Altered Autonomic Cardiac Control Predicts Restenosis After Percutaneous Coronary Intervention
Bibliographic record
Abstract
BACKGROUND: Early and late restenosis in up to 30% remains a major problem for long-term success after percutaneous coronary intervention (PCI). Compared to bare metal stents, the use of drug-eluting stents reduces restenosis below 10%, but implant coasts have to be considered. In restenosis noninvasive testing lacks diagnostic power. We applied a new approach to identify patients with a high risk for restenosis after PCI by combining heart rate (HR) and blood pressure variability (BPV) analyses. METHODS: In 52 patients with clinical suspicion of restenosis and history of PCI, we investigated patterns of cardiovagal autonomic regulation prior to cardiac catheterization. The patients were separated in (i) patients with restenosis (CAD+R) and (ii) patients without restenosis (CAD-R), where restenosis is defined as a stenosis greater than 75% of luminal diameter in at least one main vessel. The following parameters/methods were evaluated: Canadian Cardiovascular Society grade (CCS-grade), vessel disease score (CAD-level), left ventricular ejection fraction (LVEF), heart rate variability (HRV), BPV, baroreflex sensitivity (BRS), as well as HR turbulence and blood pressure (BP) potentiation caused by premature ventricular complexes. RESULTS: Whereas age, LVEF, CAD-level, CCS-grade, and mean BP did not differ between CAD+R and CAD-R, significant differences were found in (i) BPV: diastolic LF/P, systolic, and diastolic UVLF, (ii) in BRS: slope of tachycardic sequences, and (iii) in extrasystolic parameters: heart rate turbulence onset (HRTO) and potentiation of systolic BP (SBPP). Standard HRV parameters did not show significant differences between the groups. Using the two parameters diastolic LF/P (threshold >0.2) and HRTO (threshold >0) restenosis were predicted in 83.4%. CONCLUSIONS: These results demonstrate that indicators of sympathetic activation or vagal depression identify restenosis in patients after PCI, thus opening a perspective for a new noninvasive monitoring.
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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) | 0.001 | 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 | 0.000 |
| 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".