Sulfonylureas Improve Outcome in Patients With Type 2 Diabetes and Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The sulfonylurea receptor 1-regulated NC(Ca-ATP) channel is upregulated in rodent models of stroke with block of the channel by the sulfonylurea, glibenclamide (glyburide), significantly reducing mortality, cerebral edema, and infarct volume. We hypothesized that patients with type 2 diabetes mellitus taking sulfonylurea agents both at the time of stroke and during hospitalization would have superior outcomes. METHODS: We reviewed medical records of patients with diabetes mellitus hospitalized within 24 hours of onset of acute ischemic stroke in the Neurology Clinic, Charité Hospital, Berlin, Germany, during 1994 to 2000. After exclusions, the cohort comprised 33 patients taking a sulfonylurea at admission through discharge (treatment group) and 28 patients not on a sulfonylurea (control group). The primary outcome was a decrease in National Institutes of Health Stroke Scale of 4 points or more from admission to discharge or a discharge National Institutes of Health Stroke Scale score of 0. The secondary outcome was a discharge modified Rankin Scale score < or =2. RESULTS: No significant differences, other than stroke subtype, were observed among baseline variables between control and treatment groups. The primary outcome was reached by 36.4% of patients in the treatment group and 7.1% in the control group (P=0.007). The secondary outcome was reached by 81.8% versus 57.1% (P=0.035). Subgroup analyses showed that improvements occurred only in patients with nonlacunar strokes and were independent of gender, previous transient ischemic attack, and blood glucose levels. CONCLUSIONS: Sulfonylureas may be beneficial for patients with diabetes mellitus with acute ischemic stroke. Further investigation of similar cohorts and a prospective randomized trial are recommended to confirm the present observations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".