Health economic impact of first-pass success among patients with acute ischemic stroke treated with mechanical thrombectomy: a United States and European perspective
Bibliographic record
Abstract
BACKGROUND: First-pass effect (FPE), restoring complete or near complete reperfusion (modified Thrombolysis in Cerebral Infarction (mTICI) 2c-3) in a single pass, is an independent predictor for good functional outcomes in the endovascular treatment of acute ischemic stroke. The economic implications of achieving FPE have not been assessed. OBJECTIVE: To assess the economic impact of achieving complete or near complete reperfusion after the first pass. METHODS: Post hoc analyses were conducted using ARISE II study data. The target population consisted of patients in whom mTICI 2c-3 was achieved, stratified into two groups: (1) mTICI 2c-3 achieved after the first pass (FPE group) or (2) after multiple passes (non-FPE group). Baseline characteristics, clinical outcomes, and healthcare resource use were compared between groups. Costs from peer-reviewed literature were applied to assess cost consequences from the perspectives of the United States (USA), France, Germany, Italy, Spain, Sweden, and United Kingdom (UK). RESULTS: Among patients who achieved mTICI 2c-3 (n=172), FPE was achieved in 53% (n=91). A higher proportion of patients in the FPE group reached good functional outcomes (90-day modified Rankin Scale score 0-2 80.46% vs 61.04%, p<0.01). The patients in the FPE group had a shorter mean length of stay (6.10 vs 9.48 days, p<0.01) and required only a single stent retriever, whereas 35% of patients in the non-FPE group required at least one additional device. Driven by improvement in clinical outcomes, the FPE group had lower procedural/hospitalization-related (24-33% reduction) and annual care (11-27% reduction) costs across all countries. CONCLUSIONS: FPE resulted in improved clinical outcomes, translating into lower healthcare resource use and lower estimated costs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".