Impact of COVID-19 on the cardiovascular health of women: a review by the Italian Society of Cardiology Working Group on ‘gender cardiovascular diseases’
Bibliographic record
Abstract
The coronavirus disease 19 (COVID-19), due to coronavirus 2 (SARS-CoV-2) infection, presents with an extremely heterogeneous spectrum of symptoms and signs. COVID-19 susceptibility and mortality show a significant sex imbalance, with men being more prone to infection and showing a higher rate of hospitalization and mortality than women. In particular, cardiovascular diseases (preexistent or arising upon infection) play a central role in COVID-19 outcomes, differently in men and women. This review will discuss the potential mechanisms accounting for sex/gender influence in vulnerability to COVID-19. Such variability can be ascribed to both sex-related biological factors and sex-related behavioural traits. Sex differences in cardiovascular disease and COVID-19 involve the endothelial dysfunction, the innate immune system and the renin-angiotensin system (RAS). Furthermore, the angiotensin-converting enzyme 2 (ACE2) is involved in disease pathogenesis in cardiovascular disease and COVID-19 and it shows hormone-dependent actions. The incidence of myocardial injury during COVID-19 is sex-dependent, predominantly in association with a greater degree of inflammation and coagulation disorders among men. Its pathogenesis is not fully elucidated, but the main theories foresee a direct role for the ACE2 receptor, the hyperimmune response and the RAS imbalance, which may also lead to isolated presentation of COVID-19-mediated myopericarditis. Moreover, the latest evidence on cardiovascular diseases and their relationship with COVID-19 during pregnancy will be discussed. Finally, authors will analyse the prevalence of the long-covid syndrome between the two sexes and its impact on the quality of life and cardiovascular health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".