Depression and cardiovascular disease in women: is there a common immunological basis? A theoretical synthesis
Bibliographic record
Abstract
Clinical studies have established an inherent comorbidity between depression and the development of cardiovascular disease (CVD). Furthermore, this comorbidity seems to be more amplified in women than in men. To further investigate this comorbidity, a thorough literature review was conducted on studies from 1992 to date. The PubMed database was accessed using the keywords: cardiovascular disease, inflammation, depression, and sex differences. Both human and animal studies were considered. This review takes the standpoint that depression and CVD are both inflammatory disorders, and that their co-occurrence may be related to how the hypothalamic-pituitary-adrenal axis, serotonergic transmission and circulation, and the renin-angiotensin-aldosterone system via angiotensin II are affected by the excess secretion of proinflammatory cytokines. More recently, preliminary research attributes this systemic inflammation to a global deficiency in CD4+CD25+FOXP3 regulatory T cells. 17-β estradiol and progesterone mediated modulation of cytokine secretion may partially explain the sex differences observed. These hormones and reproductive events associated with hormonal fluctuations are discussed in depth, including the analysis of perinatal models of depression and CVD, including preeclampsia. However, as evidenced by this review, there is a need for mechanistic research in humans to truly understand the nature and directionality of the relationship between depression and CVD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".