511 MYOCARDIAL PERFUSION PRESSURE IN PATIENTS WITH HYPERTENSION AND CORONARY ARTERY DISEASE
Bibliographic record
Abstract
Background: Establishing target blood pressure (BP) in persons with hypertension (HTN) and coronary artery disease (CAD) is an ongoing challenge for clinical practice guidelines. There is concern about a limit to BP reduction in CAD but there is little data from direct measurements of myocardial perfusion pressure. Methods: BP in coronary arteries proximal and distal to coronary artery stenosis was measured in 40 patients with HTN at coronary angiography. Fractional flow reserve (FFR) across stenotic coronary arteries was measured during maximal hyperemia, achieved by adenosine. FFR is measured when the degree of stenosis is not obviously critical by angiographic criteria. The most severe coronary lesion for each person was selected. Results: FFR was 0.82 + 0.09 (mean + SD) with a range from 0.53 to 0.96 and with 42.9% having a significant stenosis of < 0.8. Myocardial perfusion pressure (MPP), diastolic BP distal to coronary stenosis during maximal hyperemia, was 58.1 + 12.7 mmHg with 31% of MPP below 50mmHg. Using these FFR values, DBP of 80, 70 and 65 mmHg would have respectively 2.4%, 14.3% and 28.6% of patients with a MMP of < 50 mmHg - a range in which estimated coronary blood flow approximates zero Conclusion: Clinical practice guidelines for patients with HTN and CAD confront the challenge of not knowing the degree of coronary stenosis and the hazard of setting a target that might induce myocardial ischemia. Based on our population, a diastolic BP target of 80mmHg is safe while diastolic BP of < 70mmHg may produce unacceptably low myocardial perfusion pressures.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".