Economic evaluation of endovascular treatment for acute ischaemic stroke in Thailand
Bibliographic record
Abstract
OBJECTIVES: Endovascular therapy (EVT) has proven to be clinically effective in treating large vessel occlusion acute ischaemic stroke (AIS), either alone or in combination with intravenous alteplase. Despite this, there is a limited evidence on the cost-effectiveness of EVT in Thailand and other low-income and middle-income countries. This study aims to assess whether EVT is a cost-effective therapy for AIS, and to estimate the fiscal burden to the Thai government through budget impact analysis. METHODS: An economic evaluation was performed to compare AIS therapy with and without EVT from a societal perspective. The primary outcome was incremental cost-effectiveness per quality-adjusted life year (QALY) gained. Clinical parameters were derived from both national and international literature, while cost and utility data were collected locally. The analysis applied a cost-effectiveness threshold of 160 000 Baht (~$5000) per QALY, as set by the Thai government. RESULTS: Both EVT alone and EVT combined with intravenous alteplase, among patients who are ineligible and eligible for intravenous alteplase, respectively, improved health outcomes but incurred additional cost. The combination of EVT and intravenous alteplase was associated with an incremental cost-effectiveness ratio (ICER) of 146 800 THB per QALY gained compared with intravenous alteplase alone, and the ICER of EVT alone compared with supportive care among patients ineligible for intravenous alteplase was estimated at 115 000 THB per QALY gained. Sensitivity analysis showed that the price of EVT has the greatest impact on model outcomes. Over a time horizon of 5 years, the introduction of EVT into the Thai health benefit package would require an additional budget of 887 million THB, assuming 2000 new cases per year. CONCLUSIONS: EVT represents good value for money in the Thai context, both when provided to patients eligible for intravenous alteplase, and when provided alone to those who are ineligible for intravenous alteplase.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".