Faculty Opinions recommendation of Leptomeningeal collaterals are associated with modifiable metabolic risk factors.
Bibliographic record
Abstract
OBJECTIVE: We sought to identify potentially modifiable determinants associated with variability in leptomeningeal collateral status in patients with acute ischemic stroke.METHODS: Data are from the Keimyung Stroke Registry. Consecutive patients with M1 segment middle cerebral artery ± intracranial internal carotid artery occlusions on baseline computed tomographic angiography (CTA) from May 2004 to July 2009 were included. Baseline and follow-up imaging was analyzed blinded to all clinical information. Two raters assessed leptomeningeal collaterals on baseline CTA by consensus, using a previously validated regional leptomeningeal score (rLMC).RESULTS: Baseline characteristics (N = 206) were: mean age = 66.9 ± 11.6 years, median baseline National Institutes of Health Stroke Scale = 14 (interquartile range [IQR] = 11-20), and median time from stroke symptom onset to CTA = 166 minutes (IQR = 96-262). Poor collateral status at baseline (rLMC score = 0-10) was seen in 73 of 206 patients (35.4%). On univariate analyses, patients with poor collateral status at baseline were older; were hypertensive; had higher white blood cell count, blood glucose, D-dimer, and serum uric acid levels; and were more likely to have metabolic syndrome. Multivariate modeling identified metabolic syndrome (odds ratio [OR] = 3.22, 95% confidence interval [CI] = 1.69-6.15, p < 0.001), hyperuricemia (per 1mg/dl serum uric acid; OR = 1.35, 95% CI = 1.12-1.62, p < 0.01), and older age (per 10 years; OR = 1.34, 95% CI = 1.02-1.77, p = 0.03) as independent predictors of poor leptomeningeal collateral status at baseline.INTERPRETATION: Metabolic syndrome, hyperuricemia, and age are associated with poor leptomeningeal collateral status in patients with acute ischemic stroke.© 2013 American Neurological Association. PMID: 23536377 Funding information This work was supported by: Canadian Institutes of Health Research, Canada NINDS NIH HHS, United States Grant ID: R01 NS083633 NHLBI NIH HHS, United States Grant ID: R01 HL111070
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.221 | 0.067 |
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".