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.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".