Estimating uncertainty in read-out patterns: Application to controls-based denoising and voxel-based morphometry patterns in neurodegenerative and neuropsychiatric diseases

Quantifying pathology-related patterns in patient data with pattern expression score (PES) is a standard approach in medical image analysis. In order to estimate the PES error, we here propose to express the uncertainty contained in read-out patterns in terms of the expected squared Euclidean distance between the read-out pattern and the unknown "true" pattern (squared standard error of the read-out pattern, SE2 ). Using SE2 , we predicted and optimized the net benefit (NBe) of the recently suggested method controls-based denoising (CODE) by weighting patterns of nonpathological variance (NPV). Multi-center MRI (1192 patients with various neurodegenerative and neuropsychiatric diseases, 1832 healthy controls) were analysed with voxel-based morphometry. For each pathology, accounting for SE2 , NBe correctly predicted classification improvement and allowed to optimize NPV pattern weights. Using these weights, CODE improved classification performances in all but one analyses, for example, for prediction of conversion to Alzheimer's disease (AUC 0.81 vs. 0.75, p = .01), diagnosis of autism (AUC 0.66 vs. 0.60, p < .001), and of major depressive disorder (AUC 0.62 vs. 0.50, p = .03). We conclude that the degree of uncertainty in a read-out pattern should generally be reported in PES-based analyses and suggest using weighted CODE as a complement to PES-based analyses.

Differences in Health Literacy of Older Adults According to Sociodemographic Characteristics

BACKGROUND: The research is based on the concept of health literacy. This is the “sixth vital sign” to navigating the healthcare system and raising self-efficacy in the field of healthcare. AIM: The study aim was to present the health literacy of the elderly in the Savinja statistical region in Slovenia. METHODS: The study was based on a non-experimental quantitative research approach. The study included 199 elderly people aged 65 and more, without the presence of dementia. The data were collected using the Health Literacy and Montreal Cognitive Assessment questionnaire. We used a non-random, convenience sampling. RESULTS: We established that in the study population, 64.8 % of the population was below the level of acceptable general health literacy, whereas only 3.5 % of this population had an excellent level of health literacy. Statistically significant differences in the level of health literacy are shown in the field of healthcare treatment in older adults living with their families (F = 5,198; p ˂ 0,001). Respondents who engaged in activities in day care centres also had a higher level of health literacy (t = 3,738; p < 0,001). People with low health literacy, who use health services more frequently, should be given access to health education, based on individual presentation of contents, supported by andragogical knowledge. CONCLUSION: The health literacy of older adults is the basis for their greater care for their own health and a better quality of life.

Chronic Pain Severity and Sociodemographics: An Evaluation of the Neurobiological Interface

Chronic pain is variably associated with brain structure. Phenotyping based on pain severity may address inconsistencies. Sociodemographic groups also differ in the experience of chronic pain severity. Whether differences by chronic pain severity and/or sociodemographic groups are indicated in pain-related areas of the brain is unknown. Relations between 2 measures of chronic pain severity and brain structure via T1-weighted MRI were investigated and sociodemographic group differences explored. The observational study included 142 community-dwelling (68 non-Hispanic Black [NHB] and 74 non-Hispanic White [NHW]) adults with/at risk for knee osteoarthritis. Relationships between chronic pain severity, sociodemographic groups, and a priori selected brain structures (postcentral gyrus, insula, medial orbitofrontal, anterior cingulate, rostral middle frontal gyrus, hippocampus, amygdala, thalamus) were explored. Chronic pain severity associated with cortical thickness. NHB participants reported lower sociodemographic protective factors and greater clinical pain compared to NHWs who reported higher sociodemographic protective factors and lower clinical pain. Greater chronic pain severity was associated with smaller amygdala volumes in the NHB group and larger amygdala volumes in the NHW group. Brain structure by chronic pain stage differed between and within sociodemographic groups. Overall, chronic pain severity and sociodemographic factors are associated with pain-related brain structures. Our findings highlight the importance of further investigating social and environmental contributions in the experience of chronic pain to unravel the complex array of factors contributing to disparities. PERSPECTIVE: The study presents data demonstrating structural brain relationships with clinical pain severity, characteristic pain intensity and chronic pain stage, differ by sociodemographic groups. Findings yield insights into potential sources of previous inconsistent pain-brain relationships and highlights the need for future investigations to address social and environmental factors in chronic pain disparities research.