Evidence map›Paper›PMID 41137119›Full record

ArticleJournal of orthopaedic surgery and research2025

From variability to consistency: building a Kellgren-Lawrence gonarthrosis dataset.

Salih Beyaz, Sahika Betul Yayli, Kutay Kılıç

Abstract readMulticenter Study
In one paragraph

Article in Journal of orthopaedic surgery and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Salih BeyazAdana Turgut Noyan Research and Training Centre, Orthopedics and Traumatology Department, Baskent University, Adana, Turkey. sbeyaz@baskent.edu.tr.ORCID http://orcid.org/0000-0002-5788-5116
Sahika Betul YayliArtificial Intelligence & Digital Analytic Solutions, Turkcell Technology, İstanbul, Turkey.ORCID http://orcid.org/0000-0001-5057-8634
Kutay KılıçArtificial Intelligence & Digital Analytic Solutions, Turkcell Technology, İstanbul, Turkey.ORCID http://orcid.org/0000-0002-0247-079X

Funding

Başkent University KA22/434
6 · The paper itself

Abstract

objectiveThis study aims to address variability in Kellgren-Lawrence (KL) staging by analyzing interobserver differences between radiologists and orthopedic surgeons to build unbiased datasets for AI-driven gonarthrosis solutions.

methodsThis retrospective study analyzed 15,159 weight-bearing AP knee radiographs from patients aged 18 years and older collected from five centers between 2011 and 2020. The radiographs were labeled by two radiologists and two orthopedic surgeons independently, followed by a consensus evaluation by two experienced orthopedic specialists. KL staging was assessed both on a 0-4 scale and in two clinically relevant categories: early stage (KL ≤ 2) and advanced stage (KL ≥ 3). In clinical practice, low stage cases are generally managed with conservative treatments, while high-stage cases often indicate a higher need for surgical intervention.

resultsA total of 15,159 knee radiographs were analyzed, with participants comprising 6,207 (40.9%) males and 8,952 (59.1%) females, with a mean age of 56.97 ± 4.2 years. The agreement between radiologists and experts in the KL staging ranged from κ = 0.085 to κ = 0.172, while agreement between orthopedic surgeons and experts ranged from κ = 0.18 to κ = 0.307. These values indicate slight to fair agreement among radiologists and fair to moderate agreement among orthopedic surgeons on the original KL stage The categorization of the KL stages into two groups (KL ≤ 2 vs. KL ≥ 3) resulted in enhanced inter-rater reliability, with orthopedic surgeons demonstrating substantial agreement (κ = 0.637-0.692) compared to radiologists (κ = 0.183-0.230). The highest intra-professional agreement was observed between Radiologist 1 and Radiologist 2 (κ = 0.55) on the 0-4 the KL scale and between Orthopedic Surgeon 1 and Orthopedic Surgeon 2 (κ = 0.642) in the two-category classification.

conclusionsOrthopedic surgeons showed higher agreement with experts and among themselves, particularly in advanced stages (KL ≥ 3), compared to radiologists, who demonstrated only mild to moderate agreement. Categorizing KL stages into early (KL ≤ 2) and advanced (KL ≥ 3) groups improved interobserver reliability, thereby facilitating the development of standardized AI datasets.

Indexed as

Datasets as TopicKnee JointOsteoarthritis, KneeAdultAgedFemaleHumansMaleMiddle AgedObserver VariationOrthopedic SurgeonsRadiographyRadiologistsRetrospective StudiesAlgorithm training, gonarthrosisInterobserver reliabilityKellgren LawrenceKnee

Identifiers

PMID41137119
PMCPMC12553152

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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.