A patient‐specific approach to assessing blood pressure management in patients with hypertension and coronary artery disease
Bibliographic record
Abstract
The objective was to improve the management of patients with hypertension (HTN) and coronary artery disease (CAD), utilizing a model which integrates 3 determinants of coronary blood flow (CBF)-CAD severity, diastolic blood pressure (DBP), and left ventricular (LV) mass. We validated non-parametric equations for CBF estimation in a consecutive patient sample (N = 81) with HTN and CAD. There was a highly significant correlation (r = .565; P < .01) between clinical DBP and estimated CBF. Greater LV mass and more severe CAD shifted the relationship towards less CBF at the same DBP. LV mass was more critical when DBP >70 mm Hg. Estimated changes in CBF at different DBP considering the severity of CAD and LV mass can be calculated. In summary, the severity of CAD from coronary CT or coronary angiography combined with LV mass from echocardiography permits clinicians to guide the extent of, or target for, DBP to avoid seriously compromising CBF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".