Abstract 67: HsCRP Predicts Recurrent Stroke and Vascular Events among Patients with Lacunar Stroke: The Levels of Inflammatory Markers in the Treatment of Stroke (LIMITS) Study
Bibliographic record
Abstract
Objective: To determine whether high sensitivity C-reactive protein (hsCRP) predicts recurrent stroke and other vascular events among recent lacunar stroke patients. Background: Inflammatory markers have been associated with risk of first stroke. Their role in predicting recurrence is unclear. Methods: The Levels of Inflammatory Markers in the Treatment of Stroke study is an international prospective study of inflammatory markers among recent lacunar stroke patients enrolled in the NIH-funded randomized Secondary Prevention of Small Subcortical Strokes trial. Patients had blood samples drawn, saved at -80 degrees C, and run at a central lab for hsCRP using nephelometry. Cox proportional hazard models were used to estimate hazard ratios and 95% confidence intervals (HR, 95% CI) for associations of hsCRP with recurrence risk before and after adjusting for demographics, comorbidities, and statin use. Results: Among 1244 lacunar stroke patients (mean 63.3 ± 10.8 years), median hsCRP was 2.16 mg/L (interquartile range 0.93-4.86), and levels differed by age, sex, smoking, and LDL. Median time between stroke and hsCRP measurement was 60 days, and levels were inversely and weakly correlated with proximity to stroke date (r=-0.06, p=0.039). There were 83 recurrent ischemic strokes (45 lacunes), 16 hemorrhages, and 115 major vascular events (stroke, MI, vascular death). Compared to the bottom quartile, those in the top quartile of hsCRP (>4.86 mg/dl) were at increased risk of recurrent ischemic stroke (unadjusted HR 2.54, 95% CI 1.30-4.96), and the risk persisted after adjusting for age, sex, race, region, hypertension, smoking, prior history of stroke, diabetes, lipid levels, and statin use (adjusted HR 2.28, 95% CI 1.14-4.57). HsCRP was associated with an increased risk of major vascular events (top quartile adjusted HR 1.98, 95% CI 1.11-3.54). Results were similar using clinical thresholds of high risk hsCRP (> 3 mg/dl). There was no interaction of randomized antiplatelet treatment with hsCRP levels for stroke risk. Conclusions: Among recent lacunar stroke patients, elevated hsCRP levels predict increased risk of recurrent strokes and other vascular events. Levels of inflammatory markers did not predict a response to dual antiplatelet treatment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".