Effects of Implantable Cardioverter-Defibrillator Leads on the Tricuspid Valve and Right Ventricle
Bibliographic record
Abstract
BACKGROUND: There are no randomized data to inform the extent to which transvenous cardiac leads cause tricuspid regurgitation (TR). OBJECTIVES: This study sought to determine the effect of a transvenous implantable cardioverter-defibrillator (TV-ICD) on TR severity, and secondarily, on right ventricular (RV) size and function. METHODS: We evaluated TR severity before and 6 months after implantable cardioverter-defibrillator insertion in a post hoc analysis of adults randomized to receive a transvenous (n = 252) or subcutaneous implantable cardioverter-defibrillator (S-ICD) (n = 251) device. TR and RV size and systolic function were assessed by echocardiographic images analyzed in a core laboratory. RESULTS: At baseline, at least mild TR was present in 30% of individuals. At 6 months, the proportion of participants with any TR in the TV-ICD group was 42% vs 19% in the S-ICD group (P < 0.001). The proportion with moderate or severe TR was 7% in the TV-ICD group vs 2% in the S-ICD group (P = 0.021). At 6 months, the OR of at least 1 grade worsening of TR in the TV-ICD group as compared with the S-ICD group was 7.2 (95% CI: 3.3-15.8; P < 0.001). There were no differences between groups with respect to RV size or systolic function. CONCLUSIONS: Six months following TV-ICD insertion, there was a 7-fold increase in the risk of at least 1 grade worsening of TR, with 7% of individuals having TR that was moderate or severe. There was no detectable difference in RV size or function; however, longer follow-up is needed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".