Development of a predictive model for pediatric atopic dermatitis: A retrospective cross-sectional nationwide database study.

BACKGROUND: The rise in prevalence of atopic dermatitis (AD) has been correlated with numerous elements of the exposome, modern-day lifestyle, and familial history. The combined analysis of familial history and other risk elements may allow us to understand the driving factors behind the development of AD. OBJECTIVE: To develop prediction models to assess the risk of developing AD using a large and diverse cohort (N = 77,525) and easily assessed risk factors. METHODS: We analyzed electronic medical record data from Leumit Health System. Documented predictive factors include sex, season of birth, environment (urban/rural), socioeconomic status, household smoking, diagnosed skin conditions, number of siblings, a paternal, maternal, or sibling history of an atopic condition, and antibiotic prescriptions during pregnancy or after birth. Predictive models were trained and validated on the data set. RESULTS: Medium (odds ratio [OR] 2.04, CI 1.92-2.17, P < .001) and high (OR 2.13, CI 1.95-2.34, P < .001) socioeconomic status, a previous diagnosis of contact dermatitis (OR 2.57, CI 2.37-2.78, P < .001), presence of siblings with an AD diagnosis (OR 2.21, CI 2.04-2.40, P < .001), and the percentage of siblings with any atopic condition (OR 2.58, CI 2.09-3.17, P < .001) drove risk for AD in a logistic regression model. A random forest prediction model with a sensitivity of 61% and a specificity of 84% was developed. Generalized mixed models accounting for the random effect of familial relationships boasted an area under the curve of 0.98. CONCLUSION: Predictive modeling using noninvasive and accessible inputs is a powerful tool to stratify risk for developing AD.

Online survey comparing coping responses to SARS-CoV-2 by people with and without existing health conditions in the UK.

OBJECTIVES: To investigate the impact of SARS-CoV-2 on self-reported mood, coping and health behaviours of people living with existing health conditions in the UK to understand how to improve coping responses to the threat of SARS-CoV-2. DESIGN: Quantitative design using a cross-sectional survey. SETTING: Online survey in the UK. PARTICIPANTS: UK adults (18+ years) were eligible to participate. A total of 9110 people participated. Of these, 4377 (48%) reported at least one existing health condition, 874 (10%) reported having two or more existing conditions, and 715 (8%) reported having an existing mental health condition. PRIMARY AND SECONDARY OUTCOME MEASURES: Multivariable linear regression and sequential multiple mediation analysis were used to estimate differences in average scores for active and avoidant coping response scores due to pre-existing health conditions, and to investigate the extent to which these differences are explained by differences in perceptions, beliefs, concerns and mood. RESULTS: People with pre-existing physical (+1.11 higher; 95% CI 0.88 to 1.34) and especially mental health conditions (3.06 higher; 95% CI 2.65 to 3.48) reported poorer health and used more avoidant coping compared with healthy participants. Under some strong untestable assumptions, we estimate that experiencing low mood or concern related to SARS-CoV-2 mostly explained the relationship between existing health conditions and avoidant coping. CONCLUSION: Psychological support and interventions including behaviour change are required to mitigate the psychological burden of the SARS-CoV-2 pandemic and increase autonomy in people with and without pre-existing conditions during this highly uncertain time. Psychologists are well placed to support clinicians and people with existing health conditions to minimise the psychological impact of SARS-CoV-2, in order to alleviate the subsequent strain on healthcare services.

First Branchial Cleft Anomalies: Awareness Is Key.

Two patients presented with fluctuant areas inferior to the pinna. The first required numerous procedures and investigations before a correct diagnosis was obtained. However, with awareness of this condition, the subsequent patient was quickly identified and managed appropriately. First branchial cleft abnormalities are uncommon, however, present with common symptoms. Their location and characteristics in paediatric patients is key to having it in the differential diagnosis. Consideration of this condition by ENT surgeons is key to prevent multiple invasive and futile operations in our paediatric cohort.

Rate of Cognitive Decline in Alzheimer's Disease Stratified by Age.

BACKGROUND: There is only limited information available about the effect of age on course of cognitive decline in patients with onset of Alzheimer's disease (AD) over the age of 64 years. OBJECTIVE: We compared the rate of, and factors affecting, cognitive decline in patients with AD aged < 65 years (young-onset AD), 65-74 years (middle-onset AD), and ≥75 years (late-onset AD). METHOD: The study used longitudinal data from the Essex Memory Clinic which included a total of 305 participants; 56 had YOAD, 73 had MOAD, and 176 had LOAD. The rate of cognitive decline was measured using scores from the Mini-Mental State Examination (MMSE), and the data were examined using multilevel models analysis. RESULTS: There was evidence of a difference in cognitive decline across the age groups with the YOAD group declining 2.8 MMSE points per year, those with MOAD declined 2.0 MMSE points per year, and the LOAD group declined 1.4 MMSE points per year. CONCLUSIONS: Patients with LOAD have a better prognosis than YOAD and MOAD. However, even between the MOAD and LOAD groups, age is a significant predictor of cognitive decline, with older patients having a more benign course.