Evidence map›Paper›PMID 36817090›Full record

ArticleOsteoarthritis and cartilage open2023

Patterns of variation among baseline femoral and tibial cartilage thickness and clinical features: Data from the osteoarthritis initiative.

Thomas H Keefe, Mary Catherine Minnig, Liubov Arbeeva, Marc Niethammer, Zhenlin Xu, Zhengyang Shen, Boqi Chen, Daniel B Nissman, Yvonne M Golightly, J S Marron and 1 more

Abstract read
In one paragraph

Article in Osteoarthritis and cartilage open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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

11 authors.

Thomas H KeefeStatistics and Operations Research, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
Mary Catherine MinnigThurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Liubov ArbeevaThurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Marc NiethammerDepartment of Computer Science, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
Zhenlin XuDepartment of Computer Science, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
Zhengyang ShenDepartment of Computer Science, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
Boqi ChenDepartment of Computer Science, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
Daniel B NissmanDepartment of Radiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Yvonne M GolightlyThurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
J S MarronStatistics and Operations Research, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
Amanda E NelsonThurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Funding

UNC Core Center for Clinical ResearchP30AR072580 · NIAMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LEIGH Fleming CALLAHAN, Amanda E Nelson · 2019 to 2026
$6.1M
6 · The paper itself

Abstract

Objective: To employ novel methodologies to identify phenotypes in knee OA based on variation among three baseline data blocks: 1) femoral cartilage thickness, 2) tibial cartilage thickness, and 3) participant characteristics and clinical features. Methods: Baseline data were from 3321 Osteoarthritis Initiative (OAI) participants with available cartilage thickness maps (6265 knees) and 77 clinical features. Cartilage maps were obtained from 3D DESS MR images using a deep-learning based segmentation approach and an atlas-based analysis developed by our group. Angle-based Joint and Individual Variation Explained (AJIVE) was used to capture and quantify variation, both Results: Three major modes of variation were shared across the three data blocks. Mode 1 reflected overall thicker cartilage among men, those with higher education, and greater knee forces; Mode 2 showed associations between worsening Kellgren-Lawrence Grade, medial cartilage thinning, and worsening symptoms; and Mode 3 contrasted lateral and medial-predominant cartilage loss associated with BMI and malalignment. Each data block also demonstrated individual, independent modes of variation consistent with the known discordance between symptoms and structure in knee OA and reflecting the importance of features such as physical function, symptoms, and comorbid conditions independent of structural damage. Conclusions: This exploratory analysis, combining the rich OAI dataset with novel methods for determining and visualizing cartilage thickness, reinforces known associations in knee OA while providing insights into the potential for data integration in knee OA phenotyping.

Indexed as

cartilage thicknessKnee osteoarthritisModes of variation

Identifiers

PMID36817090
PMCPMC9932103

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Registered trials

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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.