Evidence map›Paper›PMID 41213302›Full record

ArticleBone & joint open2025

Interobserver reliability of Coronal Plane Alignment of the Knee (CPAK) phenotype classification : external validation using data from the Osteoarthritis Initiative.

William Wynell-Mayow, Thomas A G Hall, Abhinav Singh, Richard J van Arkel, Gareth G Jones

Abstract read
In one paragraph

Article in Bone & joint open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. [Impact of coronal plane alignment of knee phenotype alteration on short-term effectiveness in robot-assisted total knee arthroplasty].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2026
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

William Wynell-MayowImperial College Healthcare NHS Trust, St Mary's Hospital, London, UK.
Thomas A G HallBiomechanics Group, Department of Mechanical Engineering, Imperial College London, London, UK.
Abhinav SinghNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Richard J van ArkelBiomechanics Group, Department of Mechanical Engineering, Imperial College London, London, UK.
Gareth G JonesImperial College Healthcare NHS Trust, St Mary's Hospital, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Coronal Plane Alignment of the Knee (CPAK) phenotyping is gaining momentum in research and clinical practice to understand individualized knee alignments and predict knee balance in total knee arthroplasty (TKA). The nine CPAK classes are based on joint line obliquity (JLO) and arithmetic hip-knee-ankle angle (aHKA), which are calculated using the medial proximal tibial angle (MPTA) and lateral distal femoral angle (LDFA). This study aims to assess CPAK classification reproducibility, and analyze what level of angular error is associated with CPAK misclassification. Methods: Two readers labelled 75 long-leg radiographs (LLRs) from the Osteoarthritis Initiative database for analyses of CPAK inter-reader reproducibility. A single reader then labelled and classified phenotypes for an aggregate total of 1,128 LLRs. Finally, Monte Carlo simulations were run based on 1,128-patient phenotype distribution and the inter-reader reproducibility statistics to understand how CPAK agreement rates were affected by the reproducibility of MPTA and LDFA measurements. Results: There was excellent reproducibility in MPTA and LDFA measurements (mean absolute error: 0.41°/0.71°; and intraclass correlation coefficient: 0.96°/0.91°, respectively). These small angular deviations led to one-in-five disagreement in CPAK classification (20.0%; 95% CI 10.9% to 29.1%). An aHKA mean absolute error of < 0.1°, which is potentially unattainable, would be required to reduce inter-reader CPAK disagreement to below 95%. Conclusion: CPAK phenotyping from long-leg radiographs may result in clinically significant rates of misclassification. CT imaging may improve reliability, particularly in cases where aHKA and JLO are near to discriminatory values.

Identifiers

PMID41213302
PMCPMC12602010

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.