Psychological morbidities and fatigue in patients with confirmed COVID-19 during disease outbreak: prevalence and associated biopsychosocial risk factors

ObjectiveThe coronavirus disease 2019 (COVID-19) - a novel and highly infectious pneumonia - has now spread across China and beyond for over four months. However, its psychological impact on patients is unclear. We aim to examine the prevalence and associated risk factors for psychological morbidities and fatigue in patients with confirmed COVID-19 infection. MethodsAmidst the disease outbreak, 41 out of 105 COVID-19 patients in a local designated hospital in China were successfully assessed using a constellation of psychometric questionnaires to determine their psychological morbidities and fatigue. Several potential biopsychosocial risk factors (including pre-existing disabilities, CT severity score of pneumonia, social support, coping strategies) were assessed through multivariable logistic regression analyses to clarify their association with mental health in patients. Results43.9% of 41 patients presented with impaired general mental health, 12.2% had post-traumatic stress disorder (PTSD) symptoms, 26.8% had anxiety and/or depression symptoms, and 53.6% had fatigue. We did not find any association between pneumonia severity and psychological morbidities or fatigue in COVID-19 patients. However, high perceived stigmatization was associated with an increased risk of impaired general mental health and high perceived social support was associated with decreased risk. Besides, negative coping inclination was associated with an increased risk of PTSD symptoms; high perceived social support was associated with a decreased risk of anxiety and/or depression symptoms. ConclusionsPsychological morbidities and chronic fatigue are common among COVID-19 patients. Negative coping inclination and being stigmatized are primary risk factors while perceived social support is the main protective factor.

Gene Interactions and Structural Brain Change in Early-Onset Alzheimer's Disease Subjects Using the Pipeline Environment

OBJECTIVE: This article investigates subjects aged 55 to 65 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to broaden our understanding of early-onset (EO) cognitive impairment using neuroimaging and genetics biomarkers. METHODS: Nine of the subjects had EO-AD (Alzheimer's disease) and 27 had EO-MCI (mild cognitive impairment). The 15 most important neuroimaging markers were extracted with the Global Shape Analysis (GSA) Pipeline workflow. The 20 most significant single nucleotide polymorphisms (SNPs) were chosen and were associated with specific neuroimaging biomarkers. RESULTS: We identified associations between the neuroimaging phenotypes and genotypes for a total of 36 subjects. Our results for all the subjects taken together showed the most significant associations between rs7718456 and L_hippocampus (volume), and between rs7718456 and R_hippocampus (volume). For the 27 MCI subjects, we found the most significant associations between rs6446443 and R_superior_frontal_gyrus (volume), and between rs17029131 and L_Precuneus (volume). For the nine AD subjects, we found the most significant associations between rs16964473 and L_rectus gyrus (surface area), and between rs12972537 and L_rectus_gyrus (surface area). CONCLUSION: We observed significant correlations between the SNPs and the neuroimaging phenotypes in the 36 EO subjects in terms of neuroimaging genetics. However, larger sample sizes are needed to ensure that the effects will be detectable for a reasonable false-positive error rate using the GSA and Plink Pipeline workflows.