Is concurrent intravenous alteplase in patients undergoing endovascular treatment for large vessel occlusion stroke cost-effective even if the cost of alteplase is only US$1?
Bibliographic record
Abstract
BACKGROUND: The added value of intravenous (IV) alteplase in large vessel occlusion (LVO) stroke over and beyond endovascular treatment (EVT) is controversial. We compared the long-term costs and cost-effectiveness of a direct-to-EVT paradigm in LVO stroke patients presenting directly to the mothership hospital to concurrent EVT and IV alteplase. METHODS: We used a decision model consisting of a short-run model to analyze costs and functional outcomes within 90 days after the index stroke and a long-run Markov state transition model (cycle length of 12 months) to estimate expected lifetime costs and outcomes. Outcome data were from the DIRECT-MT trial (NCT03469206). Incremental cost-effectiveness ratios and net monetary benefits were calculated and probabilistic sensitivity analysis was performed. Analysis was performed from a healthcare perspective and a societal perspective using both a minimal assumed alteplase cost of US$1 and true alteplase cost. RESULTS: When assuming a minimal cost of alteplase of $1, EVT with concurrent IV alteplase resulted in incremental lifetime cost of $5664 (healthcare perspective)/$4804 (societal perspective) and a decrement of 0.25 quality-adjusted life years (QALYs) compared with EVT only, indicating dominance of the EVT only approach. Net monetary benefits were consistently higher for EVT only compared with EVT with concurrent alteplase. Probabilistic sensitivity analysis showed increased costs without an increase in QALYs for EVT and concurrent IV alteplase compared with EVT only. Results were even more in favor of EVT when the true cost of alteplase was used for analysis. CONCLUSION: EVT without concurrent alteplase is the preferred strategy 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".