Abstract MP3: Low Dose versus Standard Dose Alteplase in Acute Lacunar Ischemic Stroke
Bibliographic record
Abstract
Objective: To identify any differential efficacy and safety of low- versus standard-dose intravenous alteplase for lacunar versus non-lacunar acute ischemic stroke (AIS) in the alteplase dose-arm of the Enhanced Control of Hypertension and Thrombolysis Stroke Study (ENCHANTED). Methods: In a cohort of 3297 ENCHANTED participants, we identified those with lacunar or non-lacunar AIS with different levels of confidence (definite/probable/possible) according to pre-specified definitions based on clinical and adjudicated imaging findings. Logistic regression models were used to determine associations of lacunar AIS with 90-day outcomes (primary, modified Rankin scale [mRS] scores 2-6; secondary, other mRS scores, intracerebral hemorrhage [ICH], and early neurologic deterioration [END] or death) and treatment effects of low- versus standard-dose alteplase across lacunar and non-lacunar AIS with adjustment for baseline covariables. Results: Of 2588 participants with available imaging and clinical data, we classified cases as definite or probable lacunar (n=490) or non-lacunar AIS (n=2098) for primary analyses. Regardless of the alteplase dose received, lacunar AIS participants had favorable functional (mRS 2-6, adjusted odds ratio [95% CI] 0.60 [0.47-0.77]) and other clinical or safety outcomes, compared to participants with non-lacunar AIS. Overall, low-dose alteplase (compared to standard) had no differential effect on the functional outcome (mRS 2-6, 1.04 [0.87-1.24]) but reduced the risk of ICH. There were no differential treatment effects of low- versus standard-dose alteplase on all outcomes across lacunar and non-lacunar AIS (all P interaction ≥0.07). Conclusions: We found no clear evidence from the ENCHANTED trial that low-dose alteplase had any advantages over standard-dose for definite/probable lacunar AIS.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".