Physiological Phenotyping for Personalized Therapy of Uncontrolled Hypertension in Africa
Bibliographic record
Abstract
OBJECTIVES: African and African American hypertensives tend to retain salt and water, with lower levels of plasma renin and more resistant hypertension. We tested the hypothesis that physiological phenotyping with plasma renin and aldosterone would improve blood pressure control in uncontrolled hypertensives in Africa. METHODS: Patients at hypertension clinics in Nigeria, Kenya, and South Africa with a systolic blood pressure >140 mm Hg or diastolic pressure > 90 mm Hg despite treatment were allocated to usual care (UC) vs. physiologically individualized care (PhysRx). Plasma renin activity and aldosterone were measured using ELISA kits. Patients were followed for 1 year; the primary outcome was the percentage of patients achieving blood pressure <140 mm Hg and diastolic <90 mm Hg. RESULTS: Results are presented for the 94/105 participants who completed the study (42 UC, 52 PhysRx). Control of both systolic and diastolic pressures was obtained in 11.1% of UC vs. 50.0% of PhysRx (P = 0.0001). Systolic control was achieved in 13.9% of UC vs. 60.3% of PhysRx (P = 0.0001); diastolic control in 36.1% of UC vs. 67.2% of PhysRx, vs. (P = 0.003). Number of visits and total number of medications were not significantly different between treatment groups, but there were differences across the sites. There were important differences in prescription of amiloride as specified in the PhysRx algorithm. CONCLUSIONS: Physiologically individualized therapy based on renin/aldosterone phenotyping significantly improved blood pressure control in a sample of African patients with uncontrolled hypertension. This approach should be tested in African American and other patients with resistant hypertension. Registered as ISRCTN69440037.
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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 | 0.003 |
| 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 | 0.000 |
| 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".