Non-Invasive Determination of Left Ventricular Workload in Patients with Aortic Stenosis Using Magnetic Resonance Imaging and Doppler Echocardiography
Bibliographic record
Abstract
Early detection and accurate estimation of aortic stenosis (AS) severity are the most important predictors of successful long-term outcomes in patients. Current clinical parameters used for evaluation of the AS severity have several limitations including flow dependency. Estimation of AS severity is specifically challenging in patients with low-flow and low transvalvular pressure gradient conditions. A proper diagnosis in these patients needs a comprehensive evaluation of the left ventricle (LV) hemodynamic loads. This study has two objectives: (1) developing a lumped-parameter model to describe the ventricular-valvular-arterial interaction and to estimate the LV stroke work (SW); (2) introducing and validating a new index, the normalized stroke work (N-SW), to assess the global hemodynamic load imposed on the LV. N-SW represents the global hemodynamic load that the LV faces for each unit volume of blood ejected. The model uses a limited number of parameters which all can be measured non-invasively using current clinical imaging modalities. The model was first validated by comparing its calculated flow waveforms with the ones measured using Cardiovascular Magnetic Resonance (CMR) in 49 patients and 8 controls. A very good correlation and concordance were found throughout the cycle (median root mean square: 12.21 mL/s) and between the peak values (r = 0.98; SEE = 0.001, p<0.001). The model was then used to determine SW using the parameters measured with transthoracic Doppler-echocardiography (TTE) and CMR. N-SW showed very good correlations with a previously-validated index of global hemodynamic load, the valvular arterial impedance ([Formula: see text]), using data from both imaging modalities (TTE: r = 0.82, SEE = 0.01, p<0.001; CMR: r = 0.74, SEE = 0.01, p<0.001). Furthermore, unlike , N-SW was almost independent from variations in the flow rate. This study suggests that considering N-SW may provide incremental diagnostic and prognostic information, beyond what standard indices of stenosis severity and provide, particularly in patients with low LV outflow.
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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 | 0.000 |
| 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) | 0.000 | 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".