Simplified therapeutic intervention to control hypertension and hypercholesterolemia
Bibliographic record
Abstract
BACKGROUND: Notwithstanding improving rates of hypertension control in North America, management of patients with both hypertension and dyslipidemia remains problematic. Based on evidence of improved control utilizing a simplified algorithm for management of hypertension (STITCH), we questioned whether a simplified comprehensive treatment algorithm featuring initial use of single-pill combinations (SPCs) would improve management of participants with both hypertension and dyslipidemia. METHOD: We randomized 35 primary care practices in Ontario to either Guidelines-care (following current Canadian guidelines) or STITCH2-care (following a treatment algorithm featuring SPCs). Practices each enrolled up to 50 participants with at least one risk factor above target at entry based on Canadian guidelines for BP and LDL-cholesterol control. The primary endpoint was achieving targets for both hypertension and dyslipidemia control after 6 months, assessed at the practice level. RESULTS: The primary endpoint was achieved in 31.3% of participants in STITCH2-care practices, compared with 28.1% in Guidelines-care practices, yielding a difference of 3.2% (P = 0.63). Notably, STITCH2-care practices had a significantly greater reduction in SBP while LDL-cholesterol reduction was only marginally greater in STITCH2 practices. CONCLUSION: The STITCH2 algorithm resulted in significantly greater use of any SPC compared with Guidelines-care and greater use of the SPC of calcium channel blocker/statin. Unwillingness of the prescribing physician to advance treatment beyond a monotherapy threshold was found to be an important determinant for failing to achieve blood pressure control. In contrast, the more important determinant for failing to achieve LDL control appeared to be the unwillingness of the prescribing physician to initiate therapy with a statin.
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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".