ObjectivesCerebral reperfusion therapy is recommended for the treatment of acute ischemic stroke. However, the outcomes of patients receiving this therapy in middle- and low-income countries should be better defined. This study aimed to evaluate the clinical and functional outcomes of cerebral reperfusion therapy in patients with ischemic stroke.Materials and MethodsThis retrospective study included patients with ischemic stroke treated with cerebral reperfusion therapy, including intravenous thrombolysis (IVT), mechanical thrombectomy (MT), and IVT with MT. The primary outcomes were death and disability, assessed using the modified Rankin scale (mRS), and stroke severity, assessed using the National Institutes of Health Stroke Scale (NIHSS), after intervention and 90 days after ictus. The association between the type of treatment and the primary outcome was assessed using binary logistic regression after adjusting for confounding variables. Furthermore, receiver operating characteristic (ROC) curves were generated to identify the cutoff point of the NIHSS score that could best discriminate the mRS score in all types of treatments.ResultsPatients (n = 291) underwent IVT only (n = 241), MT (n = 21), or IVT with MT (n = 29). In the IVT with MT group, the incidence of death within 90 days increased by five times (OR, 5.192; 95% CI, 2.069–13.027; p = 0.000), prevalence of disability increased by three times (OR, 3.530; 95% CI, 1.376–9.055; p = 0.009) and NIHSS score increased after IVT (from 14.4 ± 6.85 to 17.8 ± 6.36; p = 0.045). There was no significant difference between the initial NIHSS score and that after MT (p = 0.989). Patients' NIHSS score that increased or decreased by 2.5 points had a sensitivity of 0.74 and specificity of 0.65, indicating severe disability or death in these patients.ConclusionAltogether, a 2.5-point variation in NIHSS score after reperfusion is an indicator of worse outcomes. In our particular context, patients receiving the combination of IVT and MT had inferior results, which probably reflects challenges to optimize MT in LMIC.