Abstract T P49: Improving Outcome of Placebo- but not Albumin-Treated Subjects Over the Course of the ALIAS Part 2 Multicenter Trial: Differential Influence of Thrombolytic Therapy
Bibliographic record
Abstract
In the ALIAS2 Trial, 841 subjects were randomized 1:1 to treatment with either 25% albumin (ALB, 2 g/kg) or normal saline within 5 hours of stroke onset, and the primary outcome (NIHSS 0-1 and/or modified Rankin scale 0-1) was assessed at 90 days. While overall outcomes did not differ by treatment (44% for both groups), we observed a steadily improving favorable rate in the saline-placebo arm but not in the ALB arm over the trial’s 3.5 year course. This was further analyzed here. Methods and Findings: Logistic regression confirmed a significant randomization-order x treatment interaction (p<0.001). Thus, at the first pre-specified interim analysis of N=275 subjects, favorable outcome was seen in 44.8% with ALB but only 30.3% with saline (relative benefit 1.48, p=0.0028), while at the second interim analysis of N=550 subjects, the saline rate had risen to 37.5% while the ALB rate remained steady at 44.6% (relative benefit 1.21, p=0.0176). This trend-over-time in saline subjects was highly significant (Jonckheere-Terpstra (J-T) test, p=0.001; Pearson coefficient r=0.792), but there was no such trend in ALB subjects (J-T p=1.000). Simulation analysis confirmed that the saline trend could not have arisen by chance (p=0.0007). Importantly, intravenous tPA use also increased significantly during the trial in both ALB and saline subjects (initial rate 74%, final rate 95%, p<0.0001). Separate logistic regression analyses revealed a highly significant effect of IV tPA use on outcome in saline subjects (odds ratio 2.8, 95% CI 1.5-5.3, p=0.001) but only a marginal effect in ALB subjects (odds ratio 1.7, p=0.06). Conclusion: ALB treatment appears to have conferred a stable (and desirable) therapeutic “ceiling effect” throughout the trial (in the absence of significant toxicity), while saline subjects (who were unable to benefit from ALB) were susceptible to improved outcome from increasing tPA use as the trial progressed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".