Clinical Significance of Low Blood Testosterone Concentration in Men as a Cardiovascular Risk Factor From the Perspective of Blood Rheology
Bibliographic record
Abstract
BACKGROUND: Recent clinical studies have indicated the importance of low blood testosterone concentration or whole blood passage time (WBPT) which reflects blood rheology as a cardiovascular risk factor. On the contrary, there are no reports regarding the association of blood testosterone concentrations and WBPT. This cross-sectional study aimed to elucidate the clinical significance of low blood testosterone concentration in men as a cardiovascular risk factor from the perspective of blood rheology using WBPT. METHODS: , and WBPT was also measured using microchannel array flow analyzer as a commercial device. The relationship between T-T and WBPT was evaluated. RESULTS: There was a significantly negative correlation between T-T and WBPT (r = -0.45; P < 0.001). Furthermore, multiple regression analysis revealed that T-T (β = -0.25; P < 0.001) could be selected as an independent variable when WBPT was used as a subordinate factor. According to receiver operating characteristic curve analysis and the result of the previous report that determined WBPT of > 72.4 s as a risk for incidence of primary cardiovascular disease, T-T of < 551.4 ng/dL is the optimal cut-off point for discriminating high WBPT. CONCLUSIONS: The study results showed that T-T is independently and inversely associated with WBPT in male patients with traditional cardiovascular risk factor and no history of cardiovascular disease. In addition, this study suggests that the incidence of primary cardiovascular events can be prevented by maintaining T-T at approximately ≥ 550 ng/dL from the perspective of blood rheology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".