Disasters and the Heart: a Review of the Effects of Earthquake-Induced Stress on Cardiovascular Disease
Bibliographic record
Abstract
There is growing evidence that stress contributes to cardiovascular disease. Chronic stress contributes to the atherosclerotic process through increased allostatic load, which is mediated by the neuroendocrine and immune systems (sympathetic nervous system and hypothalamus-pituitary adrenal axis) and related chronic risk factors (insulin resistance syndrome, hypertension, diabetes, and hyperlipidemia). In addition, acute stress can trigger cardiovascular events predominantly through sympathetic nervous activation and potentiation of acute risk factors (blood pressure increase, endothelial cell dysfunction, increased blood viscosity, and platelet and hemostatic activation). Earthquakes provide a good example of naturally occurring acute and chronic stress, and in this review we focus mainly on the effects of the Hanshin-Awaji earthquake on the cardiovascular system. The Hanshin-Awaji earthquake resulted in a 3-fold increase of myocardial infarctions in people living close to the epicenter, particularly in women, with most of the increase occurring in nighttime-onset events. There was also a near doubling in the frequency of strokes. These effects may be mediated by changes in hemostatic factors, as demonstrated by an increase of D-dimer, von Willebrand factor, and tissue-type plasminogen activator (tPA) antigen. Blood pressure also increased after the earthquake, and was prolonged for several weeks in patients with microalbuminuria.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".