1346: Association of Anthropometric Measures with Serum PSA Level and PSA Level Increase
Bibliographic record
Abstract
METHODS: Total prostate volume was measured with pelvic magnetic resonance imaging in 422 adult men enrolled in The Baltimore Longitudinal Study of Aging, a prospective cohort study composed of community volunteers.Generalized estimating equations regression modeling was performed with robust variance estimates to account for multiple measures over time in the same individuals.Associations of BMI, fasting glucose, and diabetes with prostate enlargement and AUA symptom score were determined with adjustment for age and serum testosterone level.RESULTS: Among 422 participants, 91 (21.6%) had prostate enlargement (defined as total prostate volume ;z: 40 cc) at first visit.Compared to men of normal weight (BMI < 25 kg/m 2 ), the age-adjusted odds ratio (OR) for prostate enlargement for overweight men (BMI 25-29.9kg/m 2 ) was 1.41 (95% Cl, 0.84-2.37),for obese men (BMI 30-34 kg/m 2 ) was 1.27 (95% Cl, 0.68-2.39),and for severely obese men (BMI ;z: 35 kg/m 2 ) was 3.52 (95% Cl, 1.45-8.56)(P-trend = 0.01 ).Men with elevated fasting glucose (>11 0 mg/dL) were more likely to have an enlarged prostate than men with normal fasting glucose (S110 mg/dL) (OR 2.98, 95% Cl 1. 70 to 5.23), as were men with a diagnosis of diabetes (OR 2.25, 95% Cl 1.23 to 4.11 ).CONCLUSIONS: Obesity, elevated fasting plasma glucose, and diabetes are risk factors for benign prostatic hyperplasia.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".