Non-invasive assessment of ventricular force–frequency relations in the univentricular circulation by tissue Doppler echocardiography: a novel method of assessing myocardial performance in congenital heart disease
Bibliographic record
Abstract
OBJECTIVE: To describe the first clinical application of a novel tissue Doppler derived index of contractility, isovolumic acceleration (IVA), in the assessment of the ventricular myocardial force-frequency relation (FFR) in the univentricular heart (UVH). DESIGN: Prospective study. SETTING: Tertiary referral centre. INTERVENTIONS: Non-invasive assessment of the myocardial FFR by tissue Doppler echocardiography during atrial pacing. RESULTS: IVA was used to measure the FFR of the systemic ventricle in patients with structurally normal hearts and in patients with UVHs. Basal IVA of the normal hearts (mean (SD) 1.9 (0.3) m/s2) was significantly greater than that of UVHs in patients with a dominant right ventricle (RV) (1.0 (0.3) m/s2) or left ventricle (LV) (0.8 (0.7) m/s2; p < 0.05 for both). Neither the absolute nor percentage change from basal to peak values of IVA with pacing differed between the three groups. Peak force developed by the normal LV was significantly greater than that of the UVH, dominant LV group but not different from that of the UVH, dominant RV group. CONCLUSION: Contractility at basal heart rate is depressed in patients with UVH compared with the normal LV. Analysis of ventricular FFRs exposes further differences in myocardial contractility. There is no evidence that contractile function of the dominant RV is inferior to that of the dominant LV over a physiological range of heart rates.
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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 | 0.002 |
| 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".