Lowering Blood Pressure Reduces Renal Events in Type 2 Diabetes
Bibliographic record
Abstract
BP is an important determinant of kidney disease among patients with diabetes. The recommended thresholds to initiate treatment to lower BP are 130/80 and 125/75 mmHg for people with diabetes and nephropathy, respectively. We sought to determine the effects of lowering BP below these currently recommended thresholds on renal outcomes among 11,140 patients who had type 2 diabetes and participated in the Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation (ADVANCE) study. Patients were randomly assigned to fixed combination perindopril-indapamide or placebo, regardless of their BP at entry. During a mean follow-up of 4.3 yr, active treatment reduced the risk for renal events by 21% (P < 0.0001), which was driven by reduced risks for developing microalbuminuria and macroalbuminuria (both P < 0.003). Effects of active treatment were consistent across subgroups defined by baseline systolic or diastolic BP. Lower systolic BP levels during follow-up, even to <110 mmHg, was associated with progressively lower rates of renal events. In conclusion, BP-lowering treatment with perindopril-indapamide administered routinely to individuals with type 2 diabetes provides important renoprotection, even among those with initial BP <120/70 mmHg. We could not identify a BP threshold below which renal benefit is lost.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".