Detrimental Immediate- and Medium-Term Clinical Effects of Right Ventricular Pacing in Patients With Myocardial Fibrosis
Bibliographic record
Abstract
BACKGROUND: Long-term right ventricular (RV) pacing leads to heart failure or a decline in left ventricular (LV) function in up to a fifth of patients. We aimed to establish whether patients with focal fibrosis detected on late gadolinium enhancement cardiovascular magnetic resonance (CMR) have deterioration in LV function after RV pacing. METHODS: We recruited 84 patients with LV ejection fraction ≥40% into 2 observational CMR studies. Patients (n=34) with a dual-chamber device and preserved atrioventricular conduction underwent CMR in 2 asynchronous pacing modes (atrial asynchronous and dual-chamber asynchronous) to compare intrinsic atrioventricular conduction with forced RV pacing. Patients (n=50) with high-grade atrioventricular block underwent CMR before and 6 months after pacemaker implantation to investigate the medium-term effects of RV pacing. RESULTS: =0.012); (3) patients with fibrosis did not experience an improvement in quality of life, biomarkers, or functional class after pacemaker implantation; (4) after 6 months of RV pacing, 10 of 50 (20%) patients developed LV ejection fraction <35% and were eligible for upgrade to cardiac resynchronization according to current guidelines. All 10 patients had fibrosis on their preimplant baseline scan and were identified by >1.1 g of fibrosis with 90% sensitivity and 70% specificity. CONCLUSIONS: Fibrosis detected on CMR is associated with immediate- and medium-term deterioration in LV function following RV pacing and could be used to identify those at risk of heart failure before pacemaker implantation.
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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 | 0.002 |
| 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 | 0.000 |
| 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".