Classification of cognitive impairment in older adults based on brain functional state measurement data via hierarchical clustering analysis.

Introduction: Cognitive impairment (CI) is a common degenerative condition in the older population. However, the current methods for assessing CI are not based on brain functional state, which leads to delayed diagnosis, limiting the initiatives towards achieving early interventions. Methods: A total of one hundred and forty-nine community-dwelling older adults were recruited. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Exam (MMSE) were used to screen for CI, while brain functional was assessed by brain functional state measurement (BFSM) based on electroencephalogram. Bain functional state indicators associated with CI were selected by lasso and logistic regression models (LRM). We then classified the CI participants based on the selected variables using hierarchical clustering analysis. Results: Eighty-one participants with CI detected by MoCA were divided into five groups. Cluster 1 had relatively lower brain functional states. Cluster 2 had highest mental task-switching index (MTSi, 13.7 ± 3.4), Cluster 3 had the highest sensory threshold index (STi, 29.9 ± 7.7), Cluster 4 had high mental fatigue index (MFi) and cluster 5 had the highest mental refractory period index (MRPi), and external apprehension index (EAi) (21.6 ± 4.4, 35.4 ± 17.7, respectively). Thirty-three participants with CI detected by MMSE were divided into 3 categories. Cluster 1 had the highest introspective intensity index (IIi, 63.4 ± 20.0), anxiety tendency index (ATi, 67.2 ± 13.6), emotional resistance index (ERi, 50.2 ± 11.9), and hypoxia index (Hi, 41.8 ± 8.3). Cluster 2 had the highest implicit cognitive threshold index (ICTi, 87.2 ± 12.7), and cognitive efficiency index (CEi, 213.8 ± 72.0). Cluster 3 had higher STi. The classifications both showed well intra-group consistency and inter-group variability. Conclusion: In our study, BFSM-based classification can be used to identify clinically and brain-functionally relevant CI subtypes, by which clinicians can perform personalized early rehabilitation.

Relationship between size and location of infarction beside lateral ventricle and motor recovery following rehabilitation.

BACKGROUND: The lesions besides lateral ventricle and motor recovery following rehabilitation have hardly been studied. OBJECTIVE: To explore the relationship between the size, location of infarction beside the lateral ventricle and motor recovery following rehabilitation. METHODS: A prospective cohort of 55 patients submitted to a Rehabilitation Medical Center between January 2015 and June 2019 who suffered a single cerebral infarction beside the lateral ventricle were included in the study. The size and distance between the posterior margin and the frontal-middle line (FML) of the lesion were measured. Follow-up was conducted until the recovery was no longer progressing. Barthel index and Brunstrom stages were used to evaluate the outcome (full recovery, partial recovery and poor recovery). Variance analysis and nonparametric test were used for the comparison between groups. Multivariate logistic regression analysis was used to screen the factors affecting the outcomes. The Pearson correlation coefficient was used to compare the volume of infarction, behind the FML and the outcomes. RESULTS: Among the 55 patients, the outcome was full recovery (n = 28), partial recovery (n = 13) and poor recovery (n = 14). Multivariate logistic regression analysis showed that volume and location of the infarction were significantly correlated with the outcome (p = 0.039, 0.050). The lesion volume in the full recovery patients was significantly smaller than that in the poor recovery patients (p < 0.01). The posterior edge of the lesion in the full recovery patients behind the FML was statistically significant compared with that in the poor recovery patients (p < 0.01). Spearman correlation analysis showed that the motor recovery was negative correlation to lesion volume (r = -0.508, P < 0.01) and location (r = -0.450, P < 0.01) of the infarction. CONCLUSION: The motor recovery of patients with cerebral infarction beside lateral ventricle is related to the volume and location of the lesion. The larger the volume of the lesion, and the farther the posterior margin of the lesion to the FML, the worse the motor recovery.

Factors predicting the instant effect of motor function after subthalamic nucleus deep brain stimulation in Parkinson's disease.

BACKGROUND: Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for Parkinson's disease (PD), the predictive effect of levodopa responsiveness on surgical outcomes was confirmed by some studies, however there were different conclusions about that through long- and short-term follow-ups. We aimed to investigate the factors which influence the predictive value of levodopa responsiveness, and discover more predictive factors of surgical outcomes. METHODS: Twenty-three PD patients underwent bilateral STN-DBS and completed our follow-up. Clinical evaluations were performed 1 week before and 3 months after surgery. RESULTS: STN-DBS significantly improved motor function of PD patients after 3 months; preoperative levodopa responsiveness and disease subtype predicted the effect of DBS on motor function; gender, disease duration and duration of motor fluctuations modified the predictive effect of levodopa responsiveness on motor improvement; the duration of motor fluctuations and severity of preoperative motor symptoms modified the predictive effect of disease subtype on motor improvement. CONCLUSIONS: The intensity of levodopa responsiveness served as a predictor of motor improvement more accurately in female patients, patients with shorter disease duration or shorter motor fluctuations; PD patients with dominant axial symptoms benefit less from STN-DBS compared to those with limb-predominant symptoms, especially in their later disease stage.