Left ventricular isovolumic relaxation is a predictor of left ventricular end-diastolic pressure.
Bibliographic record
Abstract
BACKGROUND: The relationship between isovolumic left ventricular (LV) relaxation and LV filling pressures remains incompletely explored. If there is a relationship between the rate of early diastolic LV relaxation and LV end-diastolic pressure, this would have important implications concerning both our understanding and, potentially, our treatment of LV diastolic dysfunction. OBJECTIVE: To examine the baseline hemodynamic correlates of LV end-diastolic pressure in patients with both normal and abnormal LV function. METHODS: The relationships between LV end-diastolic pressure, a variety of hemodynamic parameters (tau, the rate of LV isovolumic relaxation, LV peak positive+dP/dt, LV peak systolic pressure and heart rate), measures of LV end-systolic and end-diastolic volume, and age were determined using regression analysis techniques in 104 patients with normal LV systolic function and 90 patients with an LV ejection fraction of less than 40%. RESULTS: Univariate analysis demonstrated a correlation between tau and LV end-diastolic pressure (r=0.743, P<0.001). There were significant univariate relationships between a number of other hemodynamic variables and LV end-diastolic pressure. A multiple regression model demonstrated that tau made the most important contribution to a model where LV end-diastolic pressure is the dependent variable. LV peak systolic pressure and heart rate also made significant contributions to the model. In 33 of these patients, when LV end-diastolic pressure was reduced using an inferior vena cava occlusion balloon, tau did not change. The acute administration of clonidine (n=11) caused an increase in LV end-diastolic pressure that was closely correlated with an observed increase in tau (r=0.843, P<0.001). CONCLUSIONS: These observations suggest that the rate of LV isovolumic relaxation is a predictor of LV end-diastolic pressure.
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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 | 0.000 | 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 | 0.001 |
| 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".