THERAPEUTIC RESISTANCE AS THE KEY DETERMINANT OF POOR BLOOD PRESSURE CONTROL IN HYPERTENSIVE PATIENTS: A STITCH SUBSTUDY: 4B.03
Bibliographic record
Abstract
Objective: Despite impressive improvements in blood pressure control generally, control rates remain significantly lower than those achievable under optimal conditions, i.e., in clinical trials. Further, patients with diabetes and hypertension have control rates less than half of those without diabetes. The determinants of poor blood pressure control in the general population and in those with diabetes are unclear. Therefore we conducted a post hoc exploratory analysis to assess blood pressure control in patients from the STITCH study, a cluster randomized controlled trial of hypertension management strategies. Methods: Data were collected in 45 general practices, which enrolled patients with uncontrolled hypertension at trial entry. Pre test and post test blood pressure measurements were taken approximately 6 months apart. Antihypertensive medication changes throughout this follow-up period were documented. Of the 2104 hypertensive patients that were analyzed in the STITCH study, 320 had a diagnosis of diabetes. Results: Overall, 58% of the study population achieved target blood pressures. Through multivariate modeling it was identified that the addition of an antihypertensive drug was a significant predictor of blood pressure reduction. Notably, there were not significant differences in the intensity of treatment (1.7 vs. 1.9 standard doses), number of antihypertensive medications (1.9 drugs), or prescription of 3 or more drugs (26% vs. 31%), comparing those who did and did not reach target. Patients with diabetes were significantly less likely to reach target than those without diabetes (26% vs. 64%, p < 0.001). Notwithstanding, the antihypertensive therapy prescribed to patients with diabetes was only marginally more intensive than to those without diabetes (2.4 vs. 1.7 standard doses). Conclusions: In a community setting, there appears to be a ceiling on antihypertensive prescription regardless of whether target blood pressure is achieved. This ceiling effect is also apparent in patients with diabetes - patients in whom control rates lag far behind. These data suggest that therapeutic resistance and/or patient resistance to advancing therapy remains a very significant barrier to achieving blood pressure control.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".