Investigating Functioning Profile of Adolescents with Anorexia before and during the COVID-19 Pandemic: A Cross-Sectional Study on Mentalizing, Alexithymia, and Impulsiveness.

Anorexia nervosa (AN) usually emerges in adolescence when important changes occur in cognitive, emotional, and social processes. Mentalizing, alexithymia, and impulsiveness represent key dimensions for the understanding and interpretation of psychological difficulties in AN. The outbreak of the COVID-19 pandemic has impacted adolescents with AN, showing a worsening of the disease. The main aims of the present paper are (1) to compare adolescents with AN before and during the COVID-19 pandemic and (2) to explore the relationship between mentalizing, alexithymia, impulsiveness, and psychological difficulties related to eating disorders in adolescents with AN during the COVID-19 pandemic. One hundred and ninety-six AN female adolescents (N = 94 before COVID-19; N = 102 during COVID-19) participated in this study. The results show that adolescents with AN during the COVID-19 pandemic had a more impaired functioning profile than the before COVID-19 group. Mentalizing, alexithymia, and impulsiveness had a predictive role on psychological difficulties related to eating disorders in adolescents with AN during the COVID-19 pandemic. In conclusion, our data reveal that the COVID-19 pandemic has likely represented a stress condition that affects mental health; worsening the severity of adolescents with AN clinical condition. Lastly, predictive patterns suggest the existence of a link between difficulties in the ability to face the problems of the present time using effective strategies and the severity of psychological symptoms.

Characteristics of patients affecting the duration of positivity at SARS-CoV-2: a cohort analysis of the first wave of epidemic in Italy.

OBJECTIVES: to investigate the characteristics of patients affecting the duration of positivity test by RT-PCR in the population of Piedmont, a Region of North-West of Italy. DESIGN: observational cohort study. SETTING AND PARTICIPANTS: from the administrative database of the regional SARS-CoV-2 surveillance system, a cohort of all patients who tested positive by a RT-PCR assay to SARS-CoV-2 occurring from 22.02.2020 to 30.09.2020 in the Piedmont Region (N. 29,292) was obtained. The cohort has been linked to the hospital discharge database and to the vital statistics database. MAIN OUTCOMES MEASURES: outcome of the study was the risk of non negativization, estimated by fitting Generalizing Estimating Equation model (GEE), a longitudinal model which consider for each subject several records collected on fixed time intervals 15, 30, 45 or 60+ days from the first positive test. Negativization was defined as the condition in which two consecutive samples taken from the patient at least 24 hours apart were negative for the presence of SARS-CoV-2. RESULTS: the median duration of positive RT-PCR was 27 days. A higher median of days until positive persistence was observed in people over 80 (34 days, IQR 25-49), female (28 days, IQR 18-40), symptomatic patients (28 days, IQR 19-40), hospitalized people (32 days, IQR 21-44), patients with Charlson's index >0 (34 days, IQR 23-49), patients host of elderly nursing homes (37 days, IQR 25-51). In the GEE multivariable model, the variables associated to the non negativization at all times intervals were: older age (at 15th day: class 65+, OR 2.56, 95%CI 2.39-2.74), female gender (at 15th day: OR 1.12, 95%CI 1.06-1.18), and to be hospitalized for COVID-19 (at 15th day: OR 1.38, 95%CI 1.29-1.48). The presence of comorbidities and of symptoms were associate with the non negativization at 15th day (respectively, class 4+: OR 1.29, 95%CI 1.08-1.56 and symptoms: OR 1.20, 95%CI 1.13-1.27), but not at 45th day. CONCLUSIONS: older age, female gender, presence of comorbidities and severity of disease (proxy hospitalization for COVID-19) were risk factors for non negativization at all times intervals. The presence of symptoms was a risk factors for the non negativization after 2 weeks from the first diagnosis and not at 45th day. Using a longitudinal model for the analysis of the dataset, it is possible to compare the weight of the variables included in the model at different times and correct an overestimation of the attributable risk after the first considered time interval.