Journal Club: Efficacy and Safety of IV Thrombolysis for Acute Ischemic Stroke Patients With Moyamoya Disease
Bibliographic record
Abstract
The "Efficacy and Safety of IV Thrombolysis for Acute Ischemic Stroke Patients With Moyamoya Disease" study was a retrospective analysis of administrative data to examine the safety and efficacy of intravenous thrombolysis (IVT) in patients with moyamoya disease (MMD). Here, we examine this study in detail, looking at its strengths and limitations. The authors identified 3,050 patients with MMD of whom 214 (7.0%) had received IVT. The study used propensity score matching (PSM), a technique which aims to reduce confounding by matching treatment and control groups. After PSM, there were 212 patients in the IVT group and 818 patients in the no-IVT group. A higher proportion of patients in the IVT group had a good outcome (return to home with self-care) than the no-IVT group (53.6% [95% CI 42.7%-63.3%] vs 45.1% [95% CI 39.9%-50.3%]). There were no differences in intracranial hemorrhage (ICH) or mortality between groups. The main strength of this study was the large sample size acquired from nationwide data for this uncommon disease. A few limitations include (1) the observational nature of the study with lack of details about the definition of MMD or of ICH, (2) lack of confirmatory imaging evidence of infarct at 24 hours, and (3) limitations inherent to the technique of PSM. In summary, this study was the first large retrospective study to provide evidence that IVT may be safe in patients with MMD. Future studies are needed to determine whether there is benefit of IVT in these patients.
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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 | 0.004 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".