Incidence rates of Parkinson’s disease in Mexico: Analysis of 2014-2017 statistics
Bibliographic record
Abstract
The objective of this study was to estimate and analyze the incidence and incidence rates of Parkinson's disease (PD) in Mexico. Methods: Data on new cases of PD from January 2014 to December 2017 were extracted from the electronic Morbidity Annals and Epidemiological Bulletin published by the Secretary of Health. Crude and age-standardized incidence and incidence rate were calculated and compared with reports from other countries. Results: The overall incidence rate for the 2014-2017 period was 37.92/100,000 (incidence density of 9.48/100,000 person-years). The incidence rate in the 65+ population was 313.94/100,000. The incidence rate was higher in men than in women (42.22 vs. 34.78/100,000, respectively). Conclusion: The incidence rate in Mexican population increases with age, and it is slightly more frequent in men but is lower in comparison to developed countries. Differences in incidence rates between developed and underdeveloped countries merit further studies.
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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 | 0.000 | 0.000 |
| 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".