Oncological pediatric early warning score: a dedicated tool to predict patient's clinical deterioration and need for pediatric intensive care treatment.

Pediatric oncohematological patients frequently require PICU admission during their clinical history. The O-PEWS is a specific score developed to predict the need for PICU admission of oncohematological children. This study aimed at i) describing the trend of the O-PEWS in a cohort of patients hospitalized in the Pediatric Oncohematology ward and transferred to the PICU of Padua University Hospital, measured at different time-points in the 24 hours before PICU admission and to evaluate its association with mortality and presence of organ failure; ii) investigating the association between the recorded O-PEWS, and PIM3, number of organ failure and the need for ventilation, dialysis and inotropes.This retrospective single-center study enrolled oncohematological children admitted to the PICU between 2017 and 2021. The O-PEWS, ranging between 0 and 15, was calculated on the available medical records and the TIPNet-Network database at 24 (T-24), 12 (T-12), 6 (T-6) and 0 (T0) hours before PICU admission.RESULTS: 101 PICU admissions, related to 80 children, were registered. During the 24 hours prior to PICU admission, the O-PEWS progressively increased in all the patients. At T-24 the median O-PEWS was 3 (IQR 1-5), increasing to a median value of 6 (IQR 4-8) at T0. The O-PEWS was positively associated with mortality, organ failure and the need for ventilation at all the analyzed time-points and with the need for dialysis at T-6.The O-PEWS appears as a useful tool for predicting early clinical deterioration in oncohematological patients and for anticipating the initiation of life-support treatments.

Information extraction from medical case reports using OpenAI InstructGPT.

BACKGROUND AND OBJECTIVE: Researchers commonly use automated solutions such as Natural Language Processing (NLP) systems to extract clinical information from large volumes of unstructured data. However, clinical text's poor semantic structure and domain-specific vocabulary can make it challenging to develop a one-size-fits-all solution. Large Language Models (LLMs), such as OpenAI's Generative Pre-Trained Transformer 3 (GPT-3), offer a promising solution for capturing and standardizing unstructured clinical information. This study evaluated the performance of InstructGPT, a family of models derived from LLM GPT-3, to extract relevant patient information from medical case reports and discussed the advantages and disadvantages of LLMs versus dedicated NLP methods. METHODS: In this paper, 208 articles related to case reports of foreign body injuries in children were identified by searching PubMed, Scopus, and Web of Science. A reviewer manually extracted information on sex, age, the object that caused the injury, and the injured body part for each patient to build a gold standard to compare the performance of InstructGPT. RESULTS: InstructGPT achieved high accuracy in classifying the sex, age, object and body part involved in the injury, with 94%, 82%, 94% and 89%, respectively. When excluding articles for which InstructGPT could not retrieve any information, the accuracy for determining the child's sex and age improved to 97%, and the accuracy for identifying the injured body part improved to 93%. InstructGPT was also able to extract information from non-English language articles. CONCLUSIONS: The study highlights that LLMs have the potential to eliminate the necessity for task-specific training (zero-shot extraction), allowing the retrieval of clinical information from unstructured natural language text, particularly from published scientific literature like case reports, by directly utilizing the PDF file of the article without any pre-processing and without requiring any technical expertise in NLP or Machine Learning. The diverse nature of the corpus, which includes articles written in languages other than English, some of which contain a wide range of clinical details while others lack information, adds to the strength of the study.

Can we predict adolescent cannabis use? A Bayesian semi-parametric approach to project future trends.

Despite its decrease in many Western countries, cannabis remains the most used illicit substance among adolescents. This study aims to summarize cannabis consumption during the last two decades and project trends among 15-year-olds in the 2021-22 HBSC survey. A Bayesian semi-parametric hierarchical model was adopted to estimate the trend of cannabis consumption using data of about 287,000 adolescents from the 2001/2002 to the 2017/2018 HBSC wave and the 38 countries that met the inclusion criteria. Data show an overall decline in most countries for both boys and girls. However, in 22 countries of 38 cannabis use is expected to increase again in our projection. The discussion of these findings should take into account cultural, policy, social factors and unpredictable events such as the Covid-19 pandemic, that can significantly impact future trends leading to discrepancies between the projected and observed values. However, these discrepancies can provide insight into understanding the potential impact of preventive strategies and the underlying processes responsible for changes in cannabis use over time.

Effectiveness of interventions to increase healthcare workers' adherence to vaccination against vaccine-preventable diseases: a systematic review and meta-analysis, 1993 to 2022.

BackgroundVaccination adherence among healthcare workers (HCWs) is fundamental for the prevention of vaccine-preventable diseases (VPDs) in healthcare. This safeguards HCWs' well-being, prevents transmission of infections to vulnerable patients and contributes to public health.AimThis systematic review and meta-analysis aimed to describe interventions meant to increase HCWs' adherence to vaccination and estimate the effectiveness of these interventions.MethodsWe searched literature in eight databases and performed manual searches in relevant journals and the reference lists of retrieved articles. The study population included any HCW with potential occupational exposure to VPDs. We included experimental and quasi-experimental studies presenting interventions aimed at increasing HCWs' adherence to vaccination against VPDs. The post-intervention vaccination adherence rate was set as the main outcome. We included the effect of interventions in the random-effects and subgroup meta-analyses.ResultsThe systematic review considered 48 studies on influenza and Tdap vaccination from database and manual searches, and 43 were meta-analysed. A statistically significant, positive effect was seen in multi-component interventions in randomised controlled trials (relative risk (RR) = 1.37; 95% CI: 1.13-1.66) and in observational studies (RR = 1.43; 95% CI: 1.29-1.58). Vaccination adherence rate was higher in community care facilities (RR = 1.58; 95% CI: 1.49-1.68) than in hospitals (RR = 1.24; 95% CI: 0.76-2.05).ConclusionInterventions aimed at increasing HCWs' adherence to vaccination against VPDs are effective, especially multi-component ones. Future research should determine the most effective framework of interventions for each setting, using appropriate study design for their evaluation, and should compare intervention components to understand their contribution to the effectiveness.

Impact of the first 24 h of continuous kidney replacement therapy on hemodynamics, ventilation, and analgo-sedation in critically ill children.

BACKGROUND: In a group of children admitted to the paediatric intensive care unit (PICU) receiving continuous kidney replacement therapy (CKRT), we aim to evaluate the data about their hemodynamic, ventilation and analgo-sedation profile in the first 24 h of treatment and possible associations with mortality. METHODS: Retrospective cohort study of children admitted to the PICU of the University Hospital of Padova undergoing CKRT between January 2011 and March 2021. Data was collected at baseline (T0), after 1 h (T1) and 24 h (T24) of CKRT treatment. The differences in outcome measures were compared between these time points, and between survivors and non-survivors. RESULTS: Sixty-nine patients received CKRT, of whom 38 (55%) died during the PICU stay. Overall, the vasoactive inotropic score and the adrenaline dose increased at T1 compared to T0 (p = 0.012 and p = 0.022, respectively). Compared to T0, at T24 patients showed an improvement in the following ventilatory parameters: Oxygenation Index (p = 0.005), Oxygenation Saturation Index (p = 0.013) PaO2/FiO2 ratio (p = 0.005), SpO2/FiO2 ratio (p = 0.002) and Mean Airway Pressure (p = 0.016). These improvements remained significant in survivors (p = 0.01, p = 0.027, p = 0.01 and p = 0.015, respectively) but not in non-survivors. No changes in analgo-sedative drugs have been described. CONCLUSIONS: CKRT showed a significant impact on hemodynamics and ventilation in the first 24 h of treatment. We observed a significant rise in the inotropic/vasoactive support required after 1 h of treatment in the overall population, and an improvement in the ventilation parameters at 24 h only in survivors.

A focus on adolescent substance use in Europe, central Asia and Canada. Health Behaviour in School-aged Children international report from the 2021/2022 survey. Volume 3

The Health Behaviour in School-aged Children (HBSC) study is a large school-based survey carried out every four years in collaboration with the WHO Regional Office for Europe. HBSC data are used at national/regional and international levels to gain new insights into adolescent health and well-being, understand the social determinants of health and inform policy and practice to improve young people’s lives. The 2021/2022 HBSC survey data are accompanied by a series of volumes that summarize the key findings around specific health topics. This report, Volume 3 in the series, focuses on adolescent substance use, using the unique HBSC evidence on adolescents aged 11, 13 and 15 years across 44 countries and regions in Europe, central Asia and Canada. It describes the status of adolescent substance use (cigarette smoking, electronic cigarette use, alcohol consumption, drunkenness and cannabis use), the role of gender, age and social inequality, and how adolescent substance use has changed over time. Findings from the 2021/2022 HBSC survey provide an important evidence benchmark for current research, intervention and policy-planning.

Risk Behaviors among Migrant Adolescents in Italy.

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.

Distinct clinical phenotypes in paediatric cancer patients with sepsis are associated with different outcomes-an international multicentre retrospective study.

Background: Identifying phenotypes in sepsis patients may enable precision medicine approaches. However, the generalisability of these phenotypes to specific patient populations is unclear. Given that paediatric cancer patients with sepsis have different host response and pathogen profiles and higher mortality rates when compared to non-cancer patients, we determined whether unique, reproducible, and clinically-relevant sepsis phenotypes exist in this specific patient population. Methods: We studied patients with underlying malignancies admitted with sepsis to one of 25 paediatric intensive care units (PICUs) participating in two large, multi-centre, observational cohorts from the European SCOTER study (n = 383 patients; study period between January 1, 2018 and January 1, 2020) and the U.S. Novel Data-Driven Sepsis Phenotypes in Children study (n = 1898 patients; study period between January 1, 2012 and January 1, 2018). We independently used latent class analysis (LCA) in both cohorts to identify phenotypes using demographic, clinical, and laboratory data from the first 24 h of PICU admission. We then tested the association of the phenotypes with clinical outcomes in both cohorts. Findings: LCA identified two distinct phenotypes that were comparable across both cohorts. Phenotype 1 was characterised by lower serum bicarbonate and albumin, markedly increased lactate and hepatic, renal, and coagulation abnormalities when compared to phenotype 2. Patients with phenotype 1 had a higher 90-day mortality (European cohort 29.2% versus 13.4%, U.S. cohort 27.3% versus 11.4%, p < 0.001) and received more vasopressor and renal replacement therapy than patients with phenotype 2. After adjusting for severity of organ dysfunction, haematological cancer, prior stem cell transplantation and age, phenotype 1 was associated with an adjusted OR of death at 90-day of 1.9 (1.04-3.34) in the European cohort and 1.6 (1.2-2.2) in the U.S. cohort. Interpretation: We identified two clinically-relevant sepsis phenotypes in paediatric cancer patients that are reproducible across two international, multicentre cohorts with prognostic implications. These results may guide further research regarding therapeutic approaches for these specific phenotypes. Funding: Part of this study is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Automatic Forecast of Intensive Care Unit Admissions: The Experience During the COVID-19 Pandemic in Italy.

The experience of the COVID-19 pandemic showed the importance of timely monitoring of admissions to the ICU admissions. The ability to promptly forecast the epidemic impact on the occupancy of beds in the ICU is a key issue for adequate management of the health care system.Despite this, most of the literature on predictive COVID-19 models in Italy has focused on predicting the number of infections, leaving trends in ordinary hospitalizations and ICU occupancies in the background.This work aims to present an ETS approach (Exponential Smoothing Time Series) time series forecasting tool for admissions to the ICU admissions based on ETS models. The results of the forecasting model are presented for the regions most affected by the epidemic, such as Veneto, Lombardy, Emilia-Romagna, and Piedmont.The mean absolute percentage errors (MAPE) between observed and predicted admissions to the ICU admissions remain lower than 11% for all considered geographical areas.In this epidemiological context, the proposed ETS forecasting model could be suitable to monitor, in a timely manner, the impact of COVID-19 disease on the health care system, not only during the early stages of the pandemic but also during the vaccination campaign, to quickly adapt possible preventive interventions.

A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials.

Background: Randomized Clinical Trials (RCT) represent the gold standard among scientific evidence. RCTs are tailored to control selection bias and the confounding effect of baseline characteristics on the effect of treatment. However, trial conduction and enrolment procedures could be challenging, especially for rare diseases and paediatric research. In these research frameworks, the treatment effect estimation could be compromised. A potential countermeasure is to develop predictive models on the probability of the baseline disease based on previously collected observational data. Machine learning (ML) algorithms have recently become attractive in clinical research because of their flexibility and improved performance compared to standard statistical methods in developing predictive models. Objective: This manuscript proposes an ML-enforced treatment effect estimation procedure based on an ensemble SuperLearner (SL) approach, trained on historical observational data, to control the confounding effect. Methods: The REnal SCarring Urinary infEction trial served as a motivating example. Historical observational study data have been simulated through 10,000 Monte Carlo (MC) runs. Hypothetical RCTs have been also simulated, for each MC run, assuming different treatment effects of antibiotics combined with steroids. For each MC simulation, the SL tool has been applied to the simulated observational data. Furthermore, the average treatment effect (ATE), has been estimated on the trial data and adjusted for the SL predicted probability of renal scar. Results: The simulation results revealed an increased power in ATE estimation for the SL-enforced estimation compared to the unadjusted estimates for all the algorithms composing the ensemble SL.

Fitting Early Phases of the COVID-19 Outbreak: A Comparison of the Performances of Used Models.

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.

Italian pediatric intensive care units admitting critically ill cancer children: results from a national survey.

BACKGROUND: Pediatric patients affected by oncologic disease have a significant risk of clinical deterioration that requires admission to the intensive care unit. This study reported the results of a national survey describing the characteristics of Italian onco-hematological units (OHUs) and pediatric intensive care units (PICUs) that admit pediatric patients, focusing on the high-complexity treatments available before PICU admission, and evaluating the approach to the end-of-life (EOL) when cared in a PICU setting. METHODS: A web-based electronic survey has been performed in April 2021, involving all Italian PICUs admitting pediatric patients with cancer participating in the study. RESULTS: Eighteen PICUs participated, with a median number of admissions per year of 350 (IQR 248-495). Availability of Extracorporeal Membrane Oxygenation therapy and the presence of intermediate care unit are the only statistically different characteristics between large or small PICUs. Different high-level treatments and protocols are performed in OHUs, non depending on the volume of PICU. Palliative sedation is mainly performed in the OHUs (78%), however, in 72% it is also performed in the PICU. In most centers protocols that address EOL comfort care and treatment algorithms are missing, non depending on PICU or OHU volume. CONCLUSIONS: A non-homogeneous availability of high-level treatments and in OHUs is described. Moreover, protocols addressing EOL comfort care and treatment algorithms in palliative care are lacking in many centers.

Knowledge assessment among subjects with chronic venous leg ulcer in outpatient setting: Translation and adaptation of a tool to identify subjects at risk of poor understanding.

Promotion of self-care is an important issue in the treatment of chronic diseases such as venous leg ulcers, as adequate self-care can prevent complications and ulcer recurrence. However, only a few tools have been developed and tested to assess the knowledge of patients with venous leg ulcers. This study aimed to translate, adapt and validate in an Italian language and context a questionnaire to assess the knowledge of patients with venous leg ulcers about their disease (pathophysiology, risk factors, lifestyle changes due to ulcer) and the proper management of the ulcer to prevent recurrence. This is a cross-sectional study divided into two phases: (1) translation and cross-cultural adaptation of the 'Educational Interventions in Venous Leg Ulcer Patients' tool in a six-stage process and (2) validation and reliability study with patients with active ulceration. There was great agreement for the English-to-Italian translation. In content validation, the tool showed good applicability among experts. Adjustments were made to improve semantic equivalence, and the questionnaire was made to be easy and quick to administer. The results of the target population showed a low level of knowledge among the patients. Knowing the deficiencies of the patients makes it possible to create educational projects to improve their abilities. Now more than ever, it is necessary to improve self-care and patient knowledge, allowing home care, improving autonomy, and avoiding hospital care that results in higher costs and risks. This questionnaire could be used in future studies to identify topics that need to be reinforced through education and to improve the awareness and self-care of these patients.

Who Stays, Who Moves on and the Host Population: A Picture of Adolescents' Perceived Well-Being and Risk Behaviours.

The study aims to evaluate the health profile of first- and second-generation Romanian immigrants living in Italy compared to their adolescent peers in the country of origin (Romania) and the host population (Italian-borns). Analyses were performed on the 2013/2014 Health Behaviour in School-aged Children (HBSC) survey data. Romanian natives showed lower levels of health complaints and higher life satisfaction than Romanian migrants, who were similar to the host population, especially the second-generation ones. A comparable prevalence of being bullied was registered among Romanians, both native and immigrant, with significantly lower levels among Italian natives. Bullying others showed the second-generation migrants share a similar prevalence with the host population. The prevalence of liking school a lot was three times higher among the Romanian natives than among their peers living in Italy. Thanks to the HBSC data, this study is the first to examine the health of adolescent migrants from both the perspective of the host country and the population of origin. The results highlight the need for a more nuanced approach to studying immigrant populations, taking into account both the host country's perspective and the health patterns of the population of origin.

Sepsis Prognostic Scores Accuracy in Predicting Adverse Outcomes in Children With Sepsis Admitted to the Pediatric Intensive Care Unit From the Emergency Department: A 10-Year Single-Center Experience.

OBJECTIVE: To compare the performance of several prognostic scores calculated in the first 24 hours of admission (day 1) in predicting mortality and morbidity among critically ill children with sepsis presenting to the pediatric emergency department (PED) and then admitted to the pediatric intensive care unit (PICU). METHODS: Single-center, retrospective cohort study in children with a diagnosis of sepsis visiting the PED and then admitted to the PICU from January 1, 2010 to December 31, 2019. Sepsis organ dysfunction scores-pediatric Sequential Organ Failure Assessment (pSOFA) (Schlapbach, Matics, Shime), quickSOFA, quickSOFA-L, Pediatric Logistic Organ Dysfunction (PELOD)-2, quickPELOD-2, and Pediatric Multiple Organ Dysfunction score-were calculated during the first 24 hours of admission (day 1) and their performance compared with systemic inflammatory response syndrome (SIRS) and severe sepsis-International Consensus Conference on Pediatric Sepsis(ICCPS)-derived criteria-using the area under the receiver operating characteristic curve. Primary outcome was PICU mortality. Secondary outcomes were: a composite of death and new disability (ie, change from baseline Pediatric Overall Performance Category score ≥1); prolonged PICU length of stay (>5 d); prolonged invasive mechanical ventilation (MV) (>3 d). RESULTS: Among 60 patients with sepsis, 4 (6.7%) died, 7 (11.7%) developed new disability, 26 (43.3%) experienced prolonged length of stay, and 21 (35%) prolonged invasive MV. The prognostic ability in mortality discrimination was significantly higher for organ dysfunction scores, with PELOD-2 showing the best performance (area under the receiver operating characteristic curve, 0.924; 95% confidence interval, 0.837-1.000), significantly better than SIRS 3 criteria (0.924 vs 0.509, P = 0.009), SIRS 4 criteria (0.924 vs 0.509, P < 0.001), and severe sepsis (0.924 vs 0.527, P < 0.001). Among secondary outcomes, PELOD-2 performed significantly better than SIRS criteria and severe sepsis to predict prolonged duration of invasive MV, whereas better than severe sepsis to predict "poor outcome" (mortality or new disability). CONCLUSIONS: Day 1 organ dysfunction scores performed better in predicting mortality and morbidity outcomes than ICCPS-derived criteria. The PELOD-2 was the organ dysfunction score with the best performance for all outcomes.

Implantable cardioverter defibrillator lead performance: A systematic review and individual patient data Meta-analysis.

BACKGROUND: Reliable post-approval surveillance of implantable cardioverter-defibrillator (ICD) lead performance remains a challenge. In the past, two ICD leads were recalled due to a high frequency of failures. In this meta-analysis, we sought to provide a combined estimate of failure-free rate for ICD leads by reconstructing individual patient data from published Kaplan-Meier (KM) curves and to investigate whether estimates could be influenced by the characteristics of the study. METHODS: Observational studies assessing failure-free estimates of transvenous ICD leads with KM method, were identified through a systematic search up to November 2021. RESULTS: Forty-four studies were eligible that included 41,870 (63.1%) non-recalled leads and 24,493 (36.9%) recalled leads. The 8-year cumulative failure-free rate was 94.1% (CI, 93.6% - 94.6%) for contemporary non-recalled leads and 81.2% (80.3% - 82.0%) for recalled leads (hazard ratio [HR], 3.15 [2.85-3.47], p < 0.001). Failure-free rate was lower in single-center studies in both the non-recalled (HR, 0.28 [0.15-0.51], p < 0.001) and recalled (HR, 0.54 [0.33-0.88], p = 0.014) group compared with multicenter studies. Similarly, estimates were significantly lower in small (i.e. extracted KM curve with <312 leads) versus large studies (HR non-recalled group, 0.54 [CI, 0.33-0.89], p = 0.015; HR recalled group, 0.62 [CI, 0.43-0.89], p = 0.009). CONCLUSIONS: In this meta-analysis including >66,000 leads, we provide pooled survival curves that may play a role in generating evidence-based standards for assessing clinically acceptable failure rates for ICD leads. Lead performance was underestimated with single-center and small-sized studies; multicenter studies remain the main tool to reliably conduct post-market surveillance of ICD leads.

COVID-19 hospitalizations and patients' age at admission: The neglected importance of data variability for containment policies.

Introduction: An 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. Methods: An 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. Results: This 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. Discussion: This 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.

The Mental Well-Being of Italian Adolescents in the Last Decade through the Lens of the Dual Factor Model.

(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.

Suicide spectrum among young people during the COVID-19 pandemic: A systematic review and meta-analysis.

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).

Immune Response of a Heterologous mRNA-1273 Second-Dose Immunization after a First Dose of ChadOx1 against SARS-CoV-2: A Cross-Sectional Study.

Heterologous vaccination regimens could contribute to broadening vaccination coverage. To date, there is little evidence on the effectiveness of a combination of adenoviral COVID-19 vaccines with a second dose of mRNA vaccines. This study aims to evaluate the antibody response to the SARS-CoV-2 spike protein 25 weeks after vaccination with mRNA-1273 after a first dose of ChAdOx1. A cross-sectional study was conducted collecting sociodemographic data, clinical characteristics, and serological data from among the general population. Antibody levels were expressed as binding antibody units (BAU) per mL (cutoff = 33.8 BAU/mL). Linear regression models were used to assess the relationship between the subjects' characteristics and anti-SARS-CoV-2 antibody levels. A total of 229 participants were followed up after a median time of 173 days. The overall anti-SARS-CoV-2 IgG antibody titer was 729.0 BAU/mL. The multivariable analysis showed that the only factor associated with anti-SARS-CoV-2 IgG levels was the BMI (p = 0.007), with decreases within the healthy range weight and increases in under- or overweight people. Our results support the use of heterologous COVID-19 vaccination regimens, as they can guarantee a sustained immune antibody response. More studies are needed to understand the link between BMI and body composition and the immune response to COVID-19 vaccinations.