The feasibility of mechanical thrombectomy versus medical management for acute stroke with a large ischemic territory.

Publication/Presentation Date

1-17-2025

Abstract

BACKGROUND: Mechanical thrombectomy (MT) for acute ischemic stroke is generally avoided when the expected infarction is large (defined as an Alberta Stroke Program Early CT Score of < 6).

OBJECTIVE: To perform a meta-analysis of recent trials comparing MT with best medical management (BMM) for treatment of acute ischemic stroke with large infarction territory, and then to determine the cost-effectiveness associated with those treatments.

METHODS: A meta-analysis of the RESCUE-Japan, SELECT2, and ANGEL-ASPECT trials was conducted using R Studio. Statistical analysis employed the weighted average normal method for calculating mean differences from medians in continuous variables and the risk ratio for categorical variables. TreeAge software was used to construct a cost-effectiveness analysis model comparing MT with BMM in the treatment of ischemic stroke with large infarction territory.

RESULTS: The meta-analysis showed significantly better functional outcomes, with higher rates of patients achieving a modified Rankin Scale score of 0-3 at 90 days with MT as compared with BMM. In the base-case analysis using a lifetime horizon, MT led to a greater gain in quality-adjusted life-years (QALYs) of 3.46 at a lower cost of US$339 202 in comparison with BMM, which led to the gain of 2.41 QALYs at a cost of US$361 896. The incremental cost-effectiveness ratio was US$-21 660, indicating that MT was the dominant treatment at a willingness-to-pay of US$70 000.

CONCLUSIONS: This study shows that, besides having a better functional outcome at 90-days' follow-up, MT was more cost-effective than BMM, when accounting for healthcare cost associated with treatment outcome.

Volume

17

Issue

2

First Page

223

Last Page

228

ISSN

1759-8486

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

38471764

Department(s)

Administration and Leadership

Document Type

Article

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