Genetically predicted testosterone and electrocardiographic QT interval duration in Chinese: a Mendelian randomization analysis in the Guangzhou Biobank Cohort Study
Bibliographic record
Abstract
BACKGROUND: QT interval prolongation, a predictor of cardiac arrhythmias, and elevated heart rate are associated with higher risk of cardiovascular mortality. Observationally testosterone is associated with shorter corrected QT interval and slower heart rate; however, the evidence is open to residual confounding and reverse causality. We examined the association of testosterone with electrocardiogram (ECG) parameters using a separate-sample instrumental variable (SSIV) estimator. METHODS: To minimize reverse causality, a genetic score predicting testosterone was developed in 289 young Chinese men from Hong Kong, based on a parsimonious set of single nuclear polymorphisms (rs10046, rs1008805 and rs1256031). Linear regression was used to examine the association of genetically predicted testosterone with QT interval, corrected QT interval [using the Framingham formula (QTf) and Bazett formula (QTb)] and heart rate in 4212 older (50+ years) Chinese men from the Guangzhou Biobank Cohort Study. RESULTS: Predicted testosterone was not associated with QT interval [-0.08 ms per nmol/l testosterone, 95% confidence interval (CI) -0.81 to 0.65], QTf interval (0.40 ms per nmol/l testosterone, 95% CI -0.12 to 0.93) or heart rate (0.26 beats per minute per nmol/l testosterone, 95% CI -0.04 to 0.56), but was associated with longer QTb interval (0.66 ms per nmol/l testosterone, 95% CI 0.02 to 1.31). CONCLUSIONS: Our findings do not corroborate observed protective associations of testosterone with QT interval or heart rate among men, but potentially suggest effects in the other direction. Replication in a larger sample is required.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".