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Abstract It is partially unknown whether the immune response to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection persists with time. To address this issue, we detected the presence of SARS-CoV-2 antibodies in different groups of individuals previously diagnosed with COVID-19 disease (group 1 and 2), or potentially exposed to SARS-CoV-2 infection (group 3 and 4), and in a representative group of individuals with limited environmental exposure to the virus due to lockdown restrictions (group 5). The primary outcome was specific anti-SARS-CoV-2 antibodies in the different groups assessed by qualitative and quantitative analysis at baseline, 3 and 6 months follow-up. The seroconversion rate at baseline test was 95% in group 1, 61% in group 2, 40% in group 3, 17% in group 4 and 3% in group 5. Multivariate logistic regression analysis revealed male gender, close COVID-19 contact and presence of COVID-19 related symptoms strongly associated with serological positivity. The percentage of positive individuals as assessed by the qualitative and quantitative tests was superimposable. At the quantitative test, the median level of SARS-CoV-2 antibody levels measured in positive cases retested at 6-months increased significantly from baseline. The study indicates that assessing antibody response to SARS-CoV-2 through qualitative and quantitative testing is a reliable disease surveillance tool.

Children/adolescents with cancer can develop adverse effects impacting gross motor function. There is a lack of gross motor function assessment tools that have been validated for this population. The aim of this multicenter cross-sectional study was to preliminary validate the 88-item Gross Motor Function Measure (GMFM-88) for use in children/adolescents with cancer, exploring internal consistency and floor/ceiling effect. Inclusion criteria regarded children/adolescents diagnosed with cancer on treatment or

Abstract Background The prognosis of patients with Relapsed/Refractory Osteosarcoma (R/R OS) remains dismal without an agreement on systemic therapy. The use of High-Dose Ifosfamide (14 g/sqm) with an external pump in outpatient setting (14-IFO) in R/R OS patients is limited. This study represents the first retrospective cohort analysis focused on evaluating the activity and toxicity of 14-IFO in this setting. Patients and methods The study investigated 14-IFO activity, in terms of tumour response according to RECIST 1.1 criteria, as well as survival rates and toxicity, according to CTCAE v.5. Results The trial enrolled 26 patients with R/R OS. The Overall Response Rate (ORR) and Disease Control Rate (DCR) obtained was 23% and 57.5%, respectively. Patients with relapsed OS showed a higher ORR (45%) and DCR (82%) compared to refractory patients, irrespective of the number of prior treatment lines received. The achievement of disease control with 14-IFO administration enabled 27% of patients to undergo new local treatment. Four-month Progression-Free Survival (PFS) was 54% for all patients and 82% for the relapsed OS sub-group. Median Overall Survival (OSurv) was 13.7 months, with 1-year OSurv of 51% for all patients and 71% for relapsed patients. Age over 18 years and the presence of refractory disease were identified as negative prognostic factors for this patient cohort. A total of 101 cycles were evaluated for toxic assessment, demonstrating a tolerable profile without grade 3–4 non-haematological toxicities. Conclusions 14-IFO should be considered a viable treatment option for R/R OS, particularly due to its well tolerated toxicity profile and the potential for home-administration, which can improve patient quality of life without compromising efficacy.

Abstract Background The hypothesis underlying this work is that the social network of a child might have an impact on the alimentary behaviors, in particular for what concerns snack consumption patterns. Methods 1215 Italian children 6-10 ys old were interviewed using a CATI facility in January 2010. 608 "snackers" and 607 "no-snackers" were identified. Information regarding family composition, child and relatives BMI, mother perception of child weight, child, father and mother physical activity, TV watching, social network, leisure time habits and dietary habits of peers, were collected. Association of variables with the status of snacker was investigated using a multivariable logistic regression model. Results Snackers children seem to be part of more numerous social network (1.40 friends vs 1.14, p = 0.042) where the majority of peers are also eating snacks, this percentage being significantly higher (89.5 vs 76.3, p < 0.001) than in the "no-snacker" group. The snacking group is identified by the fact that it tends to practice at least 4 hours per week of physical activity (OR: 1.36, CI: 1.03-1.9). No evidence of an association between snacking consumption and overweight status has been shown by our study. Conclusions The snacking child has more active peer-to-peer social relationships, mostly related with sport activities. However, spending leisure time in sportive activities implies being part of a social environment which is definitely a positive one from the point of view of obesity control, and indeed, no increase of overweight/obesity is seen in relation to snack consumption.

Abstract Background Only few studies with small experimental samples investigated the impact of psychoactive substances on driving performance. We conducted a multicenter international cross-sectional study to evaluate the correlation between alcohol use and driving-related skill as measured by brake reaction time (RT). Methods Before and after the entrance into randomly selected recreational sites from six European countries, all subjects aged 16-35 years, owning a driver license, were asked to compile a structured socio-demographic questionnaire and measure RT (SimuNomad3 driving simulator), breath alcohol concentration (BAC; Drager Alcoltest), and drug use (Oratect III saliva test, only at the exit). Mixed regression modeling was used to evaluate the independent association between RT and alcohol concentration or drug use. Results Before the entrance into the recreational site, 4534 subjects completed all assessments and composed the final sample. Their mean age was 23.1 ± 4.2y; 68.3% were males; 54.7% had BAC > 0 g/L (assumed alcoholics); 7.5% declared illegal drug assumption (mostly cannabis). After the exit, 3019 also completed the second assessment: 71.7% showed BAC > 0 g/L. Controlling for age, gender, educational level, occupation, driver license years, and drug use, BAC was positively associated with RT, achieving significance, however, only when BAC was higher than 0.49 g/L. Significant interaction terms were found between BAC and female gender or drug use, with highest RTs (> 1 sec.) recorded among drug users with BAC > = 1 g/L. Conclusions This field study confirms previous experimental data on the negative impact of alcohol use on driving-related skill, supporting regulations and educational campaigns aimed at discouraging driving after consumption of psychoactive substances.

Abstract Background this study aims to evaluate the effectiveness and safety of laparoscopic conservative management of ureteral endometriosis. Methods Eighty cases of histologically confirmed endometriosis affecting the ureter, 10 of which with bladder involvement were prospectively studied. In detail, patients were 13 women with ureteral stenosis (7 with hydronephrosis), 32 with circular lesions totally encasing the ureter, and 35 with endometriotic foci on the ureteral wall, but not completely encasing it. They were submitted to laparoscopic ureterolysis with or without partial cystectomy, ureteroneocistostomy. The rate of surgical complications, the recurrence rate, the patients' satisfaction rate was assessed during 22 months (median) follow-up. Results Laparoscopic ureterolysis was employed for all patients and set free the ureter from the disease in 95% of cases, whereas ureteroneocystostomy was necessary for 4 patients showing severe stenosis with hydronephrosis, among which 2 had intrinsic endometriosis of the ureteral muscularis. Three post-surgery ureteral fistulae occurred in cases with ureteral involvement longer than 4 cm: two cases were successfully treated placing double J catheter, the third needed ureteroneocistostomy. During follow-up, ureteral endometriosis recurred in 2 patients who consequently underwent ureteroneocystostomy. Most patients expressed high satisfaction rate throughout the whole follow-up period. Conclusion laparoscopic ureterolysis is effective and well tolerated in most cases of ureteral endometriosis. Ureteroneocystostomy is a better strategy for patients with extended (more than 4 cm) ureteral involvement or with severe stenosis with or without hydronephrosis.

Background Integrated home care (IHC) is one strategy to provide care to people with multiple chronic conditions, and it contributes to the reduction of unnecessary emergency department (ED) use, but there are conflicting results on its effectiveness. In this study, we assessed the frequency and characteristics of ED visits occurring before, during, and after IHC in a large cohort of IHC patients enrolled over 6 years.Methods The analysis included 39 822 IHC patients identified in Italian administrative databases. Patients were grouped in tertiles according to IHC duration (short, intermediate, and long) and the number of ED visits during IHC was compared to that the 12 months before IHC enrolment and in the 12 months after IHC discharge across IHC duration groups.Results We observed a reduction in ED visits during IHC. IHC was significantly associated with a reduction in ED visits in the long and short IHC duration groups. A non-significant reduction in ED visits was observed in the intermediate IHC duration group. A 90% reduction in ED visits during IHC and a 45% reduction after IHC was observed in the short IHC duration group. Corresponding reductions were 17% and 64% during and after IHC, respectively, in the long IHC duration group.Conclusion IHC was effective in reducing ED visits, but expansion of IHC to include additional necessary services could further reduce ED visits. Investment in the creation of a structured, effective network of engaged professionals (including community care services and hospitals) is crucial to achieving this.

Abstract Image texture analysis (radiomics) uses radiographic images to quantify characteristics that may identify tumour heterogeneity and associated patient outcomes. Using fluoro‐deoxy‐glucose positron emission tomography/computed tomography (FDG‐PET/CT)‐derived data, including quantitative metrics, image texture analysis and other clinical risk factors, we aimed to develop a prognostic model that predicts survival in patients with previously untreated diffuse large B‐cell lymphoma (DLBCL) from GOYA (NCT01287741). Image texture features and clinical risk factors were combined into a random forest model and compared with the international prognostic index (IPI) for DLBCL based on progression‐free survival (PFS) and overall survival (OS) predictions. Baseline FDG‐PET scans were available for 1263 patients, 832 patients of these were cell‐of‐origin (COO)‐evaluable. Patients were stratified by IPI or radiomics features plus clinical risk factors into low‐, intermediate‐ and high‐risk groups. The random forest model with COO subgroups identified a clearer high‐risk population (45% 2‐year PFS [95% confidence interval (CI) 40%–52%]; 65% 2‐year OS [95% CI 59%–71%]) than the IPI (58% 2‐year PFS [95% CI 50%–67%]; 69% 2‐year OS [95% CI 62%–77%]). This study confirms that standard clinical risk factors can be combined with PET‐derived image texture features to provide an improved prognostic model predicting survival in untreated DLBCL.

Adolescence is a critical period for engaging in health risk behaviors. Migrant adolescents may face unique challenges due to acculturation stress. This study aims to monitor substance use and problem gambling among migrant adolescents living in Italy. Data from the 2017/18 Health Behavior in School-Aged Children survey in Italy were analyzed. The 18,794 participants included 15-year-olds, categorized as native or migrants, with ethnic backgrounds from Western, Eastern European, or non-Western/non-European countries. Girls had higher smoking rates, while boys exhibited higher prevalence of alcohol-related risk behaviors, cannabis use, and gambling. Boys from Eastern European countries displayed a greater risk of drunkenness (OR: 1.58, 95% CI: 1.06–2.37), particularly in the first generation, while those from Western countries showed a higher risk of multiple substance use (OR: 1.44, 95% CI: 1.05–1.96). Girls from Eastern European and non-Western/non-European countries had a lower risk of alcohol consumption (OR: 0.50, 95% CI: 0.29–0.85; OR: 0.55, 95% CI: 0.33–0.91, respectively). Finally, boys, especially those from Eastern European and non-Western/non-European countries, had a significantly higher risk of problem gambling (OR: 1.83, 95% CI: 1.04–3.22; OR: 2.10, 95% CI: 1.29–3.42, respectively). This disparity was more pronounced in the first generation, possibly due to acculturation challenges and socio-economic factors. Risk behaviors in adolescents are influenced by complex interplays of gender, cultural factors, and migration generation. Preventive strategies should consider these factors to effectively address substance use and gambling in this heterogeneous population.

Summary: Background: There are concerns that suicidal behaviors are arising among adolescents. The COVID-19 pandemic could have worsened the picture, however, studies on this topic reported contrasting results. This work aimed to summarise findings from the worldwide emerging literature on the rates of suicidality among young people during the COVID-19 pandemic. Methods: A systematic review and meta-analysis were performed, searching five electronic databases for studies published from January 1, 2020 until July 27, 2022. Studies reporting rates for each of the three considered outcomes (suicide, suicidal behaviors, and suicidal ideation) among young people under 19 years old during the COVID-19 pandemic were included. Random-effects meta-analyses were conducted, and the intra-study risk of bias was assessed. When pre-COVID-19 data were available, incidence rate ratio (IRR) and prevalence ratio (PR) estimates were calculated between the two periods. All the analyses were performed according to the setting explored: general population, emergency department (ED), and psychiatric services. The review protocol was registered on PROSPERO (CRD42022308014). Findings: Forty-seven observational studies were selected for more than 65 million subjects. The results of the meta-analysis showed a pooled annual incidence rate of suicides of 4.9 cases/100,000 during 2020, accounting for a non-statistically significant increase of 10% compared to 2019 (IRR 1.10, 95% CI: 0.94–1.29). The suicidal behaviors pooled prevalence during the COVID-19 pandemic was higher in the psychiatric setting (25%; 95% CI: 17–36%) than in the general population (3%; 1–13%) and ED (1%; 0–9%). The pooled rate of suicidal ideation was 17% in the general population (11–25%), 36% in psychiatric setting (20–56%) and 2% in ED (0–12%). The heterogeneity level was over 97% for both outcomes in all settings considered. The comparison between before and during COVID-19 periods highlighted a non-statistically significant upward trend in suicidal behaviors among the general population and in ED setting. The only significant increase was found for suicidal ideation in psychiatric setting among studies conducted in 2021 (PR 1.15; 95% CI: 1.04–1.27), not observed exploring 2020 alone. Interpretation: During the pandemic, suicide spectrum issues seemed to follow the known pattern described in previous studies, with higher rates of suicidal ideation than of suicidal behaviors and suicide events. Governments and other stakeholders should be mindful that youth may have unique risks at the outset of large disasters like the COVID-19 pandemic and proactive steps are necessary to address the needs of youth to mitigate those risks. Funding: The present study was funded by the University of Torino (CHAL_RILO_21_01).

IntroductionAn excess in the daily fluctuation of COVID-19 in hospital admissions could cause uncertainty and delays in the implementation of care interventions. This study aims to characterize a possible source of extravariability in the number of hospitalizations for COVID-19 by considering age at admission as a potential explanatory factor. Age at hospitalization provides a clear idea of the epidemiological impact of the disease, as the elderly population is more at risk of severe COVID-19 outcomes. Administrative data for the Veneto region, Northern Italy from February 1, 2020, to November 20, 2021, were considered.MethodsAn inferential approach based on quasi-likelihood estimates through the generalized estimation equation (GEE) Poisson link function was used to quantify the overdispersion. The daily variation in the number of hospitalizations in the Veneto region that lagged at 3, 7, 10, and 15 days was associated with the number of news items retrieved from Global Database of Events, Language, and Tone (GDELT) regarding containment interventions to determine whether the magnitude of the past variation in daily hospitalizations could impact the number of preventive policies.ResultsThis study demonstrated a significant increase in the pattern of hospitalizations for COVID-19 in Veneto beginning in December 2020. Age at admission affected the excess variability in the number of admissions. This effect increased as age increased. Specifically, the dispersion was significantly lower in people under 30 years of age. From an epidemiological point of view, controlling the overdispersion of hospitalizations and the variables characterizing this phenomenon is crucial. In this context, the policies should prevent the spread of the virus in particular in the elderly, as the uncontrolled diffusion in this age group would result in an extra variability in daily hospitalizations.DiscussionThis study demonstrated that the overdispersion, together with the increase in hospitalizations, results in a lagged inflation of the containment policies. However, all these interventions represent strategies designed to contain a mechanism that has already been triggered. Further efforts should be directed toward preventive policies aimed at protecting the most fragile subjects, such as the elderly. Therefore, it is essential to implement containment strategies before the occurrence of potentially out-of-control situations, resulting in congestion in hospitals and health services.

Objective In the past 2 years, the number of scientific publications has grown exponentially. The COVID-19 outbreak hugely contributed to this dramatic increase in the volume of published research. Currently, text mining of the volume of SARS-CoV-2 and COVID-19 publications is limited to the first months of the outbreak. We aim to identify the major topics in COVID-19 literature collected from several citational sources and analyze the temporal trend from November 2019 to December 2021. Methods We performed an extensive literature search on SARS-Cov-2 and COVID-19 publications on PubMed, Scopus, and Web of Science (WoS) and a structural topic modelling on the retrieved abstracts. The temporal trend of the recognized topics was analyzed. Furthermore, a comparison between our corpus and the COVID-19 Open Research Dataset (CORD-19) repository was performed. Results We collected 269,186 publications and identified 10 topics. The most popular topic was related to the clinical pictures of the COVID-19 outbreak, which has a constant trend, and the least popular includes studies on COVID-19 literature and databases. “Telemedicine”, “Vaccine development”, and “Epidemiology” were popular topics in the early phase of the pandemic; increasing topics in the last period are “COVID-19 impact on mental health”, “Forecasting”, and “Molecular Biology”. “Education” was the second most popular topic, which emerged in September 2020. Conclusions We identified 10 topics for classifying COVID-19 research publications and estimated a nonlinear temporal trend that gives an overview of their unfolding over time. Several citational databases must be searched to retrieve a complete set of studies despite the efforts to build repositories for COVID-19 literature. Our collected data can help build a more focused literature search between November 2019 and December 2021 when carrying out systematic and rapid reviews and our findings can give a complete picture on the topic.

The COVID-19 outbreak involved a spread of prediction efforts, especially in the early pandemic phase. A better understanding of the epidemiological implications of the different models seems crucial for tailoring prevention policies. This study aims to explore the concordance and discrepancies in outbreak prediction produced by models implemented and used in the first wave of the epidemic. To evaluate the performance of the model, an analysis was carried out on Italian pandemic data from February 24, 2020. The epidemic models were fitted to data collected at 20, 30, 40, 50, 60, 70, 80, 90, and 98 days (the entire time series). At each time step, we made predictions until May 31, 2020. The Mean Absolute Error (MAE) and the Mean Absolute Percentage Error (MAPE) were calculated. The GAM model is the most suitable parameterization for predicting the number of new cases; exponential or Poisson models help predict the cumulative number of cases. When the goal is to predict the epidemic peak, GAM, ARIMA, or Bayesian models are preferable. However, the prediction of the pandemic peak could be made carefully during the early stages of the epidemic because the forecast is affected by high uncertainty and may very likely produce the wrong results.

Abstract Background Transferring results obtained in cardiovascular outcome trials (CVOTs) to the real-world setting is challenging. We herein transposed CVOT results to the population of patients with type 2 diabetes (T2D) seen in routine clinical practice and who may receive the medications tested in CVOTs. Methods We implemented the post-stratification approach based on aggregate data of CVOTs and individual data of a target population of diabetic outpatients. We used stratum-specific estimates available from CVOTs to calculate expected effect size for the target population by weighting the average of the stratum-specific treatment effects according to proportions of a given characteristic in the target population. Data are presented as hazard ratio (HR) and 95% confidence intervals. Results Compared to the target population (n = 139,708), the CVOT population (n = 95,816) was younger and had a two to threefold greater prevalence of cardiovascular disease. EMPA-REG was the CVOT with the largest variety of details on stratum-specific effects, followed by TECOS, whereas DECLARE and PIONEER-6 had more limited stratum-specific information. The post-stratification HR estimate for 3 point major adverse cardiovascular event (MACE) based on EMPA-REG was 0.88 (0.74–1.03) in the target population, compared to 0.86 (0.74–0.99) in the trial. The HR estimate based on LEADER was 0.88 (0.77–0.99) in the target population compared to 0.87 (0.78–0.97) in the trial. Consistent results were obtained for SUSTAIN-6, EXSCEL, PIONEER-6 and DECLARE. The effect of DPP-4 inhibitors observed in CVOTs remained neutral in the target population. Conclusions Based on CVOT stratum-specific effects, cardiovascular protective actions of glucose lowering medications tested in CVOTs are transferrable to a much different real-world population of patients with T2D.

Abstract Background Italy has been the first European country to be affected by the COVID-19 epidemic which started out at the end of February. In this report, we focus our attention on the Veneto Region, in the North-East of Italy, which is one of the areas that were first affected by the rapid spread of SARS-CoV-2. We aim to evaluate the trend of all-cause mortality and to give a description of the characteristics of the studied population. Methods Data used in the analyses were released by the majority of municipalities and cover the 93% of the total population living in the Veneto Region. We evaluated the trend of overall mortality from Jan.01 to Jun.30. 2020. Moreover we compared the COVID-19-related deaths to the overall deaths. Results From March 2020, the overall mortality rate increased exponentially, affecting males and people aged > 76 the most. The confirmed COVID-19-related death rate in the Veneto region between Mar.01 and Apr.302020 is 30 per 100,000 inhabitants. In contrast, the all-cause mortality increase registered in the same months in the municipalities included in the study is 219 per 100,000 inhabitants. Conclusions COVID-19 has a primary role in the increase in mortality but does not entirely explain such a high number of deaths. Strategies need to be developed to reduce this gap in case of future waves of the pandemic.

Machine learning is usually associated with big data; however, experimental or clinical data are usually limited in size. The aim of this study was to describe how supervised machine learning can be used to classify astrocytes from a small sample into different morphological classes. Our dataset was composed of only 193 cells, with unbalanced morphological classes and missing observations. We combined classification trees and ensemble algorithms (boosting and bagging) with under sampling to classify the nuclear morphology (homogeneous, dotted, wrinkled, forming crumples, and forming micronuclei) of astrocytes stained with anti-LMNB1 antibody. Accuracy, sensitivity (recall), specificity, and F1 score were assessed with bootstrapping, leave one-out (LOOCV) and stratified cross-validation. We found that our algorithm performed at rates above chance in predicting the morphological classes of astrocytes based on the nuclear expression of LMNB1. Boosting algorithms (tree ensemble) yielded better classifications over bagging ones (tree bagger). Moreover leave-one-out and bootstrapping yielded better predictions than the more commonly used k-fold cross-validation. Finally, we could identify four important predictors: the intensity of LMNB1 expression, nuclear area, cellular area, and soma area. Our results show that a tree ensemble can be optimized, in order to classify morphological data from a small sample, even in the presence of highly unbalanced classes and numerous missing data.

INTRODUCCIÓN: Los premolares inferiores son conocidos por la naturaleza compleja de la configuración de sus conductos. Generalmente cuando presentan uno solo es estrecho y acintado. En la actualidad contamos con herramientas de diagnóstico más precisas como las Tomografías Computadas de Haz Cónico para evaluar la morfología de los conductos en los tres planos del espacio. OBJETIVO: Es estudiar la sección transversal de los conductos de premolares inferiores humanos, con un solo conducto radicular. MATERIAL Y MÉTODO: Fueron estudiados 120 premolares inferiores humanos extraídos. Los especímenes fueron estudiados por medio de CBCT, con un tomógrafo Carestream 8200. Del total de la muestra, se seleccionaron a través de las CBCT, sólo los premolares con un conducto. Los mismos fueron analizados en cortes perpendiculares al eje largo del diente (axiales) En cada pieza dentaria se midió el diámetro en sentido bucolingual y mesiodistal del conducto (expresado en milímetros) en los tres tercios: cervical, medio y apical. Posteriormente, se analizó la morfología del conducto en los cortes axiales, en los tres tercios antes mencionados, clasificándolos en: circulares, ovales, ovalesalargados y acintados. Las variables cuantitativas fueron representadas en tablas mediante promedio y desvío, mientras que las cualitativas con frecuencias y porcentajes. Se realizaron pruebas de Friedman y prueba de uniformidad chi cuadrado. Se utilizaron los soft RMedic e Infostat. En todos los casos el nivel de significación fue del 5%. RESULTADOS: El 1,22% de los casos presentaron un conducto circular y 4,88 % ovalado en todo su recorrido. El 93,9% de la muestra presentó diferentes morfologías en los 3 tercios del conducto: LCC en 21.95%, seguida por ACC con un 20.73% y OCC con un 10,98%. Se observó un predominio de conductos circulares en el 84% en el tercio apical y 56% en el medio; ovalados en tercio medio en un 31,71% y aplanados en el tercio cervical en un 37.8%. El diámetro promedio del conducto circular a 3 mm del ápice fue de 0,55 mm2. En cervical el promedio de diámetro mayor fue de 2.58 mm en BL y 0.83 mm en MD y en tercio medio 1,29 mm en BL y 0.82 mm en MD. CONCLUSIONES: Los premolares inferiores con un solo conducto presentaron diferentes morfologías en los tres tercios del conducto. El predominio de la anatomía fue Alargada o Aplanada en el tercio Cervical (37.80%) y predominio de Circulares en Medio (56.10%) y Apical (84.15%). Este tipo de conductos, que varían su morfología longitudinalmente, pueden ser un verdadero desafío para su instrumentación, irrigación y obturación.

Objectives The present work aims to present the results of the ‘PRESTOinsieme’ (which is ‘we will be together soon’ in English). The web-based survey (www.prestoinsieme.com) describes changes in lifestyle habits and symptoms of psychological discomfort in the Italian population during the COVID-19 lockdown.Design Cross-sectional online survey disseminated by messaging apps (ie, WhatsApp and Telegram) and social networks (ie, Instagram, Facebook and LinkedIn).Setting Italy.Participants Italian population older than 16 years of age.Exposure COVID-19 lockdown.Main outcomes and measures Survey respondents filled out a set of validated questionnaires aimed at assessing lifestyle habits and psychological health, that is, the General Health Questionnaire (GHQ-12) to screen for psychological distress, the Impact of Event Scale-Revised (IES-R) to screen for post-traumatic stress and the Center for Epidemiologic Studies Depression Scale (CES-D).Results Survey respondents totalled 5008. Moderate or severe psychological distress was reported in 25.5% and 22% of survey respondents, respectively. Lower age, female gender, being unemployed (OR 1.57, 95% CI 1.22 to 2.02) or being a student (OR 1.73, 95% CI 1.31 to 2.28) were predictors of more severe depressive symptoms.Conclusions The present study is one of the largest population-based surveys conducted in Italy during the first COVID-19 lockdown, providing valuable data about the Italian population’s psychological health. Further studies should be conducted to understand whether psychological distress persists after the end of the lockdown.

Abstract Background The growing number of medical literature and textual data in online repositories led to an exponential increase in the workload of researchers involved in citation screening for systematic reviews. This work aims to combine machine learning techniques and data preprocessing for class imbalance to identify the outperforming strategy to screen articles in PubMed for inclusion in systematic reviews. Methods We trained four binary text classifiers (support vector machines, k-nearest neighbor, random forest, and elastic-net regularized generalized linear models) in combination with four techniques for class imbalance: random undersampling and oversampling with 50:50 and 35:65 positive to negative class ratios and none as a benchmark. We used textual data of 14 systematic reviews as case studies. Difference between cross-validated area under the receiver operating characteristic curve (AUC-ROC) for machine learning techniques with and without preprocessing (delta AUC) was estimated within each systematic review, separately for each classifier. Meta-analytic fixed-effect models were used to pool delta AUCs separately by classifier and strategy. Results Cross-validated AUC-ROC for machine learning techniques (excluding k-nearest neighbor) without preprocessing was prevalently above 90%. Except for k-nearest neighbor, machine learning techniques achieved the best improvement in conjunction with random oversampling 50:50 and random undersampling 35:65. Conclusions Resampling techniques slightly improved the performance of the investigated machine learning techniques. From a computational perspective, random undersampling 35:65 may be preferred.

(1) Background: In Italy, the components of adolescents’ mental well-being (psychological symptomatology and cognitive perception of life satisfaction) showed different temporal trends, suggesting the adoption of a multidimensional conceptualization. We aimed to assess temporal patterns and provide additional insights into Italian adolescents’ mental well-being in the last decade by adopting the Dual Factor Model; (2) Methods: We used nationally representative samples of Italian students (n = 165,000) aged 11, 13, and 15 years across the three more recent Italian Health Behaviour in School-aged Children (HBSC) surveys. Two measures of mental well-being were used: life satisfaction (LS, indicator of positive subjective well-being) and psychological health complaints (PHC, indicator of mental illness); (3) Results: Our study showed that the overall sample has been moving from a Complete Mental Health (Flourishing) to an Incomplete Mental Illness (Struggling) condition. Among 13- and 15-year-old girls, a jump from one to the other mental condition was observed in the 2014–2018 and 2010–2014 time periods, respectively; (4) Conclusions: Our findings suggest that Italian adolescents, especially older girls, have been shifting from Complete Mental Health to Incomplete Mental Illness in the last decade. Further research is needed to investigate this breaking up of the connection between psychological symptomatology and cognitive perception of life satisfaction.

Patients are the most important actors in clinical research. Therefore, patient preference information (PPI) could support the decision-making process, being indisputable for research value, quality, and integrity. However, there is a lack of clear guidance or consensus on the search for preference studies. In this blueprint, an openly available and regularly updated patient preference management system for an integrated database (PPMSDB) that contains the minimal set of data sufficient to provide detailed information for each study (the so-called evidence tables in systematic reviews) and a high-level overview of the findings of a review (summary tables) is described. These tables could help determine which studies, if any, are eligible for quantitative synthesis. Finally, a web platform would provide a graphical and user-friendly interface. On the other hand, a set of APIs (application programming interfaces) would also be developed and provided. The PPMSDB, aims to collect preference measures, characteristics, and meta-data, and allow researchers to obtain a quick overview of a research field, use the latest evidence, and identify research gaps. In conjunction with proper statistical analysis of quantitative preference measures, these aspects can facilitate formal evidence-based decisions and adequate consideration when conducting a structured decision-making process. Our objective is to outline the conceptual infrastructure necessary to build and maintain a successful network that can monitor the currentness and validity of evidence.

Background: In recent years, eye movement desensitization and reprocessing (EMDR) has been applied to different psychiatric conditions beyond post-traumatic stress disorder (PTSD), and an increasing number of studies have evaluated its effect on depression. To date, no quantitative synthesis of the efficacy of EMDR on depression has been conducted. Objective: To meta-analytically review the studies on EMDR for depression as the primary target for treatment. Method: Studies with a controlled design evaluating the effect of EMDR on depression were searched on six electronic databases (PubMed, Embase, CINAHL, PsycINFO, Cochrane database, and Francine Shapiro Library) and then selected by two independent reviewers. A systematic review and meta-analysis was conducted. Results: Eleven studies were included for qualitative synthesis. Nine studies were included in the meta-analysis, involving 373 participants. The overall effect size of EMDR for depressive symptoms is large (n = 9, Hedges’ g = – 1.07; 95%CI [–1.66; – 0.48]), with high heterogeneity (I2 = 84%), and corresponds to a ‘number needed to treat’ of 1.8. At follow-up (range 3–6 months), the effect remains significant but moderate (n = 3, Hedges’ g = – 0.62; 95%CI [–0.97; – 0.28]; I2 = 0%). The effect of EMDR compared with active controls is also moderate (n = 7, g = – 0.68; 95%CI [–0.92; – 0.43]; I2 = 0%). No publication bias was found, although the results are limited by the small number and poor methodological quality of the included studies. Conclusions: Review findings suggest that EMDR may be considered an effective treatment for improving symptoms of depression, with effects comparable to other active treatments. However, findings need to be interpreted in light of the limited number of the studies and their quality. Further research is required to understand the longer-term of effects EMDR in treating depression and preventing depression relapse. Protocol registration: PROSPERO (CRD42018090086).