Epidemiology of the Rheumatic Diseases in Mexico. A Study of 5 Regions Based on the COPCORD Methodology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence of musculoskeletal (MSK) disorders and to describe predicting variables associated with rheumatic diseases in 5 regions of México. METHODS: This was a cross-sectional, community-based study performed in 5 regions in México. The methodology followed the guidelines proposed by the Community Oriented Program for the Control of the Rheumatic Diseases (COPCORD). A standardized methodology was used at all sites, with trained personnel following a common protocol of interviewing adult subjects in their household. A "positive case" was defined as an individual with nontraumatic MSK pain of > 1 on a visual analog pain scale (0 to 10) during the last 7 days. All positive cases were referred to internists or rheumatologists for further clinical evaluation, diagnosis, and proper treatment. RESULTS: The study included 19,213 individuals; 11,602 (68.8%) were female, and their mean age was 42.8 (SD 17.9) years. The prevalence of MSK pain was 25.5%, but significant variations (7.1% to 43.5%) across geographical regions occurred. The prevalence of osteoarthritis was 10.5%, back pain 5.8%, rheumatic regional pain syndromes 3.8%, rheumatoid arthritis 1.6%, fibromyalgia 0.7%, and gout 0.3%. The prevalence of MSK manifestations was associated with older age and female gender. CONCLUSION: The prevalence of MSK pain in our study was 25.5%. Geographic variations in the prevalence of MSK pain and specific diagnoses suggested a role for geographic factors in the prevalence of rheumatic diseases.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it