Health economic impact of Nerinetide in addition to mechanical thrombectomy without concurrent alteplase
Bibliographic record
Abstract
Background and purposeThe ESCAPE-NA1 trial has shown that intravenous Nerinetide improves clinical outcomes in acute ischemic stroke patients with large vessel occlusion undergoing endovascular treatment without concurrent intravenous alteplase. We assessed the health economic impact of intravenous Nerinetide as an adjunctive treatment in endovascular treatment patients who do not receive concurrent intravenous alteplase.MethodsData are from the ESCAPE-NA1 trial, in which acute ischemic stroke with large vessel occlusion endovascular treatment patients were randomized to receive intravenous Nerinetide or placebo. Only those patients not treated with concurrent intravenous alteplase were included in this analysis. We used a Markov state transition model (12 months cycle length) to estimate expected lifetime costs and outcomes, assuming Nerinetide cost being zero for the purpose of this analysis. We calculated incremental cost-effectiveness ratios and derived mean net monetary benefits with 95% prediction intervals from a probabilistic sensitivity analysis. Upper, middle, and lower willingness-to-pay thresholds were set at $50,000,$100,000, and $150,000.ResultsThe incremental cost-effectiveness ratio for Nerinetide in addition to endovascular treatment was $13,721/quality-adjusted life year (healthcare perspective) and $14,453/quality-adjusted life year (societal perspective). At the upper willingness-to-pay threshold, Nerinetide in addition to endovascular treatment resulted in a higher mean net monetary benefit compared to endovascular treatment alone, both from a healthcare perspective (449,526 [95% prediction interval: 448,627-450,425] vs. 382,584 [381,781-383,386]) and a societal perspective (350,750 [349,842-351,658] vs. 282,896 [282,068-283,725]). Mean net monetary benefits were also higher for Nerinetide in addition to endovascular treatment at the middle and lower willingness-to-pay thresholds.ConclusionTreating patients with a cerebroprotectant, such as Nerinetide, in addition to endovascular treatmentl in patients who cannot receive intravenous alteplase may be beneficial from a health-economic standpoint.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".