Relationship between right and left ventricular function in candidates for implantable cardioverter defibrillator with low left ventricular ejection fraction
Bibliographic record
Abstract
Abstract Background Indications for the primary prevention of sudden death using an implantable cardioverter defibrillator (ICD) are based predominantly on left ventricular ejection fraction (LVEF). However, right ventricular ejection fraction (RVEF) is also a known prognostic factor in a variety of structural heart diseases that predispose to sudden cardiac death. We sought to investigate the relationship between right and left ventricular parameters (function and volume) measured by cardiovascular magnetic resonance (CMR) among a broad spectrum of patients considered for an ICD. Methods In this retrospective, single tertiary‐care center study, consecutive patients considered for ICD implantation who were referred for LVEF assessment by CMR were included. Right and left ventricular function and volumes were measured. Results In total, 102 patients (age 62±14 years; 23% women) had a mean LVEF of 28±11% and RVEF of 44±12%. The left ventricular and right ventricular end diastolic volume index was 140±42 mL/m2 and 81±27 mL/m2, respectively. Eighty‐six (84%) patients had a LVEF <35%, and 63 (62%) patients had right ventricular systolic dysfunction. Although there was a significant and moderate correlation between LVEF and RVEF (r=0.40, p<0.001), 32 of 86 patients (37%) with LVEF <35% had preserved RVEF, while 9 of 16 patients (56%) with LVEF ≥35% had right ventricular systolic dysfunction (Kappa=0.041). Conclusions Among patients being considered for an ICD, there is a positive but moderate correlation between LVEF and RVEF. A considerable proportion of patients who qualify for an ICD based on low LVEF have preserved RVEF, and vice versa.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".