Renal Hyperfiltration and the Effect of Intensive vs. Standard Blood Pressure Lowering on Cardiovascular Outcomes
Bibliographic record
Abstract
Background: Using the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial and Systolic Blood Pressure Intervention Trial (SPRINT), we examined whether the effect of intensive versus standard blood pressure (BP) lowering on cardiovascular outcomes varies by the presence of renal hyperfiltration (RHF). Methods: We pooled data on adults in ACCORD and SPRINT without chronic kidney disease (eGFR>60 and urine albumin-to-creatinine ratio <30 mg/g). RHF was defined as an eGFR above the 95th percentile for healthy adults in the National Health and Nutrition Examination Survey. Outcomes of interest were major adverse cardiovascular events (MACE, as defined in the ACCORD primary outcome): a composite of cardiovascular (CV) mortality, acute myocardial infarction (AMI) and stroke. Secondary outcomes were all-cause mortality, CV mortality and CV events. We used fixed effect cox regression. Results: There were 1046 (13%) adults with RHF and 7192 adults with normal filtration. RHF modified the effect of intensive versus standard BP lowering on MACE (p-interaction=0.002) but not all-cause mortality (p-interaction=0.059). For adults with RHF, intensive BP lowering reduced incidence of MACE compared with standard BP lowering (HR: 0.22, 95%-CI: 0.10-0.49). The risk reduction was smaller in adults with normal filtration (HR: 0.84, 95%-CI: 0.67-1.06). Intensive BP lowering was also associated with a larger reduction in the incidence of CV mortality and stroke among adults with RHF (Figure, p-interaction≤0.035) but not AMI or heart failure (p-interaction≥0.41). Separate analyses of ACCORD and SPRINT were similar. Conclusions: RHF modified the effect of intensive versus standard BP lowering on cardiovascular outcomes.Intensive Versus Standard Blood Pressure Lowering and Cardiovascular Outcomes in Adults With and Without Renal Hyperfiltration (Pooled Analysis)
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".