Cerebral White Matter Hyperintensities, Kidney Function Decline, and Recurrent Stroke After Intensive Blood Pressure Lowering: Results From the Secondary Prevention of Small Subcortical Strokes (SPS3) Trial
Bibliographic record
Abstract
Background We aimed to determine whether cerebral white matter hyperintensities ( WMHs ) can distinguish stroke survivors susceptible to rapid kidney function decline from intensive blood pressure ( BP ) lowering. Methods and Results The SPS3 (Secondary Prevention of Small Subcortical Strokes) trial randomized participants with recent lacunar stroke to systolic BP targets of 130 to 149 and <130 mm Hg. We included 2454 participants with WMH measured by clinical magnetic resonance imaging at baseline and serum creatinine measured during follow-up. We tested interactions between BP target and WMH burden on the incidence of rapid kidney function decline (≥30% decrease from baseline estimated glomerular filtration rate at 1-year follow-up) and recurrent stroke. Rapid kidney function decline incidence was 11.0% in the lower- BP -target arm and 8.1% in the higher-target arm (odds ratio=1.40; 95% CI=1.07-1.84). Odds ratio for rapid kidney function decline between lower- and higher-target groups ranged from 1.26 in the lowest WMH tertile (95% CI , 0.80-1.98) to 1.71 in the highest tertile (95% CI , 1.05-2.80; P for interaction=0.65). Overall incidence of recurrent stroke was 7.9% in the lower-target arm and 9.6% in the higher-target arm (hazard ratio=0.80; 95% CI , 0.63-1.03). Hazard ratio for recurrent stroke in the lower-target group was 1.13 (95% CI , 0.73-1.75) within the lowest WMH tertile compared with 0.73 (95% CI , 0.49-1.09) within the highest WMH tertile ( P for interaction=0.04). Conclusions Participants with higher WMH burden appeared to experience greater benefit from intensive BP lowering in prevention of recurrent stroke. By contrast, intensive BP lowering increased the odds of kidney function decline, but WMH burden did not significantly distinguish this risk. Clinical Trial Registration URL : http://www.clinicaltrials.gov . Unique identifier: NCT 00059306.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".