Abstract 4660: Death Due to Pacemaker or ICD Device Failure is Rare: Implications for the Management of Recalls
Bibliographic record
Abstract
Knowledge of major adverse clinical events (MACE) associated with ICD and pacemaker (PM) pulse generator (PG) and lead performance may be important for managing patients who have these devices. The aim of our study was to assess MACE in our Multicenter Registry. Participating centers prospectively reported ICD and PM PG and lead failures, and PG replaced for normal battery depletion (NBD). Data included dates of implant and removal, failure signs including the elective replacement indicator (ERI), clinical consequences, and reason for removal. MACE were death, inappropriate shocks (IAS), syncope, heart failure, ischemia, sustained tachyarrhythmias, and replacement of a normally functioning PG or lead due to a manufacturers recall. Since 1998, 6,291 ICD and PM PG and leads were removed from service. Of 5,212 ICD and PM PGs, 4,562 (88%) were removed for NBD, 346 (7%) for a recall, and 304 (5%) for component defects. MACE are shown in the Table . The deaths (n=2) were due to component defects causing an ICD PG to short-circuit and a PM PG to deliver high rate pacing. Thus, of the 304 component defects in our database, 2 resulted in death (0.7%). No deaths were associated with ICD or PM lead failure, but 2 deaths occurred following PM lead extraction. The ERI, signifying NBD, resulted in 48 MACE, primarily syncope (67%). Most MACE are due to replacement of normally functioning recalled devices. However, our experience suggests that death due to ICD and PM PG component or lead failure is rare; this finding may be important for managing patients who have recalled devices. Overall, MACE may be substantially reduced by improving high voltage lead reliability, and by providing physiologic ERIs.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".