Accidente cerebrovascular en poblaciones situadas a grandes alturas: revisión y análisis de los factores de riesgo
Bibliographic record
Abstract
Despite our understanding about cerebrovascular accident, also known as stroke, its risk factors, treatment and prevention, it remains the leading cause of death of both men and women worldwide. Several risk factors have been associated with higher incidence of stroke such as systolic or diastolic hypertension, diabetes, hypercholesterolemia, cigarette smoking or obesity. Other such as cocaine abuse, heavy alcohol consumption, AIDS, Vitamin D and protein C deficiency are also important non traditional risk factors, associated with increased prevalence of stroke. Nevertheless, high altitude exposure and potential impact of hypoxia as a stroke risk factor –in people living or visiting high altitude environments– has not been clearly established yet. This review will analyze the available evidence concerning about the association of risk factors with higher prevalence of stroke during acute or chronic high altitude exposure, either in high altitude dwellers or new sojourners. The author will examine the available evidence behind the possible physiopathology of ischemic and hemorrhagic stroke in those living at high altitudes. We conclude that living or visiting high altitude locations is a potential non traditional risk factor associated with higher incidence of ischemic stroke, especially in young otherwise healthy men. The hypobaric hypoxia level or the altitude in which stroke commonly starts is very difficult to establish. However, it is well known that as soon as hypoxia causes acclimatization, risk becomes higher. The evidence suggests that high altitude exposure and consequent hypobaric hypoxia are important environmental factors to be considered. The time length of exposure, high levels of hematocrit and polycythemia are the most prevalent risk factors associated with higher incidence of stroke in subjects exposed to chronic or acute hypoxia.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".