Inflammatory Markers and Outcomes After Lacunar Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We hypothesized that concentrations of interleukin 6 (IL-6), serum amyloid A, tumor necrosis factor-α receptor 1, CD40 ligand, and monocyte chemoattractant protein 1 would predict recurrent ischemic stroke and major vascular events after recent lacunar stroke. METHODS: Levels of Inflammatory Markers in the Treatment of Stroke (LIMITS) was an international, multicenter, prospective ancillary biomarker study nested within the Secondary Prevention of Small Subcortical Strokes (SPS3) study, a Phase III trial in patients with recent lacunar stroke. Crude and Adjusted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (95% CI) for recurrence risks. RESULTS: Among 1244 patients with lacunar stroke (mean age, 63.3±10.8 years), there were 115 major vascular events (stroke, myocardial infarction, and vascular death). The risk of major vascular events increased with elevated concentrations of both tumor necrosis factor-α receptor 1 (adjusted HR per SD, 1.21; 95% CI, 1.05-1.41; P=0.01) and IL-6 (adjusted HR per SD, 1.10; 95% CI, 1.02-1.19; P=0.008). Compared with the bottom quartile (tumor necrosis factor-α receptor 1 <2.24 ng/L), those in the top quartile of tumor necrosis factor-α receptor 1 (>3.63 ng/L) were at twice the risk of major vascular events after adjusting for demographics (partially adjusted HR, 1.98; 95% CI, 1.11-3.52), though the effect attenuated after adjusting for other risk factors and statin use (adjusted HR, 1.68; 95% CI, 0.93-3.04). Serum amyloid A, CD40 ligand, and monocyte chemoattractant protein 1 were not associated with prognosis. CONCLUSIONS: Among recent lacunar stroke patients, IL-6 and TNF receptor concentrations predict risk of recurrent vascular events, and they are associated with the effect of antiplatelet therapies. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00059306.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".