Should Blood Pressure Targets After Lacunar Stroke Vary by Body Size? The SPS3 Trial
Bibliographic record
Abstract
BACKGROUND: It is unknown whether the physiological impact of a given blood pressure (BP) varies by body size. We explored interactions between higher vs. lower systolic BP (SBP) targets and anthropometric measures (body mass index (BMI), body surface area (BSA), height, weight) and recurrent stroke and death in the Secondary Prevention of Small Subcortical Strokes (SPS3) Trial. METHODS: Patients with recent magnetic resonance imaging-proven lacunar infarcts were randomized to 2 BP targets (130-149 mm Hg vs. <130) in a prospective, open-label, blinded end-point design. Time to outcome was evaluated with Cox proportional hazard models and compared between targets. We examined multiplicative interactions between each anthropometric measure and target and mean difference in achieved BP 1 year after randomization between BP groups by quartile. We also computed rates of recurrent stroke and death by quartiles of anthropometrics. RESULTS: Three thousand and twenty patients were followed over a mean of 3.7 (SD 2.0) years. Mean age was 63; 63% were male. Mean height was 167 (SD 11) cm, weight 81 (18) kg, BMI 29 (5.9) kg/m(2), and BSA 1.9 (0.25) m(2). Achieved BP at 1 year was comparable between quartiles for each anthropometric measurement. We found no consistent interactions between BP target and anthropometrics for either outcome, nor were there any significant associations between hazard of stroke or death when assessed by BMI, BSA, height, or weight. CONCLUSIONS: We found no interactions between BP target groups and quartiles of anthropometrics for rates of stroke and death in SPS3. There is no evidence at this time supporting body size-based modifications to current BP targets for secondary prevention after lacunar stroke. CLINICAL TRIALS REGISTRATION: Trial Number NCT00059306.
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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 | 0.006 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".