Prevalence of Rheumatic Regional Pain Syndromes in Adults from Mexico: A Community Survey Using COPCORD for Screening and Syndrome-specific Diagnostic Criteria
Bibliographic record
Abstract
OBJECTIVE: To assess the prevalence of rheumatic regional pain syndromes (RRPS) in 3 geographical areas of México using the Community Oriented Program in the Rheumatic Diseases (COPCORD) screening methodology and validate by expert consensus on case-based definitions. METHODS: By means of an address-based sample generated through a multistage, stratified, randomized method, a cross-sectional survey was performed on adult residents (n = 12,686; age 43.6 ± 17.3 yrs; women 61.9%) of the states of Nuevo León, Yucatán, and México City. Diagnostic criteria for specific upper (Southampton group criteria) and lower limb (ad hoc expert consensus) RRPS were applied to all subjects with limb pain as detected by COPCORD questionnaire. RESULTS: The overall prevalence of RRPS was 5.0% (95% CI 4.7-5.4). The most frequent syndrome was rotator cuff tendinopathy (2.36%); followed by inferior heel pain (0.64%); lateral epicondylalgia (0.63%); medial epicondylalgia (0.52%); trigger finger (0.42%); carpal tunnel syndrome (0.36%); anserine bursitis (0.34%); de Quervain's tendinopathy (0.30%); shoulder bicipital tendinopathy (0.27%); trochanteric syndrome (0.11%); and Achilles tendinopathy (0.10%). There were anatomic regional variations in the prevalence of limb pain: Yucatán 3.1% (95% CI 2.5-3.6); Nuevo León 7.0% (95% CI 6.3-7.7); and México City 10.8% (95% CI 9.8-11.8). Similarly, the prevalence of RRPS showed marked geographical variation: Yucatán 2.3% (95% CI 1.8-2.8); Nuevo León 5.6% (95% CI 5.0-6.3); and México City 6.9% (95% CI 6.2-7.7). CONCLUSION: The overall prevalence of RRPS in México was 5.0%. Geographical variations raise the possibility that the prevalence of RRPS is influenced by socioeconomic, ethnic, or demographic factors.
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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 | 0.004 | 0.001 |
| 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 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".