ArticleSkeletal radiology2018
Radiological glenohumeral osteoarthritis in long-term type 1 diabetes. Prevalence and reliability of three classification systems. The Dialong shoulder study.
Article in Skeletal radiology, 2018. 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, 10 citations in OpenAlex.
- AI-Assisted Detection of Supraspinatus Tendon Pathologies Using a Hierarchical Deep Learning Model to Improve Clinical Applicability: Development and Evaluation Study.JMIR medical informatics · 2026Article
- Elevation of MMP1 and ADAMTS5 mRNA expression in glenohumeral synovia of patients with hypercholesterolemia.Journal of orthopaedic surgery and research · 2022Article
- Interrater reliability of physical examination tests in the acute phase of shoulder injuries.BMC musculoskeletal disorders · 2021Article
- The Intriguing Intersection of Type 2 Diabetes, Obesity-Related Insulin Resistance, and Osteoarthritis.The Journal of clinical endocrinology and metabolism · 2021Article
- Insulin Resistance in Osteoarthritis: Similar Mechanisms to Type 2 Diabetes Mellitus.Journal of nutrition and metabolism · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveIn the present study, we evaluate the intra- and interrater agreement of radiological glenohumeral OA using three different classification systems and estimate the prevalence of radiological and clinical glenohumeral OA in patients with type 1 diabetes mellitus (DM1), for over 45 years and controls (The Dialong study). MATERIALS AND
methodsWe included 102 patients with DM1 (49% women, mean age, 61.9 years) and 73 controls (57% women, mean age, 62.6 years). Anterior-posterior shoulder radiographs were interpreted by two observers applying the Kellgren-Lawrence (K-L), Samilson-Prieto (S-P) and Samilson-Prieto Allain (S-PA) classifications.
resultsThe interrater agreement was moderate (weighted kappa, 0.46 to 0.48) for all classifications and the intrarater agreement mainly substantial (0.48-0.86) for both observers. The agreed prevalence of radiological OA was 26 and 18% (OR 1.6 (0.8 to 3.3), p = 0.22, 44 and 26% (OR 2.2 (1.2 to 4.2), p = 0.02) and 30 and 17% (OR 2.1 (1.0 to 4.5), p = 0.05) for the K-L, S-P and S-PA classifications respectively in the diabetes and control groups. The prevalence of moderate or severe radiological OA was 1 to 6% and clinical OA 1 to 2% with no difference between the groups.
conclusionThe prevalence of radiological glenohumeral OA was higher in the diabetes group with the Samilson-Prieto classification systems, but not associated with clinical OA. The interrater agreement was moderate. We recommend the Samilson-Prieto Allain classification for glenohumeral OA to avoid interpretation of osteophytes < 1 mm as OA in patient groups with a low pre-test likelihood of glenohumeral OA.
Indexed as
Identifiers
What OpenQuestion holds
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.