019· article· en· W2990543460 on OpenAlexaff
Alexander J. Nedopil, Stephen M. Howell, Maury L. Hull

Bibliographic record

VenueKnee Surgery Sports Traumatology Arthroscopy · 2019
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFemurValgusMedicineOrthodonticsKnee JointArthroplastyCondyleJoint (building)Total knee arthroplastyAnatomySurgery

Abstract

fetched live from OpenAlex

PURPOSE: Kinematically aligned total knee arthroplasty (KA TKA) strives to restore the native distal and posterior joint lines of the femur. Because the joint lines of a virtually planned femoral component on the native femur can serve as surrogates of those of the native femur, the present study determined position and orientation deviations of the femoral joint lines following calipered KA TKA from virtually planned joint lines and whether these alignment deviations affect clinical outcomes. Our hypotheses were that the alignment deviations for most knees would be less than 2 mm and/or 2° and that larger alignment deviations would not be associated with lower clinical outcome scores. METHODS: A review of lower extremity CT scanograms and CT scans of the knee identified 36 patients treated with calipered KA TKA in one limb and no other skeletal deformities in either limb. 3D models of the operated femur with the implanted femoral component and the native femur were created. The articular surfaces of a 3D model of the implanted femoral component in the TKA knee were shape-matched to the condyles of the native femur to create a virtual plan. The shape-matched femoral component served as a reference from which to determine alignment deviations of the femoral component implanted in the ipsilateral femur. The Forgotten Joint Score (FJS) and Oxford Knee Score (OKS) were obtained at an average of 20 months. RESULTS: For proximal-distal and anterior-posterior positions and varus-valgus and internal-external orientations of the femoral component, the root mean square deviations from the planned joint lines ranged from 1.4 to 1.5 (mm or degrees). The mean differences ranged from - 0.1 to 0.2 (mm or degrees) indicating an absence of systematic alignment deviations. The proportion of knees with joint lines within ± 2 mm and ± 2° of the joint lines of virtually planned knees ranged from 83 to 92%. For the FJS and OKS, the median values were 79 (out of 100) and 45 (out of 48), respectively, and there were no significant correlations between deviations in the positions and orientations and either the FJS or the OKS. CONCLUSION: Alignment deviations were bounded by 2 mm and 2° for most knees, which previous biomechanical studies have shown reduce the risks of stiffness, loss of extension, loss of flexion, and tibial compartment forces higher than those of the native knee. Moreover, because median FJS and OKS were relatively high, and because larger alignment deviations did not correlate with lower outcome scores, deviations did not affect clinical outcomes. These results validate calipered KA TKA as a surgical technique which closely restores the distal and posterior femoral joint lines to those planned and achieves concomitant high patient-reported outcome scores. Thus, surgeons can use the calipered KA TKA technique with confidence that the surgical alignment goal will be satisfied with sufficient accuracy that high patient-reported outcomes are achieved. LEVEL OF EVIDENCE: III.

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)0.005
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.069
GPT teacher head0.320
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 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

Citations41
Published2019
Admission routes1
Has abstractyes

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