Noninvasive Assessment of Left Ventricular Force-Frequency Relationships Using Tissue Doppler–Derived Isovolumic Acceleration
Bibliographic record
Abstract
BACKGROUND: We have demonstrated that myocardial acceleration during isovolumic contraction (IVA) is a sensitive index of right ventricular contractile function. In this study, we assessed the usefulness of IVA to measure left ventricular (LV) contractile function and force-frequency relationships in an experimental preparation. METHODS AND RESULTS: In study 1, we examined 6 pigs by use of tissue Doppler imaging of LV free wall and simultaneous measurements of intraventricular pressure, volume, maximal elastance (Emax), and dP/dtmax by conductance catheterization. Animals were paced via the right atrium at a rate of 130 bpm. IVA was compared with elastance during contractility modulation by esmolol and dobutamine and assessed during preload reduction and afterload increase. In study 2, in 6 more pigs, force-frequency data were obtained during incremental atrial pacing from 120 to 180 bpm. Study 1: Esmolol led to a decrease in IVA and Emax (P<0.03 and <0.02, respectively), both of which increased during dobutamine infusion (P<0.02 and <0.03, respectively). IVA was unaffected by significant (P<0.001) acute reduction of LV volume and a significantly increased LV afterload (systolic pressure increase, P<0.001). Study 2: There was a positive correlation between IVA and dP/dtmax (r2=0.92, P<0.05). As heart rate was increased from 120 to 160 bpm, there were significant increases in both IVA and dP/dtmax (P<0.0004 and P=0.02, respectively). Over the same range of heart rates, there was no significant change in Emax (P=0.22). CONCLUSIONS: IVA is a measurement of LV contractile function that is unaffected by preload and afterload changes within a physiological range and can be used noninvasively to measure LV force-frequency relationships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".