Metabolic Syndrome and Rheumatic Diseases in Chad: Prevalence, Associated Factors and Clinical Impact
Bibliographic record
Abstract
Objective: To assess the prevalence of metabolic syndrome (MS) and its clinical impact among patients with rheumatic diseases in Chad.Methods: A retrospective, cross-sectional, analytical study was conducted at the HRT Rheumatology Department from January 2018 to May 2024. Among 5000 patients, 330 fulfilled IDF and 214 WHO criteria for MS. Clinical, laboratory, and therapeutic data, as well as functional scores (Short Form-36 (SF-36), Disease Activity Score in 28 joints (DAS28), Bath Ankylosing Spondylitis Functional Index (BASFI), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)), were systematically analyzed.Results: MS prevalence was 6.6% (IDF) and 4.3% (WHO). The cohort was predominantly female (88.7%), with a mean age of 49.8 ± 12.4 years. The most frequent components were abdominal obesity (93.0%), hypertension (89.7%), and hyperglycemia (64.8%). Associated diseases included connective tissue disorders (40.9%), degenerative conditions (34.3%), and autoinflammatory diseases (24.8%). After a mean two-year follow-up, functional and quality-of-life scores improved, although 13 patients developed cardio-renal complications. This retrospective single-center design may limit the generalizability of our findings. Conclusions: MS is common among rheumatology patients in Chad and worsens disease prognosis. Systematic screening and multidisciplinary management are essential to improve outcomes and quality of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".