Glucose Modifies the Effect of Endovascular Thrombectomy in Patients With Acute Stroke
Bibliographic record
Abstract
Background and Purpose- Hyperglycemia is a negative prognostic factor after acute ischemic stroke but is not known whether glucose is associated with the effects of endovascular thrombectomy (EVT) in patients with large-vessel stroke. In a pooled-data meta-analysis, we analyzed whether serum glucose is a treatment modifier of the efficacy of EVT in acute stroke. Methods- Seven randomized trials compared EVT with standard care between 2010 and 2017 (HERMES Collaboration [highly effective reperfusion using multiple endovascular devices]). One thousand seven hundred and sixty-four patients with large-vessel stroke were allocated to EVT (n=871) or standard care (n=893). Measurements included blood glucose on admission and functional outcome (modified Rankin Scale range, 0-6; lower scores indicating less disability) at 3 months. The primary analysis evaluated whether glucose modified the effect of EVT over standard care on functional outcome, using ordinal logistic regression to test the interaction between treatment and glucose level. Results- Median (interquartile range) serum glucose on admission was 120 (104-140) mg/dL (6.6 mmol/L [5.7-7.7] mmol/L). EVT was better than standard care in the overall pooled-data analysis adjusted common odds ratio (acOR), 2.00 (95% CI, 1.69-2.38); however, lower glucose levels were associated with greater effects of EVT over standard care. The interaction was nonlinear such that significant interactions were found in subgroups of patients split at glucose < or >90 mg/dL (5.0 mmol/L; P=0.019 for interaction; acOR, 3.81; 95% CI, 1.73-8.41 for patients < 90 mg/dL versus 1.83; 95% CI, 1.53-2.19 for patients >90 mg/dL), and glucose < or >100 mg/dL (5.5 mmol/L; P=0.004 for interaction; acOR, 3.17; 95% CI, 2.04-4.93 versus acOR, 1.72; 95% CI, 1.42-2.08) but not between subgroups above these levels of glucose. Conclusions- EVT improved stroke outcomes compared with standard treatment regardless of glucose levels, but the treatment effects were larger at lower glucose levels, with significant interaction effects persisting up to 90 to 100 mg/dL (5.0-5.5 mmol/L). Whether tight control of glucose improves the efficacy of EVT after large-vessel stroke warrants appropriate testing.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".