Is cardiovascular disease risk in transgender, gender-diverse, and non-binary adults associated with autonomic imbalance?
Bibliographic record
Abstract
Blood pressure is a key indicator of cardiovascular health with chronically high levels increasing the risk of cardiovascular diseases (CVD) such as heart attack and stroke. Emerging evidence shows that transgender, gender-diverse, and non-binary (TGD) adults tend to have higher blood pressure than age-matched cisgender adults, corresponding to an increased CVD risk in this population. Yet, the mechanisms underlying elevated blood pressure in TGD adults remain unclear, posing challenges to TGD-affirming healthcare. Given the autonomic nervous system's role in CVD - wherein reduced parasympathetic and heightened sympathetic activity are key risk factors for CVD - this review explores the question: "Is cardiovascular disease risk in TGD adults associated with autonomic imbalance?" Limited research exists on autonomic balance within TGD populations. Accordingly, this review considers how TGD-specific factors, such as minority stress, lifestyle behaviors, sex and gender, and hormones (i.e., testosterone, estrogen, progesterone), may impact autonomic balance. Finally, this review aims to underscore the critical need for interdisciplinary research to elucidate these mechanisms and advance TGD-inclusive healthcare in the domains of autonomic control of blood pressure and overall 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".