11 Left ventricular end diastolic filling pressure predicted by left atrial strain measured by feature tracking
Bibliographic record
Abstract
Introduction Left ventricular end-diastolic filling pressure (LVEDP) is an invasive measure of LV function obtained at cardiac catheterisation (CC) that predicts prognosis and guides therapeutic strategy. Echocardiographic E/E’ ratio has been shown to be inaccurate for estimation of LVEDP. Feature-tracking cardiovascular magnetic resonance (FT-CMR) is a novel method for quantification of myocardial deformation and can be used to quantitatively assess left atrial (LA) function. Currently there is no validated MRI parameter that estimates LVEDP. We hypothesised that LA strain correlates to LVEDP. Methods 14 patients in sinus rhythm, with severe AS underwent a 1.5T CMR protocol (Ingenia, Phillips Healthcare, Best, The Netherlands). LVEDP was recorded at the time of CC by standard techniques. 4 chamber and mid ventricular short axis steady state free procession cine images were obtained: LA endocardial and epicardial borders were traced manually on the end-diastolic slice and strain measurements were calculated using commercially available post-processing software (CVI42, Circle Cardiovascular Imaging, Calgary, Alberta, Canada). Results Patients were divided into 2 groups: low EDP (13 ± 2.4mmHg) and high EDP (36.1 ± 3.4mmHg) (p < 0.01). Both groups were evenly matched for baseline demographics (Table 1). Peak atrial longitudinal strain (PALS) was significantly different between low EDP and high EDP group (−21.7 ± 8.5 versus −11.1 ± 2.1% p = 0.01) (Figure 1). In multivariable analysis of demographics and CMR parameters PALS was the only determinant of LVEDP independent of other factors (Beta −0.93 p = 0.01). There was a moderate negative correlation between increasing invasive LVEDP and PALS (Pearson’s correlation coefficient −0.647, p = 0.009). Conclusion LA function (PALS) as measured by FT-CMR is independently associated with LVEDP and may have a role in predicting LV filling pressures via a routine CMR protocol.
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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) | 0.004 | 0.001 |
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".