Lipid profile and risk of cardiovascular disease in adult transgender men receiving cross-sex hormone therapy: a systematic review
Bibliographic record
Abstract
CONTEXT: A recent US national survey of the health status of the male transgender population has raised awareness about the little-studied relationship between testosterone hormone therapy in transgender men and cardiovascular outcomes. OBJECTIVE: The aim of this systematic review was to assess the relationship between cross-sex hormone therapy in transgender men and lipid profiles and cardiovascular risk. DATA SOURCES: The PubMed, SciELO, SpringerLink, and EBSCOhost databases were searched up to March 2021 for studies assessing the association between cross-sex hormone therapy and the incidence of outcomes related to cardiovascular disease in transgender men over 18 years of age . DATA EXTRACTION: Data extracted were sorted into clinical data (systolic, diastolic, and mean blood pressure), anthropometric data (body mass index, weight, waist circumference, fat mass, and lean mass), and biochemical data (triglycerides, total cholesterol, low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], very low-density lipoprotein cholesterol [VLDL-C], and the HDL-C to LDL-C ratio). DATA ANALYSIS: Study quality was appraised independently by two reviewers using the Cochrane tools for assessment of methodological quality or risk of bias in nonrandomized studies, and the Newcastle-Ottawa Scale was applied. Of 735 studies identified, 11 were included in the review. Most studies reported no change in cholesterol or triglyceride levels after hormone treatment. A reduction in HDL-C levels was observed in 7 of 11 studies, although this alone cannot be considered a cardiovascular risk factor. Likewise, clinical and anthropometric findings showed no changes predictive of cardiovascular risk. CONCLUSIONS: Although these findings suggest that hormone therapy may lead to a decrease in HDL-C levels and an increase in LDL-C levels, they are insufficient to establish a relationship with cardiovascular disease. Furthermore, no significant effects on metabolic and anthropometric values were found. Further studies with higher quality and longer follow-up periods are needed to establish cardiovascular risk. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number CRD 42020212560.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".