Bibliographic record
Abstract
BACKGROUND: Several mental disorders has been associated with cardiovascular disease (CVD), although stress may have the strongest correlation. In this narrative review, we examine how stress is linked to CVD. RESULTS: Stress can be secondary to multiple factors and it can be imposed on an individual in more or less manifest ways. Psychosocial stress can result from adverse social circumstances such as poverty, racial, gender, religious disparities or discrimination, violence and environmental pollution. Large segments of the population are forced to endure poor working conditions, low food quality, physical and verbal abuse not only in the developing world but also in more flourishing societies as well. Wars that have ignited widely of late are inherently stressful events with potential enduring effects after the conflicts. Isolation and loneliness are growing issues in modern societies and impose a heavy burden of stress. Epidemiological studies have shown that stress is linked to CVD through an increased incidence of traditional risk factors (smoking, hypertension, insulin resistance and obesity). Experimental and laboratory evidence has shown a link between stress and CVD via neuro-endocrine, inflammatory and immune pathways. Patients with prior CV events affected by stress are at higher risk of recurrent events compared to similar patients without stressful conditions. CONCLUSIONS: The close association between stress and CVD suggests that interventions to limit the effect of stress may result in a reduced incidence of de novo and recurrent CV events. Physicians should be aware of the importance of screening for stress in patients with CVD. Future efforts should be directed to the development of easily implementable screening tools and targeted interventions within healthcare frameworks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".