Does QTc Interval Predict the Response to β-Blockers and Calcium Channel Blockers in Hypertensives?
Bibliographic record
Abstract
The QT interval corrected for heart rate (QTc) is believed to reflect sympathovagal balance. It has also been established that beta-blockers and dihydropyridine-type calcium channel blockers (DHPCCB) influence the autonomic nervous system. This study tested the hypothesis that QTc interval length is a predictor of the blood pressure reduction induced by beta1-selective beta-blockers or DHPCCB. The predictive values of pretreatment heart rate and of the heart rate change with therapy were also evaluated. The authors conducted an historical reanalysis of 5 clinical trials that looked at the antihypertensive effects of beta-blockers (nebivolol) or DHPCCB (amlodipine, felodipine, isradipine, nifedipine). Correlation and quintile analyses were performed to measure the association between QTc interval, heart rate, or heart rate change and therapeutic blood pressure response. Separate analyses were undertaken for beta-blockers and DHPCCB. Seventy-three and 98 hypertensive subjects respectively were included in the beta-blocker and DHPCCB analyses. QTc interval, pretreatment heart rate, and heart rate change with therapy were not associated with therapeutic blood pressure response. In this study, QTc interval length, pretreatment heart rate, and heart rate change with therapy were not good predictors of the blood pressure response to beta1-selective beta-blockers or DHPCCB in hypertensive subjects.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".