Abstract Background and aims Stroke frequently results in persistent neurological and functional impairments that compromise independence and quality of life. While advances in acute stroke care have improved survival, effective strategies to enhance recovery beyond the acute phase remain limited. MLC901 has been used as an adjunctive therapy in post-stroke recovery, but real-world outcome data remain scarce. Methods Anonymized data from the NeuroAiD Safe Treatment (NeST) Registry (ClinicalTrials.gov: NCT02536079), a prospective observational registry was analyzed. The analysis included 108 stroke patients treated with MLC901 in North Macedonia between 2018 and 2025. Neurological and functional outcomes were assessed using the National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin Scale (mRS) at baseline and at 3 months. Baseline status served as an internal comparator for within-patient outcome changes. Safety was evaluated through systematic adverse-event reporting. Results The mean age was 57.9 ± 16.6 years, and 40.7% of patients were female. At baseline, median NIHSS was 9.0 and median mRS was 4.0, indicating moderate neurological deficit and functional dependence. At 3 months, median NIHSS improved to 5.5 and median mRS to 2.5, representing statistically significant within-patient improvement compared with baseline (p 0.05). Follow-up completion was high across the cohort. MLC901 was well tolerated, with no serious treatment-related adverse events or unexpected safety signals observed. Conclusions In this real-world registry, stroke patients treated with MLC901 demonstrated significant neurological and functional improvement compared with baseline, alongside a favorable safety profile. These findings support the feasibility of MLC901 as an adjunctive therapy in post-stroke recovery. Conflict of interest Nothing to disclose
Building similarity graph...
Analyzing shared references across papers
Loading...
Anita Arsovska
European Stroke Journal
Saints Cyril and Methodius University of Skopje
Building similarity graph...
Analyzing shared references across papers
Loading...
Anita Arsovska (Fri,) studied this question.
www.synapsesocial.com/papers/69fd7ec6bfa21ec5bbf0715e — DOI: https://doi.org/10.1093/esj/aakag023.1445