Health Economic Impact of Incomplete Reperfusion Patterns After Endovascular Thrombectomy in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Incomplete reperfusion in endovascular thrombectomy (EVT) impacts patients' outcomes. Different incomplete reperfusion patterns may benefit from targeted therapeutic strategies, e.g. EVT-accessible incomplete reperfusion patterns could improve by performing additional EVT attempts, while EVT-non-accessible incomplete patterns might benefit from pharmacological therapies. The health-economic implications of these therapies are uncertain. This study aims to assess the potential economic benefits of improving incomplete reperfusion patterns after EVT. MATERIALS AND METHODS: Retrospective Data analysis from the ESCAPE-NA1 trial, which included patients with large vessel occlusion strokes undergoing EVT. Reperfusion patterns were classified as near-/complete (eTICI 2c3), EVT-accessible incomplete (eTICI 2b), or EVT-non-accessible incomplete (eTICI 2b) and we compared multiple attempts to achieve eTICI 2c3 vs. first-pass eTICI 2c3. A Markov-Model was built to compare lifetime costs and quality adjusted life-years (QALY) for each reperfusion pattern over a lifetime horizon, considering both healthcare and societal perspectives. RESULTS: A total of 1105 of patients were enrolled in the ESCAPE-NA1 trial of which 949 with eTICI 2b, 2c and 3 were further analyized (mean age 70.7 ± 13.6 [SD]; 463 female). Near-Complete reperfusion (eTICI 2c3) was achieved in 506/1105 patients (45.8%). Incomplete reperfusion patterns (eTICI 2b) were found in 450/1105 (40.7%) patients. Angiography imaging could be further investigated in 443/450 (98.4%) cases with 147/443(33.2%) EVT-accessible and 296/443(66.8%) EVT-non-accessible incomplete reperfusion patterns. Compared to EVT-accessible and EVT-non-accssible incomplete reperfusion, achieving complete (eTICI 2c3) reperfusion resulted in lower costs and an additional 1.14/0.45 QALYs, making it the dominant strategy from a health-economic perspective. In the complete reperfusion (eTICI 2c3) group, cumulative lifetime QALYs were similar with 5.25 for single-pass eTICI 2c3 and 5.19 for multi-pass eTICI 2c3. CONCLUSIONS: Improving incomplete reperfusion patterns after EVT has considerable potential health economic benefits, both in the presence and absence of a target occlusion that is amenable to EVT.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".