Point process heartbeat dynamics assessment of neurocardiogenic syncope in children
Bibliographic record
Abstract
The underlying mechanisms that lead to syncope are still unclear, especially in children. In this work, we applied a novel point-process model to study timevarying heartbeat dynamics and to characterize autonomic changes that occur prior to a syncopal event. Twentysix children with history compatible with neurocardiogenic syncope (NCS) and a positive head up tilt table test (HUT) were included in the study. ECG and blood pressure signals were recorded during rest and the diagnostic HUT. Using self-developed software, a decrease of > 30% of the median systolic blood pressure during HUT compared to rest was selected as the onset of the syncopal event. After ECG peak detection and correction of ectopic beats, we modeled the time between R-wave events as a history dependent inverse Gaussian (IG) and applied the pointprocess framework to compute several measures related with HRV. We tested for significant changes in these measures for three consecutive two-minute time intervals previous to the syncopal event. Of all measures, only the mean of the heart rate probability density function, μHR, and the scale parameter of the IG probability density function, ζ<inf>0</inf>(t), presented a statistically significant increase prior to syncope, providing novel features associated with the statistical properties of heartbeat generation that could be critical to predict and explain the occurrence of syncope.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".