Gender dimension in cardio-pulmonary continuum
Bibliographic record
Abstract
Cardio-pulmonary diseases, which were once regarded as a man's illness, have been one of the leading causes of morbidity and mortality for both men and women in many countries in recent years. Both gender and sex influence the functional and structural changes in the human body and therefore play an important role in disease clinical manifestation, treatment choice, and/or response to treatment and prognosis of health outcomes. The gender dimension integrates sex and gender analysis in health sciences and medical research, however, it is still relatively overlooked suggesting the need for empowerment in the medical research community. Latest advances in the field of cardiovascular research have provided supportive evidence that the application of biological variables of sex has led to the understanding that heart disease in females may have different pathophysiology compared to males, particularly in younger adults. It has also resulted in new diagnostic techniques and a better understanding of symptomatology, while gender analysis has informed more appropriate risk stratification and prevention strategies. The existing knowledge in the pulmonary field shows the higher prevalence of pulmonary disorders among females, however, the role of gender as a socio-cultural construct has yet to be explored for the implementation of targeted interventions. The purpose of this review is to introduce the concept of gender dimension and its importance for the cardiopulmonary continuum with a focus on shared pathophysiology and disease presentation in addition to interrelation with chronic kidney disease. The review presents basic knowledge of what gender dimension means, and the application of sex and gender aspects in cardiovascular medicine with a specific focus on early pulmonary development, pulmonary hypertension, and chronic obstructive pulmonary disease (COPD). Early vascular aging and inflammation have been presented as a potential pathophysiological link, with further interactions between the cardiopulmonary continuum and chronic kidney disease. Finally, implications for potential future research have been provided to increase the impact of gender dimension on research excellence that would add value to everybody, foster toward precision medicine and ultimately improve human 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".