Stroke remains one of the leading causes of disability and mortality worldwide, particularly in the elderly, with ischemic stroke accounting for approximately 84 % of all cases. Therefore, the prevention and acute management of ischemic stroke are of paramount importance [1]. Mechanical thrombectomy (MT) is an invasive treatment option that facilitates recanalization in AIS patients, reducing both disability and mortality rates. Growing evidence supports the safety and efficacy of MT, which has become the standard treatment for large vessel occlusion (LVO)-related strokes. Several randomized clinical trials have demonstrated its superiority over best medical therapy [2], [3].

The pathogenesis of ischemic stroke is multifactorial, with neuroinflammation playing a crucial role in both disease progression and prognosis [4]. Following an ischemic event, inflammation occurs in the affected brain region, leading to blood-brain barrier disruption and subsequent neuronal injury [5]. Despite successful recanalization of the occluded artery, approximately half of the patients fail to achieve favorable clinical outcomes—a phenomenon known as futile recanalization (FR). Identifying simple and robust biomarkers to predict prognosis in AIS patients undergoing MT is therefore critical [6].

Several inflammatory indices have been utilized to predict stroke prognosis. Recently, the MII has gained attention as a potential prognostic marker. MII consists of three subtypes: MII-1, MII-2, and MII-3, each incorporating different hematological and inflammatory parameters [7].

In addition to laboratory-based biomarkers, several clinical prediction models have been developed to estimate post-thrombectomy outcomes. Notably, the THRIVE [8], PANDA [9], and BAND scores [10] integrate demographic, clinical, and imaging parameters to identify patients at higher risk of futile recanalization. Incorporating such models into clinical practice has improved risk stratification; however, they do not account for systemic inflammatory status, which may provide complementary prognostic information.

To the best of our knowledge, the prognostic significance of MII in AIS patients undergoing MT has not been previously reported. This study aims to evaluate the predictive value of MII-1, MII-2, and MII-3 in determining FR and clinical outcomes in AIS patients treated with MT.