Effect of Angiotensin-Converting Enzyme Inhibitor/Calcium Antagonist Combination Therapy on Renal Function in Hypertensive Patients With Chronic Kidney Disease: Chikushi Anti-Hypertension Trial - Benidipine and Perindopril
Bibliographic record
Abstract
Background: Appropriate blood pressure control suppresses progression of chronic kidney disease (CKD). If an angiotensin-converting enzyme (ACE) inhibitor is ineffective, adding a calcium antagonist is recommended. We compared the long-term effect of two ACE inhibitor/calcium antagonist combinations on renal function in hypertensive patients with CKD. Methods: Patients who failed to achieve the target blood pressure (systolic/diastolic: < 130/80 mm Hg) with perindopril monotherapy were randomized to either combined therapy with perindopril and the L-type calcium antagonist amlodipine (group A) or perindopril and the T/L type calcium antagonist benidipine (group B). The primary endpoint was the change of the estimated glomerular filtration rate (eGFR) after 2 years. Eligible patients had a systolic pressure ? 130 mm Hg and/or diastolic pressure ? 80 mm Hg and CKD (urine protein (+) or higher, eGFR < 60 min/mL/1.73 m 2 ). Results: After excluding 38 patients achieving the target blood pressure with perindopril monotherapy, 121 patients were analyzed (62 in group A and 59 in group B). Blood pressure decreased significantly in both groups, but there was no significant change of the eGFR. However, among patients with diabetes, eGFR unchanged in group B (n = 37, 59.1 ± 15.1 vs. 61.2 ± 27.9, P = 0.273), whereas decreased significantly in group A (n = 31, 57.3 ± 16.0 vs. 53.7 ± 16.7, P = 0.005). Conclusions: In hypertensive patients with diabetic nephropathy, combined therapy with an ACE inhibitor and T/L type calcium antagonist may prevent deterioration of renal function more effectively than an ACE inhibitor/L type calcium antagonist combination. J Clin Med Res. 2018;10(2):117-124 doi: https://doi.org/10.14740/jocmr3253w
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".