Expanding role for single‐pill combination drug therapy in the initial treatment of hypertension?
Bibliographic record
Abstract
hypertension, single-pill combination, statin, treatment Arterial hypertension is a major health concern worldwide.1 High arterial blood pressure (BP) is the leading modifiable risk factor for cardiovascular disease (CVD), contributing to the greatest global burden of disease. 2 If the presence of hypertension can be correctly diagnosed, the risk of future cardiovascular complications and events can be markedly suppressed with BP-lowering medications and dietary and lifestyle interventions.[2][3][4] However, despite the increased awareness of the importance of maintaining healthy BP values and the availability of multiple intervention options and therapies, a high percentage of hypertensive individuals fail to control their high BP and thus prevent the development of CVD.One of the major reasons for this failure is that there are major deficiencies with respect to the awareness and diagnosis of high BP, the available BP-lowering treatments, and drug adherence; moreover, these problems persist across low-, middle-, and high-income countries, emphasizing the need for widespread population-level improvement in the understanding of hypertension.5 Over the last decade, BP control rates have plateaued worldwide at low levels.It was reported that the rates of BP control are 17-31% in hypertensive patients in high-income countries, and the con-
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".