Optimal use of β-blockers in high-risk hypertension: A guide to dosing equivalence
Why this work is in the frame
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Bibliographic record
Abstract
Optimal use of β-blockers in high-risk hypertension: A guide to dosing equivalence Janet B McGillDepartment of Medicine, Washington University School of Medicine, St. Louis, Missouri, USAAbstract: Hypertension is the number one diagnosis made by primary care physicians, placing them in a unique position to prescribe the antihypertensive agent best suited to the individual patient. In individuals with diabetes mellitus, blood pressure (BP) levels > 130/80 mmHg confer an even higher risk for cardiovascular and renal disease, and these patients will benefit from aggressive antihypertensive treatment using a combination of agents. β‑blockers are playing an increasingly important role in the management of hypertension in high-risk patients. β‑blockers are a heterogeneous class of agents, and this review presents the differences between β‑blockers and provides evidence-based protocols to assist in understanding dose equivalence in the selection of an optimal regimen in patients with complex needs. The clinical benefits provided by β‑blockers are only effective if patients adhere to medication treatment long term. β‑blockers with proven efficacy, once-daily dosing, and lower side effect profiles may become instrumental in the treatment of hypertensive diabetic and nondiabetic patients.Keywords: antihypertensive, blood pressure, atenolol, carvedilol, labetalol, metoprolol, nebivolol
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it