[Coronary heart disease in Mexico and the clinical epidemiological and preventive relevance].
Bibliographic record
Abstract
Coronary heart disease is dominant among heart diseases in the population, a problem to control. Heart diseases have been first place in the general mortality for the last 20 years. The trend show an annual increase without control. Atherosclerosis is responsible for at least for one fourth of all deaths in the country. The combined data of mortality and morbidity, from hospital discharges or the whole country, disclose that one out of three die of acute myocardial infarction (AMI). While only 8% of all deaths registered were admitted to a hospital. Most, 92% were never admitted to any hospital for some reason. The estimated annual incidence of AMI cases is 140,000, on the basis of 3 cases surviving for each case death, accounted by the Death Certification System, which rounds 35,000. Standardized mortality rates of AMI in Mexico are greater than in USA o Canada creating a more concerned worry. The most probable explanation to that situation is lack of preventive care, which should also include the acute care and before reaching the hospital facilities. Running the same chances are hypertension crisis and strokes and diabetic complications. The appropriate care for critical situations might reduce significantly the cardiovascular mortality in the country, in a short and middle term. Prevention is not only for chronic conditions but for acute and critical situations. The programs of preventive care should also include cultural promotion and community awareness. The timely care is life and myocardium saving. The reinforcement of prior to hospital care reduces the delay for AMI adequate intervention. These activities agree quite well with the ongoing programs of CPR, organizing the surviving chain and the training programs for paramedical emergency technicians.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".