Estimating Atrial Action Potential Duration from Electrograms
Bibliographic record
Abstract
Electrogram analysis is important in clinical and experimental settings. Activation recovery interval (ARI) has been used to measure ventricular action potential duration (APD) but its suitability for the atria has not been addressed. Mapping of atrial repolarization may be especially important during nerve stimulation since large heterogenous APD changes may manifest. This study assessed the utility of estimating APD in the atria using electrograms. A computer model of the atria was used to compute electrograms. Two different atrial waveforms were used, as well as two ventricular. APD was modulated with an acetylcholine- (ACh) dependent potassium channel and varying the spatial ACh distribution. ARI was computed, as well as the area under the repolarization wave (ATa). APD was measured by four methods. Atrial electrograms were also compared to monophasic action potentials recorded from a dog. ARI computed from atrial action potentials was not very precise, with errors ranging over 30 ms. Determining changes in APD induced by changing [ACh] yielded larger errors. Conversely, ventricular action potentials produced ARIs that very closely correlated with APD, and changes in APD . Positive ATa indicated regions of shortened APD, and islands of ACh release were clearly demarcated by ATa polarity. Experimentally, ARI was able to detect changes in APD, but did not measure APD well. The faster rate of ventricular repolarization produces larger currents that are less susceptible to electrotonic coupling effects, improving correlation with APD. ARI most closely correlated with APD measured as a fixed threshold above rest. Atrial APs produce electrograms that can be used to detect changes in APD. This may be improved by decreasing coupling. The ATa is a robust measure for precisely identifying spatial APD heterogeneities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".