ArticleCartilage2021
Longitudinal Change in Knee Cartilage Thickness and Function in Subjects with and without MRI-Diagnosed Cartilage Damage.
Article in Cartilage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Unworn cartilage in total knee arthroplasty strongly deviates from 2 mm: MRI, robotic-assisted and ruler assessment.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- A comparison of quantitative and semi-quantitative methods for assessing cartilage status and change over time; data from the osteoarthritis initiative.BMC musculoskeletal disorders · 2025Article
- Development and evaluation of nomograms for predicting osteoarthritis progression based on MRI cartilage parameters: data from the FNIH OA biomarkers Consortium.BMC medical imaging · 2023Article
- Linking physical activity with clinical, functional, and structural outcomes: an evidence map using the Osteoarthritis Initiative.Clinical rheumatology · 2022Review
- Deep learning for large scale MRI-based morphological phenotyping of osteoarthritis.Scientific reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveCartilage damage diagnosed by magnetic resonance imaging (MRI) is highly prevalent in the population. In this article, we explore whether such cartilage damage is associated with greater longitudinal change in 3D cartilage thickness and knee function in subjects without (risk factors of) knee osteoarthritis.
designEighty-two knees of Osteoarthritis Initiative healthy reference cohort participants had baseline and 4-year follow-up MRI and knee function data. Baseline presence of semiquantitatively assessed MRI-based cartilage damage (MOAKS [MRI Osteoarthritis Knee Score] ≥ grade 1.0) was recorded by an experienced radiologist. Longitudinal femorotibial cartilage thickness change was determined after segmentation, using location-independent methodology. Knee function was evaluated by patient-reported outcomes and functional performance measures. Statistical comparisons included analysis of covariance adjusting for age, sex, and body mass index.
resultsForty-five percent of the participants had cartilage damage in at least one femorotibial subregion; the cartilage thickness change score was 15% greater in participants with than in those without damage (1216 ± 434 vs. 1058 ± 277 µm). This difference reached borderline statistical significance with and without adjustment for age, sex, and body mass index (
conclusionsIn the absence of osteoarthritis risk factors, semiquantitatively assessed MRI-based cartilage damage appears to be associated with greater longitudinal location-independent femorotibial cartilage thickness changes, but not with greater functional deteriorations.
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Registered trials
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.