Specific patterns of premature beats tend to initiate ventricular tachyarrhythmias in human patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction. Previously, we demonstrated that certain patterns of abnormal rapid beats, notably “short-long-short-short” (SLSS) patterns, tend to produce action potential block in computer models, and tend to initiate VF in in vivo canine experiments, consistent with our theory based on electrical restitution. Here we present evidence that these same patterns often precede VF in human ECG recordings. Methods. Thirty-four ECG recordings from just prior to and during tachyarrhythmic events were obtained from ICDs implanted in several human patients. The distributions of the first four abnormal RR intervals prior to arrhythmia onset were fit to single-gaussian and dual-gaussian distributions. Results. Dual-gaussian distributions were obtained for the second and third abnormal beats, while single gaussian distributions were obtained for the first and fourth. These distributions are consistent with the tendency of the SLSS pattern of premature beats, as well as SLLS and SSSS patterns, to precede the tachyarrhythmic event, as described by our computer model. Conclusions. The results provide further evidence that electrical restitution theory, the basis for both our theory and computer model, although imperfect, is sufficient to both predict and understand the manner in which premature beats initiate VF. This understanding may, in the future, lead to new methods for preventing VF, through the imposition of stimuli designed to avoid the dangerous premature beat patterns described in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it