Detrimental Effect of Acute Hyperglycemia on the Outcomes of Large Ischemic Region Stroke
Bibliographic record
Abstract
BACKGROUND: Although endovascular therapy (EVT) is effective for large ischemic region strokes, the impact of hyperglycemia remains unclear. METHODS AND RESULTS: We analyzed data from the RESCUE-Japan LIMIT (Recovery by Endovascular Salvage for Cerebral Ultra-Acute Embolism-Japan Large Ischemic Core) trial, which randomized stroke patients with Alberta Stroke Program Early Computed Tomography Score of 3 to 5 to EVT versus medical management. Outcomes were compared among patients with normoglycemia (<140 mg/dL), moderate hyperglycemia (≥140, <180 mg/dL), and severe hyperglycemia (≥180 mg/dL) on admission. Among 200 patients (median age 76.5 years, median glucose level 131 mg/dL, EVT 50%), diabetes prevalence was 10.0%, 18.4%, and 71.0% in the groups with normoglycemia (n=120), moderate hyperglycemia (n=49), and severe hyperglycemia (n=31), respectively. Achievement of modified Rankin Scale score 0 to 3 at 90 days was less frequent in the group with severe hyperglycemia (6.5%) than in the groups with normoglycemia (25.0%) and moderate hyperglycemia (24.5%), with adjusted odds ratios (aOR) of 1.48 (95% CI, 0.59-3.72) for moderate and 0.17 (95% CI, 0.03-0.95) for severe hyperglycemia relative to normoglycemia. The risk of symptomatic intracranial hemorrhage was higher for moderate hyperglycemia (6.1%; aOR, 2.86 [95% CI, 0.42-19.71]) and particularly for severe hyperglycemia (25.8%; aOR, 18.59 [95% CI, 2.47-139.87]) compared with normoglycemia (2.5%). Symptomatic intracranial hemorrhage rates were similar for EVT and medical management in normoglycemia (1.6% versus 3.4%) and moderate hyperglycemia (5.0% versus 6.9%), but for severe hyperglycemia, the rate was higher in patients with EVT (36.8%) than in those without (8.3%). CONCLUSIONS: Severe hyperglycemia was associated with worse functional prognosis and increased symptomatic intracranial hemorrhage in large ischemic region strokes. REGISTRATION: URL: https://clinicaltrials.gov. Identifier: NCT03702413.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".