Cost-Effectiveness of Endovascular Treatment in Large Vessel Occlusion Stroke With Mild Prestroke Disability: Results From the HERMES Collaboration
Bibliographic record
Abstract
BACKGROUND: The clinical and economic benefit of endovascular treatment (EVT) in addition to best medical management in patients with stroke with mild preexisting symptoms/disability is not well studied. We aimed to investigate cost-effectiveness of EVT in patients with large vessel occlusion and mild prestroke symptoms/disability, defined as a modified Rankin Scale score of 1 or 2. METHODS: Data are from the HERMES collaboration (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials), which pooled patient-level data from 7 large, randomized EVT trials. 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 from a health care and a societal perspective. Incremental cost-effectiveness ratio and net monetary benefits were calculated, and a probabilistic sensitivity analysis was performed. RESULTS: EVT in addition to best medical management resulted in lifetime cost savings of $2821 (health care perspective) or $5378 (societal perspective) and an increment of 1.27 quality-adjusted life years compared with best medical management alone, indicating dominance of additional EVT as a treatment strategy. The net monetary benefits were higher for EVT in addition to best medical management compared with best medical management alone both at the higher (100 000$/quality-adjusted life years) and lower (50 000$/quality-adjusted life years) willingness to pay thresholds. Probabilistic sensitivity analysis showed decreased costs and an increase in quality-adjusted life years for additional EVT compared with best medical management only. CONCLUSIONS: From a health-economic standpoint, EVT in addition to best medical management should be the preferred strategy in patients with acute ischemic stroke with large vessel occlusion and mild prestroke symptoms/disability.
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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 | 0.036 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".