Non-invasive assessment of left ventricular hemodynamic forces in hypertrophic cardiomyopathy
Bibliographic record
Abstract
Abstract Background Hemodynamic force (HDF) analysis allows non-invasive measurement of intraventricular pressure gradients, portraying cyclic spatial-temporal interaction between blood and tissues. Impaired HDFs have been implicated in early detecting of adverse cardiac remodelling and treatment response in various cardiovascular disorders, providing insights into cardiac physiology not offered by traditional cardiovascular imaging (1). Mainly explored in heart failure, HDF analysis has not been previously applied to hypertrophic cardiomyopathy (HCM). Purpose To investigate differences in systo-diastolic function in HCM patients compared to healthy controls using HDF analysis. Methods Forty patients with HCM diagnosis (20 obstructive and 20 non-obstructive) were retrospectively evaluated in comparison with 22 healthy controls. Left ventricular (LV) HDFs were derived from routine transthoracic apical 4-, 2- and 3-chamber views using a dedicated software. Apical-basal HDF curves were generated, where positive deflections represent forces directed from the LV apex to the base, whilst negative ones are directed toward the apex. Amplitude and timing parameters were derived, the latter indexed to total cardiac cycle duration. Results Table 1 shows the demographic, clinical and echocardiographic characteristics of HCM compared to controls. Patients with HCM were older, had a slower heart rate due to treatment with beta-blockers, and showed hypercontractility, as expressed by higher LV ejection fraction. Compared to controls, HCM patients showed reduced LV longitudinal force, i.e. the force during the whole cardiac cycle (4.17% [2.36-5.52] vs. 6.01% [4.73-7.78], p=0.002), shorter time interval to systolic peak (0.15 [0.12-0.16] vs. 0.19 [0.17-0.20], p <0.001), and shorter duration of LV impulse (0.29 [0.27-0.32] vs. 0.34 [0.32-0.37], p <0.001) (Figure 1). However, no differences in terms of systolic force peak (p=0.283) or LV impulse intensity (p=0.689) were detected. During the transition between systole and diastole, LV suction (i.e. the interval including late systolic deceleration and early diastolic suction) was significantly longer (0.26 [0.22-0.29] vs. 0.23 [0.21-0.25], p=0.023) but less pronounced (6.30% [4.56-8.44] vs. 8.72% [6.71-12.59], p=0.005), likely reflecting a relaxation impairment from the very beginning of diastole. Such impairment was maintained during early diastolic filling, where the amplitude of the positive deceleration flow force was severely reduced in HCM compared to controls (2.98% [1.98-4.58] vs. 7.11% [4.55-8.72], p <0.001). Conclusions HDF analysis in HCM patients revealed unique systolic and diastolic changes reflecting faster LV contraction during systole and slower and weaker LV forces during diastole. This analysis deepens our understanding of HCM mechanic abnormalities and may help assess response to innovative treatment options.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".