Abstract TP163: Metabolic Syndrome, Raised Serum Uric Acid And Poor Leptomeningeal Collateral Status In Patients With Acute Ischemic Strokes
Bibliographic record
Abstract
Introduction: Leptomeningeal collaterals are native (pre-existing) anastomoses that cross-connect a small number of distal-most arterioles within the crowns of the cerebral artery trees. We seek to identify potentially modifiable determinants associated with variability in leptomeningeal collateral status in patients with acute ischemic stroke. Methods: Data is from the Keimyung Stroke Registry, a prospectively collected dataset of patients with acute ischemic stroke from Daegu, South Korea. Patients with M 1 segment middle cerebral artery (MCA) +/- intracranial internal carotid artery (ICA) occlusions on baseline CT-angio from May 2004 to July 2009 were included in the study.Baseline and follow-up imaging was analyzed at the imaging core lab of the Calgary Stroke Program. Two readers blinded to all clinical information assessed leptomeningeal collaterals on baseline CT-angio by consensus using the regional leptomeningeal score (rLMC). Results: Of 206 patients[mean age66.9±11.6 years, median baseline NIHSS 14 (IQR11-20), median stroke symptom onset to CT-angio time 166 minutes (IQR 96-262)], 133 patients (64.6%) had poor collateral status at baseline (rLMC score 11-20). On univariate analyses, patients with poor collateral status at baseline were older, hypertensive, had higher blood glucose values, higher white blood cell count at baseline, higher D-dimer and serum uric acid levels (measured next day morning) and were more likely to have metabolic syndrome as per ATP III criteria. Multivariable modeling identified metabolic syndrome (OR 3.22 95% CI 1.69-6.15, p<0.001), raised serum uric acid (per 1mg/dl OR 1.35 95% CI 1.12-1.62, p<0.01) and age (per year, OR 1.03 95% CI 1-1.05, p=0.03) as independent predictors of poor leptomeningeal collateral status at baseline. Conclusion: Metabolic syndrome and hyperuricemia are modifiable determinants associated with poor leptomeningeal collateral status in patients with acute ischemic stroke. This knowledge could potentially help in focusing research on appropriate therapeutic strategies for modulating function of leptomeningeal collaterals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".