Prevalence of Musculoskeletal Manifestations in Type 2 Diabetes: A Single Centre, Cross-Sectional Study
Bibliographic record
Abstract
Objective: The study was aimed to evaluate the prevalence of musculoskeletal manifestations in patients with type 2 diabetes (T2D). Materials and methods: In this single center, cross sectional study, 300 patients with clinically documented T2D were recruited from the outpatient clinic. Demographics, diabetes history, family history, treatment modalities, musculoskeletal symptoms were self-reported by participants. Anthropometric measurements and musculoskeletal examination were conducted by investigators. Complete blood count, fasting and postprandial plasma glucose, glycated hemoglobin (HbA1c), urine analysis, and X rays of the symptomatic joints were performed. Results: Of 300 patients with T2D, musculoskeletal manifestations were observed in 50.7%. Osteoarthritis of the knee was the most common manifestation (20.3%) followed by carpal tunnel syndrome (10.7%), adhesive capsulitis (8.3%), diffuse idiopathic skeletal hyperostosis (7.3%), diabetic cheiroarthropathy (6.0%), flexor tenosynovitis (2.3%), and Dupuytren’s contracture (0.7%). Age (p = 0.001), T2D duration (p = 0.004), BMI (p = 0.031) and HbA1c (p= 0.006) were associated with increased prevalence of musculoskeletal manifestations. Conclusions: Prevalence of musculoskeletal manifestations is higher in people with T2D. Advanced age, longer duration of disease, overweight and high HbA1c levels are associated with increased prevalence of musculoskeletal manifestations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".