Statistical Investigation of Correlation between Cardiovascular Event ad Hypertension
Bibliographic record
Abstract
Cardiovascular disease is one of the most severe health killers in modern life. In this study, the association among the risk of cardiovascular diseases, patients’ blood pressure and treatment was analyzed. This study makes a secondary analysis on the data from the Evidence for Cardiovascular Prevention from Observational Cohorts in Japan (EPOCH-JAPAN) database. Participants have recruited 39705 representative participants with diverse blood pressure. The results show that the treated participants have a higher proportion of diabetes mellitus, dyslipidemia, and history of cardiovascular diseases (P<0.0001), compared with untreated participants. During the 10-year follow-up period, there were 2032 cardiovascular deaths distributed among coronary heart disease(CHD), heart failure, and stroke. The treated participants showed an significantly risk for cardiovascular mortality (Hazard ratios (HR):1.5; 95% confidence intervals (CI):1.36-1.66), CHD (HR:1.53, 95%CI: 1.23-1.9), heart failure (HR:1.39; 95%CI: 1.09-1.76) and stroke (HR:1.48; 95%CI: 1.28-1.72). Especially for the participants under antihypertensive medication, their risk of cardiovascular mortality was 1.5 times higher than that of the untreated participants.
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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 | 0.029 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".