Transvenous Pacing Leads and Systemic Thromboemboli in Patients With Intracardiac Shunts
Bibliographic record
Abstract
BACKGROUND: The risk of systemic thromboemboli associated with transvenous leads in the presence of an intracardiac shunt is currently unknown. METHODS AND RESULTS: To define this risk, we conducted a multicenter, retrospective cohort study of 202 patients with intracardiac shunts: Sixty-four had transvenous leads (group 1), 56 had epicardial leads (group 2), and 82 had right-to-left shunts but no pacemaker or implantable cardioverter defibrillator leads (group 3). Patient-years were accrued until the occurrence of systemic thromboemboli or study termination. Censoring occurred in the event of complete shunt closure, death, or loss to follow-up. Mean ages for groups 1, 2, and 3 were 33.9+/-18.0, 22.2+/-12.6, and 22.9+/-15.0 years, respectively. Respective oxygen saturations were 91.2+/-9.1%, 88.1+/-8.1%, and 79.7+/-6.7%. During respective median follow-ups of 7.3, 9.3, and 17.0 years, 24 patients had at least 1 systemic thromboembolus: 10 (15.6%), 5 (8.9%), and 9 (11.0%) in groups 1, 2, and 3, respectively. Univariate risk factors were older age (hazard ratio [HR], 1.05; P=0.0001), ongoing phlebotomy (HR, 3.1; P=0.0415), and an transvenous lead (HR, 2.4; P=0.0421). In multivariate, stepwise regression analyses, transvenous leads remained an independent predictor of systemic thromboemboli (HR, 2.6; P=0.0265). In patients with transvenous leads, independent risk factors were older age (HR, 1.05; P=0.0080), atrial fibrillation or flutter (HR, 6.7; P=0.0214), and ongoing phlebotomy (HR, 14.4; P=0.0349). Having had aspirin or warfarin prescribed was not protective. Epicardial leads were, however, associated with higher atrial (P=0.0407) and ventricular (P=0.0270) thresholds and shorter generator longevity (HR, 1.9; P=0.0176). CONCLUSIONS: Transvenous leads incur a >2-fold increased risk of systemic thromboemboli in patients with intracardiac shunts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".