Assessment of heart-evoked potentials in hypertensive patients
Bibliographic record
Abstract
In recent years, interoception, described as the ability to perceive signals from internal organs, has been actively studied. However, the relationship between cardiovascular diseases and neurophysiological characteristics of interoception remains poorly understood. Aim. In this work, we studied neurophysiological markers of interoception in a group of patients with hypertension. Heart-evoked potentials (HEPs) were used as neurophysiological markers. Material and methods . The study included 41 patients with HTN (2250 years old, 80,5% received antihypertensive therapy) and 41 people from the control group (26-50 years old), matched for sex and age. Interoception was studied at the behavioral level by heartbeat tracking task (HTT) and at the neuronal level by the electroencephalography method to record HEPs. Participants filled out the Toronto Alexithymia Scale questionnaire. Results. No significant differences in the accuracy of heartbeat sensations and HEP amplitudes were found between the HTN and control group, as well as significant relationships between accuracy of heartbeat sensations and HEP amplitudes in both groups. Significant positive correlations were found between the HEP amplitudes and the alexithymia indices in both groups. Conclusion . No differences in HEP amplitudes were found between the patients with hypertension and the control group. However, for the first time, a relationship was demonstrated between difficulties in recognizing emotions and HEP amplitudes in hypertensive patients, confirming the hypothesis about the interaction of these processes at insular cortex level.
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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 | 0.001 |
| 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".