Influence of right ventricular ejection fraction on the occurrence of arrhythmic events in patients with systolic dysfunction
Bibliographic record
Abstract
Left ventricular ejection fraction (LVEF) is the primary risk stratification tool used for therapeutic decision making related to device therapy. However, an influence of right ventricular dysfunction on cardiovascular events is becoming apparent. The incremental prognostic value of right ventricular ejection fraction (RVEF) on future arrhythmic events among those being considered for device therapy has not been well examined. In this study we evaluate the significance of MRI-based measurement of RVEF versus other clinical and MRI-based variables for their ability to predict Sudden Cardiac Death (SCD) or Appropriate ICD therapy. Consecutive patients with cardiomyopathy were evaluated for device candidacy. All patients underwent a standard Late Gadolinium Enhancement (LGE) MRI protocol followed by a blinded core-laboratory based quantification of left ventricle (LV) and right ventricle (RV) volumes, ejection fraction (EF) and total hyperenhancement (HE). Patients were stratified according to the presence or absence of significant RV systolic dysfunction, defined as an RVEF ≤45%. All patients were followed for the occurrence of SCD or appropriate ICD therapy. The secondary outcome was heart failure admission or non-sudden cardiac death. All clinical and MRI-based variables were evaluated for associations with the primary and secondary outcomes with Cox proportional multivariable regression analysis also performed. A total of 318 patients (149 ischemic, 169 non-ischemic) were followed over a median of 467 days. At the end of follow-up 49 patients (15.4%) suffered a primary outcome (10 SCD and 39 appropriate therapies). Baseline clinical characteristics were similar among those with and without the primary outcome with the exception of prior history of ventricular arrhythmia and ischemic etiology (p < 0.05). Following adjustment for etiology, LVEF, LVEDV, and Total HE, those with an RVEF≤45% were more likely to experience the primary outcome (HR 2.2; 95% 1.23 to 3.79, p value = 0.007) and the secondary outcome (HR 2.91; 95% CI 1.68 to 5.06, p value = 0.00015) of interest. Patients with right ventricular dysfunction, defined as RVEF≤45% by cardiac MRI, are at an increased risk of future arrhythmic events. Similarly, these individuals are at an elevated risk of heart failure admission and non-sudden cardiac death.
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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 | 0.005 |
| 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 | 0.001 |
| 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".