Electronic cigarettes and health with special focus on cardiovascular effects: position paper of the European Association of Preventive Cardiology (EAPC)

Background: Tobacco use is the single largest preventable risk factor for premature death of non-communicable diseases and the second leading cause of cardiovascular disease. In response to the harmful effects of tobacco smoking, the use of electronic cigarettes (e-cigarettes) has emerged and gained significant popularity over the past 15 years. E-cigarettes are promoted as safe alternatives for traditional tobacco smoking and are often suggested as a way to reduce or quit smoking. However, evidence suggests they are not harmless. Discussion: The rapid evolution of the e-cigarette market has outpaced the legislator’s regulatory capacity, leading to mixed regulations. The increasing use of e-cigarettes in adolescents and young individuals is of concern. While the long-term direct cardiovascular effects of e-cigarettes remain largely unknown, the existing evidence suggests that the e-cigarette should not be regarded as a cardiovascular safe product. The contribution of e-cigarette use to reducing conventional cigarette use and smoking cessation is complex, and the impact of e-cigarette use on long-term cessation lacks sufficient evidence. Conclusion: This position paper describes the evidence regarding the prevalence of e-cigarette smoking, uptake of e-cigarettes in the young, related legislations, cardiovascular effects of e-cigarettes and the impact of e-cigarettes on smoking cessation. Knowledge gaps in the field are also highlighted. The recommendations from the population science and public health section of the European Association of Preventive Cardiology are presented

2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts)Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR).

European Society of CardiologyThis is the author accepted manuscript. The final version is available from Oxford University Press via http://dx.doi.org/10.1093/eurheartj/ehw10

2020 ESC Guidelines on sports cardiology and exercise in patients with cardiovascular disease

The Task Force on sports cardiology and exercise in patients with cardiovascular disease of the European Society of Cardiology (ESC

The Silent Epidemic of Diabetic Ketoacidosis at Diagnosis of Type 1 Diabetes in Children and Adolescents in Italy During the COVID-19 Pandemic in 2020

To compare the frequency of diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes in Italy during the COVID-19 pandemic in 2020 with the frequency of DKA during 2017-2019

Machine Learning Approach for Care Improvement of Children and Youth with Type 1 Diabetes Treated with Hybrid Closed-Loop System

Type 1 diabetes is a disease affecting beta cells of the pancreas and it’s responsible for a decreased insulin secretion, leading to an increased blood glucose level. The traditional method for glucose treatment is based on finger-stick measurement of the blood glucose concentration and consequent manual insulin injection. Nowadays insulin pumps and continuous glucose monitoring systems are replacing them, being simpler and automatized. This paper focuses on analyzing and improving the knowledge about which Machine Learning algorithms can work best with glycaemic data and tries to find out the relation between insulin pump settings and glycaemic control. The dataset is composed of 90 days of recordings taken from 16 children and adolescents. Three Machine Learning approaches, two for classification, Logistic Regression (LR) and Random Forest (RL), and one for regression, Multivariate Linear Regression (MLR), have been used for the purpose. Specifically, the pump settings analysis was performed based on the Time In Range (TIR) computation and comparison consequent to pump setting changes. RF and MLR have shown the best results, while, for the settings’ analysis, the data show a discrete correlation between changes and TIRs. This study provides an interesting closer look at the data recorded by the insulin pump and a suitable starting point for a thorough and complete analysis of them

A Risk Profile for Disordered Eating Behaviors in Adolescents with Type 1 Diabetes: A Latent Class Analysis Study

(1) Background: This multi-center study aimed to identify a risk profile for disordered eating behaviors (DEBs) in youth with type 1 diabetes (T1D) based on their dietary intake, lipid profile, body mass index (BMI-SDS), and glycometabolic control. (2) Methods: Adolescents aged 11 to 18 years from five centers across Italy were recruited. Lipid profile, HbA1c, BMI-SDS, and dietary intake data were collected. The risk for developing DEBs was assessed via the Diabetes Eating Problems Survey-R (DEPS-R) questionnaire. A latent class analysis (LCA) was performed using a person-centered approach. (3) Results: Overall, 148 participants aged 11–18 (12.1, ±3.34), 52% males with a mean diabetes duration of 7.2 (±3.4), were enrolled. Based on the results of the DEBS-R score, LCA allowed us to highlight two different classes of patients which were defined as “at-risk” and “not at-risk” for DEB. The risk profile for developing DEBs is characterized by higher BMI—SDS (23.9 vs. 18.6), higher HbA1c (7.9 vs. 7.1%), higher LDL cholesterol (99.9 vs. 88.8 mg/dL), lower HDL cholesterol (57.9 vs. 61.3 mg/dL), higher proteins (18.2 vs. 16.1%), and lower carbohydrates (43.9 vs. 45.3%). Adolescents included in the “at-risk” class were significantly older (p = 0.000), and their parents’ SES was significantly lower (p = 0.041). (4) Conclusions: This study allowed us to characterize a risk profile for DEBs based on dietary behavior and clinical parameters. Early identification of the risk for DEBs allows timely intervention and prevention of behavior disorders

Efficacy and Safety of Dimeticone in the Treatment of Lice Infestation through Prophylaxis of Classmates

Background: We conducted a study to evaluate efficacy and safety of dimeticone 4%, a lotion with no conventional insecticide activity, to cure lice infection and to prevent spread of infestation/reinfestation by prophylaxis of classmates.Methods: The study is carried out between April 2008 and June 2008 in Petranova International Institute in Rome. A total of 131 children, aged 3 to 13 years (median age: 7 years) were included in the study. All participants received treatment with dimeticone 4% that was applied both to children with the infestation, to cure it, and to all classmates, to prevent the spreading of the infestation. They have been controlled after 7 and 30 days from the application of dimeticone.Results: At baseline we found a positivity of lice infestation in 23/131 children (17.6%), whereas 108/131 (82.4%) children were free from lice. After 7 days of treatment with dimeticone 4%, 7/23 (30.4%) positive children still had lice infestation, with a cure rate of 69.6% (16/23). At 30 days 26/131 children (19.9%) were infested: 15 children were lice free at baseline whereas 11 had lice at both evaluations; the cure rate amounted to 52.2% (12/23). The reinfestation rate (percentage of positive children that showed negativity at baseline) was 5.3% (7/131) at 7 days and 11.5% (15/131) at 30 days.Conclusion: The lower reinfestation rate showed in our trial suggests that this approach could be effective in reducing spreading of head lice in small communities. More studies are needed to confirm our finding

Trends and Cyclic Variation in the Incidence of Childhood Type 1 Diabetes in Two Italian Regions Over 33 Years and During The Covid-19 Pandemic

Aims: There is conflicting evidence about the impact of the COVID-19 pandemic on the incidence of type 1 diabetes. Here we analyzed long-term trends in the incidence of type 1 diabetes in Italian children and adolescents from 1989 to 2019 and compared the incidence observed during the COVID-19 pandemic with that estimated from long-term data. Materials and methods: This was a population-based incidence study using longitudinal data from two diabetes registries in mainland Italy. Trends in the incidence of type 1 diabetes from 1 January 1989 through 31 December 2019 were estimated using Poisson and segmented regression models. Results: There was a significant increasing trend in the incidence of type 1 diabetes of 3.7% per year (95%CI 2.4-4.9) between 1989 and 2003, a breakpoint in 2003, and then a constant incidence until 2019 (0.5%, 95%CI -0.01-2.4). There was a significant four-year cycle in incidence over the entire study period. The rate observed in 2021 (26.7, 95%CI 23.0-30.9) was significantly higher than expected (19.5, 95%CI 17.6-21.4; p = 0.010). Conclusion: Long-term incidence analysis showed an unexpected increase in new cases of type 1 diabetes in 2021. The incidence of type 1 diabetes now needs continuous monitoring using population registries to better understand the impact of COVID-19 on new-onset type 1 diabetes in children. This article is protected by copyright. All rights reserved