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Association Between Symptomatic Knee Osteoarthritis and Blood Glucose Control in Persons with Type 2 Diabetes

2025· article· en· W6966077946 on OpenAlexaffvenueabout

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsWomen's College HospitalTrillium Health CentreUniversity of Toronto
Fundersnot available
KeywordsOsteoarthritisBody mass indexType 2 diabetesDiabetes mellitusLogistic regressionKnee painOdds ratioKnee Joint

Abstract

fetched live from OpenAlex

Objectives There is a high prevalence of knee osteoarthritis (OA) in people with type 2 diabetes (T2D), and knee OA increases risk for diabetes complications. Our objective was to assess the association between symptomatic knee OA and attainment of target blood glucose levels in individuals with T2D. Methods In this cross-sectional study, we recruited individuals with T2D aged ≥45 years from diabetes clinics at 3 academic hospitals in Toronto. Participants completed standardized online questionnaires that assessed demographics, comorbidities, height and weight, and joint symptoms. From clinic records we abstracted participants’ most recent HbA1c (within 3 months). Knee OA was defined as fulfilling NICE criteria. We considered blood glucose control at target if HbA1c was ≤7.0%. We used multivariable logistic regression to assess the association between knee OA and being at blood glucose target, adjusting for age and gender. We then examined the effect of further adjusting for body mass index (BMI). In secondary analyses, we repeated modeling with exposure of interest knee OA with knee pain ≥20/100 on pain numeric rating scale (NRS) (yes/no). Results We included 351 participants. Mean age was 66.9 (SD 9.8) years, 50.7% women, mean BMI 29.1 (SD 6.8) kg/m 2 , and 28.5% fulfilled NICE criteria for knee OA. Mean HbA1c was 7.4 (SD 1.2); 44% had HbA1c at target (≤7.0%). In univariable analysis, those with knee OA had lower odds of being at target (OR 0.60, 95% CI 0.37 to 0.97). Results were similar after adjusting for age and gender (OR 0.59, 95% CI 0.36 to 0.95). When further adjusting for BMI the effect of knee OA was attenuated and was not statistically significant (OR 0.65, 95% CI 0.39 to 1.06). When exposure of interest was knee OA with self-reported pain ≥20/100, we found a stronger negative association; this met statistical significance even after adjusting for BMI (OR 0.59, 95% CI 0.35 to 0.997) (Figure 1). Figure 1. Effect of (A) knee osteoarthritis overall and (B) knee osteoarthritis with pain ≥20/100 on meeting glyeemic target (HbAlc ≤7.0%). Conclusion Individuals with T2D with knee OA are less likely to be at the recommended target for glycemic control. This association was stronger for those who currently reported pain and remained significant even after adjusting for BMI. This suggests that symptomatic knee OA may increase the risk of diabetes complications through worse glycemic control, and symptom severity is likely important. Further studies are needed to better understand this relationship, as well as the role of additional mechanisms by which knee OA could lead to diabetes complications such as cardiorespiratory fitness and/or systemic inflammation. Best Abstract on Research by Early Career Faculty Award

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.218
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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