Similarity of spontaneous and induced heart rate and blood pressure turbulence.
Bibliographic record
Abstract
BACKGROUND: Heart rate turbulence (HRT) is a transient tachycardia-bradycardia that follows premature ventricular complexes (PVCs). The physiology of turbulence is studied in the electrophysiology lab using induced premature ventricular stimuli but the reliability of this model for HRT is unknown. OBJECTIVES: To compare heart rate and blood pressure signatures of induced and spontaneous HRT. METHODS: Each patient received 10 ventricular extrastimuli at 1-min intervals. Electrocardiogram and continuous blood pressure results were digitized for 34 electrophysiology patients. RESULTS: Fifteen patients yielded at least one induced and one spontaneous analyzable PVC. Per subject, 3.6+/-2.2 spontaneous and 6.1+/-3.3 induced HRT sequences were detected. Spontaneous and inducible HRT were indistinguishable according to turbulence onset (median -1.7% versus -2.3%, P=0.09), turbulence slope (median 7.1 ms/beat versus 10.0 ms/beat, P=0.73), turbulence tachycardia (median 29 ms versus 22 ms, P=0.97) and turbulence bradycardia (45 ms versus 72 ms, P=0.60). Accompanying blood pressure signatures were indistinguishable according to initial hypotension (-0.5+/-5.9 mmHg versus 12.1+/-5.5 mmHg, P=0.19), hypertension time (7.7+/-3.6 s versus 7.8+/-1.9 s, P=0.93) and turbulence hypertension (13.5+/-5.7 mmHg versus 16.1+/-9.2 mmHg, P=0.19). Baroreflex sensitivities estimated by the spontaneous sequence method were similar for spontaneous and induced turbulence (median 7.5 ms/mmHg versus 7.2 ms/mmHg, P=0.89) and correlated with each other (r2=0.81). Heart rate and blood pressure turbulence induced in the electrophysiology laboratory were similar to those following spontaneous PVCs and induced turbulence was a valid model for study under controlled conditions.
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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 | 0.000 | 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 | 0.000 |
| 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".