Mitral Annular Dynamics and Left Ventricular Diastole
Bibliographic record
Abstract
BACKGROUND: Though diastolic interrogation of the mitral annulus (MA) using tissue Doppler imaging (TDI) has been quite useful in assessing left ventricular (LV) diastolic function, the relative contribution of the previous cycle MA systolic displacement or velocity components to subsequent LV diastole has not been previously investigated. We therefore sought to determine the association between MA systolic dynamics and LV diastolic function parameters. METHODS: For this retrospective study, only complete echocardiograms having good endocardial border resolution of both left atrial (LA) and LV chambers with M-mode (MAPSE) and tissue Doppler of the lateral MA (MA TDI S') as well as complete Doppler data to perform assessment of LV diastole were included in our analysis. RESULTS: Data from 100 patients (mean age 54 ± 14) showed that both MA systolic displacement and velocity correlate with LV ejection fraction (P < 0.05). Only MA displacement was associated with age and LV mass. Most importantly no correlation was found between MAPSE and LV diastole. However, in sharp contrast MA TDI S' correlated with MA relaxation velocities during both early and late LV diastole. CONCLUSION: Even though MAPSE and MA TDI S' are surrogate measures of LV ejection fraction, only MA TDI S' correlates with diastolic MA velocities as no correlation was identified between MAPSE and measures of LV diastole. Additional studies are now warranted to explore whether a reduced MA TDI S' may affect the symptomatic profile or the overall prognosis of patients with LV diastolic dysfunction.
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 | 0.003 |
| 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".