A Prediction Rule for the Dystonic Spread of Blepharospasm: A 4-Year Prospective Cohort Study.

OBJECTIVE: Blepharospasm (BSP), focal dystonia with the highest risk of spread, lacks clear understanding of early spreading risk factors and objective prognostic indicators. We aimed to identify these risk factors through clinical and electrophysiological assessments, and to establish a predictive model for dystonic spread in BSP. METHODS: We prospectively followed BSP patients for 4 years, collecting data on dystonic spread, and conducting electrophysiological evaluations. The blink reflex, masseter inhibitory reflex, and trigeminal somatosensory evoked potential were assessed. Univariable and multivariable Cox proportional hazard regression models were used to assess clinical characteristics associated with BSP dystonic spread. A predictive model was constructed using a nomogram, and performance of the model was evaluated using the area under the receiver operating characteristic curve. RESULTS: A total of 136 enrolled participants (mean age 56.34 years) completed a 4-year follow-up. Among them, 62 patients (45.6%) showed spread to other body regions. Multivariable Cox regression analysis showed that a high Hamilton Anxiety Scale score (hazard ratio 1.19, 95% confidence interval 1.13-1.25, p < 0.001), prolonged trigeminal somatosensory evoked potential mandibular branch P1-N2 peak interval (hazard ratio 1.11, 95% confidence interval 1.02-1.21, p = 0.017), and elevated trigeminal somatosensory evoked potential mandibular branch P1-N2 peak amplitude (hazard ratio 1.26, 95% confidence interval 1.12-1.41, p < 0.001) were independent risk factors for BSP dystonic spread within 4 years. Combining these factors, the predictive models demonstrated excellent discriminative ability, with the receiver operating characteristic curve score being 0.797, 0.790, 0.847, and 0.820 at 1, 2, 3 and 4 years after enrollment, respectively. INTERPRETATION: We established a predictive model with significant value for anticipating dystonic spread in BSP, offering crucial evidence. These findings contribute essential insights into the early clinical identification of the development and evolution of BSP diseases. ANN NEUROL 2024.

Kinect-based objective assessment of the acute levodopa challenge test in parkinsonism: a feasibility study.

INTRODUCTION: The acute levodopa challenge test (ALCT) is an important and valuable examination but there are still some shortcomings with it. We aimed to objectively assess ALCT based on a depth camera and filter out the best indicators. METHODS: Fifty-nine individuals with parkinsonism completed ALCT and the improvement rate (IR, which indicates the change in value before and after levodopa administration) of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was calculated. The kinematic features of the patients' movements in both the OFF and ON states were collected with an Azure Kinect depth camera. RESULTS: The IR of MDS-UPDRS III was significantly correlated with the IRs of many kinematic features for arising from a chair, pronation-supination movements of the hand, finger tapping, toe tapping, leg agility, and gait (rs = - 0.277 ~ - 0.672, P < 0.05). Moderate to high discriminative values were found in the selected features in identifying a clinically significant response to levodopa with sensitivity, specificity, and area under the curve (AUC) in the range of 50-100%, 47.22%-97.22%, and 0.673-0.915, respectively. The resulting classifier combining kinematic features of toe tapping showed an excellent performance with an AUC of 0.966 (95% CI = 0.922-1.000, P < 0.001). The optimal cut-off value was 21.24% with sensitivity and specificity of 94.44% and 87.18%, respectively. CONCLUSION: This study demonstrated the feasibility of measuring the effect of levodopa and objectively assessing ALCT based on kinematic data derived from an Azure Kinect-based system.

Therapeutic robots for post-stroke rehabilitation.

Stroke is a prevalent, severe, and disabling health-care issue on a global scale, inevitably leading to motor and cognitive deficits. It has become one of the most significant challenges in China, resulting in substantial social and economic burdens. In addition to the medication and surgical interventions during the acute phase, rehabilitation treatment plays a crucial role in stroke care. Robotic technology takes distinct advantages over traditional physical therapy, occupational therapy, and speech therapy, and is increasingly gaining popularity in post-stroke rehabilitation. The use of rehabilitation robots not only alleviates the workload of healthcare professionals but also enhances the prognosis for specific stroke patients. This review presents a concise overview of the application of therapeutic robots in post-stroke rehabilitation, with particular emphasis on the recovery of motor and cognitive function.