After ischemic stroke, secondary damages such as neuron loss, gliosis, and axonal degeneration occur in the nonischemic remote brain regions that have synaptic connections with the primary infarction site.These secondary damages in the remote brain regions may affect the recovery of neurological function.Several advanced neuroimaging techniques have been used to detect these secondary damages.This article reviews the research progress in this field.

Objective To evaluate the methodological quality and measurement characteristics of health literacy assessment tools for diabetic patients and to provide references for medical staff to select the best assessment tools.Methods The PubMed,Embase,CINAHL,Web of Science,CNKI,VIP database,Wanfang Data,and Chinese Biomedical Database were searched from inception to December 31,2022.Data were screened and extracted independently by 2 researchers.The consensus-based standards for the selection of health measurement instruments(COSMIN)system evaluation guidelines were spontaneously used to evaluate the included assessment tools.Finally,recommendations were made.Results A total of 15 studies were included,involving 12 health literacy assessment tools for diabetic patients.Among them,KHLS-DM and DNT-15 have satisfactory content validity and internal consistency and are recommended as Grade A.HLSQ-3 has high-quality evidence to suggest that its internal consistency is"inadequate"and recommended as Grade C,while the other 9 scales are recommended as Grade B for content validity or internal consistency of uncertain/inadequate evidence at or above the intermediate level.Conclusion KHLS-DM can evaluate written literacy,numeracy,and critical literacy of patients,and each measurement characteristic has been comprehensively evaluated with high reliability and validity,so it is recommended to be applied first.DNT-15 focuses on evaluating the numeracy of patients,which can be used in combination with other scales to evaluate health literacy of patients more comprehensively.

A number of studies have indicated that disorders of consciousness result from multifocal injuries as well as from the impaired functional and anatomical connectivity between various anterior forebrain regions. However, the specific causal mechanism linking these regions remains unclear. In this study, we used spectral dynamic causal modeling to assess how the effective connections (ECs) between various regions differ between individuals. Next, we used connectome-based predictive modeling to evaluate the performance of the ECs in predicting the clinical scores of DOC patients. We found increased ECs from the striatum to the globus pallidus as well as from the globus pallidus to the posterior cingulate cortex, and decreased ECs from the globus pallidus to the thalamus and from the medial prefrontal cortex to the striatum in DOC patients as compared to healthy controls. Prediction of the patients' outcome was effective using the negative ECs as features. In summary, the present study highlights a key role of the thalamo-basal ganglia-cortical loop in DOCs and supports the anterior forebrain mesocircuit hypothesis. Furthermore, EC could be potentially used to assess the consciousness level.
Adult ; Bayes Theorem ; Connectome ; Consciousness Disorders ; diagnostic imaging ; physiopathology ; Female ; Humans ; Machine Learning ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Neural Pathways ; diagnostic imaging ; physiopathology ; Prognosis ; Prosencephalon ; diagnostic imaging ; physiopathology ; Young Adult