Baseline tissue Doppler imaging-derived echocardiographic parameters and left ventricle reverse remodelling following cardiac resynchronization therapy introduction
Bibliographic record
Abstract
INTRODUCTION: The aim of the study was to assess the relation of baseline mechanical dyssynchrony with the left ventricular end-systolic volume (LVESV) decrease following cardiac resynchronization (CRT) therapy introduction. MATERIAL AND METHODS: Sixty consecutive patients (aged 66.3 ± 8.7 years; 57 men) with chronic heart failure (71.7% of ischaemic and 28.3% of non-ischaemic origin) and current indications for CRT were assessed before and 3 months after biventricular heart stimulator implantation. Longitudinal movements of twelve segments of the left ventricle (LV) (6 basal and 6 midlevel) and two segments of the right ventricle (RV) were analysed using tissue Doppler imaging (TDI) techniques with time from onset of Q wave in ECG to peak systolic velocity in colour-coded TDI (T(TDI)), time to peak strain (T(strain)) and time to peak strain rate (T(strain) (rate)). Minimal and maximal time differences within LV and between LV and RV walls were calculated. RESULTS: In the study group LVEF and 6-min walk test distance increased, while NYHA class, NT-proBNP level, left ventricular end-diastolic volume and LVESV decreased. Significant correlations between the magnitude of LVESV reduction with maximal time differences between T(strain) of 12 LV segments (r=0.34, p = 0.017) and time differences between T(TDI) basal LV-RV segments (r = -0.29, p=0.041) were found. CONCLUSIONS: Only a few TDI-derived parameters such as maximal time differences between T(strain) of 12 LV segments and T(TDI) difference of LV-RV basal segments can be useful to predict the magnitude of left ventricle reverse remodelling after CRT introduction.
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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 | 0.000 | 0.001 |
| 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".