Value of mechanical dyssynchrony as assessed by radionuclide ventriculography to predict the cardiac resynchronization therapy response
Bibliographic record
Abstract
AIMS: To assess the value of mechanical dyssynchrony measured by equilibrium radionuclide angiography (ERNA) in predicting long-term outcome in cardiac resynchronization therapy (CRT) patients. METHODS AND RESULTS: We reviewed 146 ERNA studies performed in heart failure patients between 2001 and 2011 at our institution. Long-term follow-up focused on death from any cause or heart transplantation. Phase images were computed using the first harmonic Fourier transform. Intra-ventricular dyssynchrony was calculated as the delay between the earliest and most delayed 20% of the left ventricular (LV) (IntraV-20/80) and inter-ventricular dyssynchrony as the difference between LV- and right ventricular (RV)-mode phase angles (InterV). Eighty-three patients (57%) were implanted with a CRT device after ERNA. Median follow-up was 35 [21-50] months. Twenty-four events were observed during the first 41 months. Median baseline ERNA dyssynchrony values were 28 [3 to 46] degrees for intraV-20/80 and 9 [-6 to 24] degrees for interV. Comparing survival between CRT and non-CRT patients according to dyssynchrony status, log-rank tests showed no difference in survival in patients with no ERNA dyssynchrony (P = 0.34) while a significant difference was observed in ERNA patients with high level of mechanical dyssynchrony (P = 0.004). CONCLUSION: ERNA mechanical dyssynchrony could be of value in CRT patient selection.
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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 | 0.004 |
| 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".