Androgen receptor-reduced sensitivity is associated with increased mortality and poorer glycaemia in men with type 2 diabetes mellitus: a prospective cohort study
Bibliographic record
Abstract
Introduction Hypogonadism is associated with poorer glycaemic outcomes/increased all-cause and cardiovascular morbidity/mortality in type 2 diabetes mellitus (T2DM). Increasing CAG repeat number within exon-1 of the androgen receptor (AR) gene is associated with increased AR resistance/insulin resistance. Methods We determined in a long-term 14-year follow-up cohort of 423 T2DM Caucasian men, the association between baseline androgen status/CAG repeat number (by PCR then Sequenom sequencing) and metabolic/cardiovascular outcomes. Results Metabolic outcomes : Lower total testosterone was associated with higher BMI (kg/m 2 ) at 14-year-follow-up: regression coefficient −0.30 (95% confidence interval −0.445 to −0.157), P = 0.0001. The range of CAG repeat number was 9-29 repeats. Higher CAG repeat number in exon-1 of the AR gene was associated with higher follow-up HbA1c2016 – each unit increase in CAG repeat-associated with an increment of 0.1% in HbA1C2016 ( P = 0.04), independent of baseline testosterone. Cardiovascular outcomes and mortality : At an average of 14-year-follow-up, 55.8% of hypogonadal men had died vs 36.1% of eugonadal men ( P = 0.001). There was a ‘u’ shaped relation between number of CAG repeats and mortality. Twenty-one CAG repeats were associated with an up to nearly 50% lower mortality rate than <21 CAG repeats and >21 CAG repeats – independent of baseline testosterone level. Conclusion A higher number of CAG repeats at the AR gene associates with higher future HbA1c. There was a ‘u’ shaped relation between CAG repeat number and mortality rate. Determination of CAG repeat number may become part of assessment of androgen status/its consequences for men with T2DM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".