A Cross Sectional Study on the Severity of Ataxia in Posterior Circulation Stroke Patients at a Tertiary Care Center

Background: Posterior circulation strokes account for a significant proportion of all strokes and present with a variety of clinical manifestations, including ataxia. Accurate quantification of ataxia severity can aid in understanding the impact of different posterior circulation stroke patterns. Objective: This study aims to quantify the severity of ataxias in patients with posterior circulation strokes and identify risk factors associated with specific stroke patterns using MRI. Methods: We conducted a cross-sectional observational study involving 115 patients with MRI-proven posterior circulation ischemic strokes. All patients had symptom onset within 7 days. The severity of ataxias was assessed using the International Cooperative Ataxia Rating Scale (ICARS). Stroke patterns were categorized based on MRI findings into various territorial patterns, including PICA-CH, SCA-CH, CH/CP, and peduncular patterns. Results: The study population had a mean age of 57.3 ± 6.6 years, with hypertension (94.7%) being the most prevalent risk factor. Gait ataxia was present in all patients, while limb ataxia, dysarthria, and nystagmus were observed in 81.7%, 46.08%, and 60.8% of patients, respectively. The PICA-CH pattern was identified in 27% of cases, CH/CP in 23.5%, and SCA-CH in 14.8%. Severity of ataxias varied significantly across stroke patterns. The highest mean ICARS scores were observed in the SCA-CH pattern, while the lowest were in the PICA-CH pattern. Hypertension was significantly associated with increased severity of ataxias. Conclusion: The severity of ataxias in posterior circulation strokes varies according to the involved territory. SCA-CH strokes are associated with the highest severity, while PICA-CH strokes show the least severity. Hypertension is a major risk factor influencing the severity of ataxias. These findings highlight the importance of targeted management and rehabilitation strategies based on stroke patterns and associated risk factors.