Intraoperative Study of Polarization and Evoked Response Signals in Different Endocardial Electrode Designs
Bibliographic record
Abstract
Some new generation pacemakers use an algorithm based on evoked response (ER) detection to verify beat-to-beat capture and to enable automatic adjustment of output. This is a prospective acute study of polarization signal (PS) and ER in nine currently available electrodes. Intraoperative testing of ventricular bipolar electrodes used the Autocapture (AC) algorithm. The intrinsic R wave, PS, ER, acceptance of AC function, and stimulation thresholds (STs) were obtained. Ventricular electrodes were categorized as follows: titanium nitride (TiN)-coated passive and active fixation, high impedance (HI), passive fixation (VP), iridium oxide-coated titanium (IROX) (VI), and platinum helix (PH) active fixation. Acute testing was performed in 217 patients with an average age of 74.26 years, 59.6% were men with primary pacing indication-SSS (46.3%). There were no significant differences found with respect to R wave and threshold between the various electrodes. PH active-fixation electrodes had significantly higher ER and PS than other groups including the TiN-coated active-fixation electrodes. TiN-coated electrodes (active and passive fixation) had significantly lower PS than other electrodes. As a result, TiN electrodes had a significantly higher functional rate of AC (91.7%), whereas PH had the lowest rate (0%). In conclusion, (1) polarization characteristics are significantly different for commercially available ventricular electrodes, (2) certain physical features at the tissue to electrode interface like TiN coating appears to be more important in determining PS than electrode tip size and fixation method, and (3) the current algorithm for AC requires electrodes that provide low polarization for satisfactory performance.
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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 | 0.003 |
| 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 | 0.000 |
| 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".