Golden Hour Intravenous Thrombolysis for Acute Ischemic Stroke: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVES: The benefits of intravenous thrombolysis are time-dependent, with maximum efficacy when administered within the first "golden" hour after onset. Nevertheless, the impact of golden hour thrombolysis has not been well quantified. METHODS: Medline, Embase, and Web of Science databases were systematically searched from inception to August 27, 2023. We included studies that reported safety and efficacy outcomes of ischemic stroke patients treated with intravenous thrombolysis in the golden hour versus later treatment window. The primary outcome was an excellent functional outcome, defined as a modified Rankin Scale score of 0-1 at 90 days. The secondary efficacy outcome was a good functional outcome (defined as modified Rankin Scale score of 0-2). The main safety outcome was symptomatic intracerebral hemorrhage. RESULTS: Seven studies involving 78,826 patients met the selection criteria. Golden hour thrombolysis was associated with higher odds of 90-day excellent functional outcomes (OR 1.40, 95% CI 1.16-1.67) and 90-day good functional outcomes (OR 1.38, 95% CI 1.13-1.69) compared with thrombolysis outside the golden hour. The number needed to treat to benefit for golden hour thrombolysis to reduce disability by at least 1 level on the modified Rankin Scale per patient was 2.6. Rates of symptomatic intracerebral hemorrhage and mortality were similar between groups. INTERPRETATION: Golden hour thrombolysis significantly improved acute ischemic stroke outcomes. The findings provide rationale for intensive efforts aimed at expediting thrombolytic therapy within the golden hour window following the onset of acute ischemic stroke. ANN NEUROL 2024;96:582-590.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".