Systematic Review of the Cost and Cost-Effectiveness of Rapid Endovascular Therapy for Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Rapid endovascular therapy (EVT) is an emerging treatment option for acute ischemic stroke. Several economic evaluations have been published examining the cost-effectiveness of EVT, and many international bodies are currently making adoption decisions. The objective of this study was to establish the cost-effectiveness of EVT for ischemic stroke patients and to synthesize all the publicly available economic literature. METHODS: A systematic review of the published literature was conducted to identify economic evaluations and cost analyses of EVT for acute ischemic stroke patients. Systematic review best practices were followed, and study quality was assessed. RESULTS: Four-hundred sixty-three articles were identified from electronic databases. After deduplication, abstract review, and full-text review, 17 studies were included. Seven of the studies were cost analyses, and 10 were cost-effectiveness studies. Generally, the cost analyses reported on the cost of the approach/procedure or the hospitalization costs associated with EVT. All of the cost-effectiveness studies reported a cost per quality-adjusted life year as the primary outcomes. Studies varied in regards to the costs considered, the perspective adopted, and the time horizon used. All the studies reported a cost per quality-adjusted life year of <$50 000 as the primary outcome. CONCLUSIONS: There is a robust body of evidence for the cost and cost-effectiveness of EVT. The cost analyses suggested that although EVT was associated with higher costs, it also resulted in improved patient outcomes. From the cost-effectiveness studies, EVT seems to be good value for money when a threshold of $50 000 per quality-adjusted life year gained is adopted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".