Postsurgical Temporary Epicardial Pacing: Electrophysiological Implications of Contemporary Pacing Lead Designs
Bibliographic record
Abstract
Background: Despite advancements in postoperative temporary epicardial pacing leads, sensing malfunction can still happen. Oversensing presents as inappropriate inhibition of pacing (a major concern for pacemaker-dependent patients), whereas undersensing may lead to an extremely rare complication of ventricular fibrillation from R on T. The single-lead and dual-lead configurations have key structural differences related to the size of the bipole electrodes and the spacing between them. We assessed how this affects the sensing function. Methods: Five porcine studies were conducted using open chest and Langendorff models. We used 2 pacing wire configurations and compared the sensed electrograms. We compared a newer single-lead configuration (small, closely spaced electrodes) with a dual-lead (large, widely spaced) configuration. The primary outcome was the amplitude of the R wave. Secondary outcomes were the relative size of the T wave and the effect of sampling frequency and low-pass filtering. Results: < 0.001). The average amplitude of the T wave was closer to the average QRS amplitude with the newer configuration across all settings. The mean T wave to R wave difference ranged from 3.0 to 3.7 mV for the single lead and 1.0 to 21.5 mV for the dual lead configuration. Large, widely spaced electrodes resulted in much larger sensed QRS signals and a safer programming window for sensitivity. Conclusions: The smaller, closely spaced electrodes detect a relatively small QRS and a larger T wave, leading to a narrower safety window and an increased risk of sensing malfunction (Central Illustration). To avert catastrophic consequences, the electrophysiologic implications of new temporary pacing wires must be considered during postoperative care.
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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 | 0.005 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".