Evidence map›Paper›PMID 34648543›Full record

ArticlePloS one2021

A whole-joint, unidimensional, irreversible, and fine-grained MRI knee osteoarthritis severity score, based on cartilage, osteophytes and meniscus (OA-COM).

Eric C Sayre, Ali Guermazi, Savvas Nicolaou, John M Esdaile, Jacek A Kopec, Joel Singer, Hubert Wong, Anona Thorne, Jolanda Cibere

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. 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
0.7field-weighted citation impact, top 29% of its field
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, 6 citations in OpenAlex.

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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

9 authors at 3 institutions in 2 countries.

Eric C SayreArthritis Research Canada, Vancouver, British Columbia, Canada.ORCID 0000-0002-4526-278X
Ali GuermaziRadiology, Boston University School of Medicine, Boston, Massachusetts, United States of America.
Savvas NicolaouRadiology, University of British Columbia, Vancouver, British Columbia, Canada.
John M EsdaileArthritis Research Canada, Vancouver, British Columbia, Canada.
Jacek A KopecArthritis Research Canada, Vancouver, British Columbia, Canada.
Joel SingerSchool of Population & Public Health, University of British Columbia, Vancouver, British Columbia, Canada.
Hubert WongSchool of Population & Public Health, University of British Columbia, Vancouver, British Columbia, Canada.
Anona ThorneSchool of Population & Public Health, University of British Columbia, Vancouver, British Columbia, Canada.
Jolanda CibereArthritis Research Canada, Vancouver, British Columbia, Canada.
University of British Columbia · CABoston University · USResearch Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a whole-joint, unidimensional, irreversible, and fine-grained MRI knee osteoarthritis (OA) severity score, based on cartilage, osteophytes and meniscus (OA-COM), and to predict progression across different severity states using OA-COM as outcome and clinical variables as predictors.

methodsPopulation-based knee pain cohort aged 40-79 was assessed at baseline and 7-year follow-up. OA-COM score was defined as the sum of MRI scores for cartilage, osteophytes and menisci, measured at 6, 8 and 6 sites, total score 0-54. To anchor severity levels, we fit cross-sectional logistic models using OA-COM to predict Kellgren-Lawrence (KL) grades in subsets at or one point below each grade. OA-COM threshold scores were selected on sensitivity, specificity, positive and negative predictive value. We developed longitudinal logistic models for OA-COM progression over each threshold over 7 years. Potential predictors included age, sex, BMI, malalignment, physical exam effusion, quadriceps weakness, and crepitus, selected on area under the receiver operating characteristic curve (AUC) and Akaike's Information Criterion (AIC).

resultsOptimal OA-COM thresholds were 12, 18, 24 and 30, for KL grades 1 to 4. Significant predictors of progression (depending on threshold) included physical exam effusion, malalignment and female sex, with other selected predictors age, BMI and crepitus.

conclusionOA-COM (0-54 range) is a whole-joint, unidimensional, irreversible, and fine-grained MRI OA severity score reflecting cartilage, osteophytes and menisci. OA-COM scores 12, 18, 24 and 30 are equivalent to KL grades 1 to 4, while offering fine-grained differentiation of states between KL grades, and within pre-radiographic disease (KL = 0) or late-stage disease (KL = 4). In modeling, several clinical variables predicted progression across different states over 7 years.

Indexed as

Magnetic Resonance ImagingAdultAgedAge FactorsArea Under CurveBody Mass IndexCartilage, ArticularCohort StudiesFemaleHumansKnee JointLogistic ModelsMaleMeniscusMiddle AgedOsteoarthritis, Knee

Identifiers

PMID34648543
PMCPMC8516189
OpenAlexW3205044849

What OpenQuestion holds

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LicenceCC BY
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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.