Mechanical chest compression and extracorporeal life support for out-of-hospital cardiac arrest. A 30-month observational study in the metropolitan area of Milan, Italy.

BACKGROUND: Return of spontaneous circulation (ROSC) is achieved in 25% of out-of-hospital cardiac arrest (OHCA) patients. Mechanical chest compression (mechCPR) may maintain better perfusion during transport, allowing hospital treatments like extracorporeal circulation life support (ECLS). We aim to assess the effectiveness of a pre-hospital protocol introduction. METHODS: Observational, retrospective study assessing all OHCA patients aged 12-75, with no-flow time <20 min in a metropolitan area (Milan, Italy, 2013-2016). PRIMARY OUTCOMES: ROSC and Cerebral Performance Category score (CPC) ≤2 at hospital discharge. Logistic regressions with multiple comparison adjustments balanced with propensity scores calculated with inverse probability of treatment weighting were performed. RESULTS: 1366 OHCA were analysed; 305 received mechCPR, 1061 manual chest compressions (manCPR), and 108 ECLS. ROSC and CPC ≤2 were associated with low-flow minutes (odds ratio [95% confidence interval] 0.90 [0.88-0.91] and 0.90 [0.87-0.93]), shockable rhythm (2.52 [1.71-3.72] and 10.68 [5.63-20.28]), defibrillations number (1.15 [1.07-1.23] and 1.15 [1.04-1.26]), and mechCPR (1.86 [1.17-2.96] and 2.06 [1.11-3.81]). With resuscitation times >13 min, mechCPR achieved more frequently ROSC compared to manCPR. Among ECLS patients, 70% had time exceeding protocol: 8 (7.5%) had CPC ≤2 (half of them with low-flow times between 45 and 90 min), 2 (1.9%) survived with severe neurological disabilities, and 13 brain-dead (12.0%) became organ donors. CONCLUSIONS: MechCPR patients achieved ROSC more frequently than manual CPR patients; mechCPR was a crucial factor in an ECLS protocol for refractory OHCA. ECLS offered a chance of survival to patients who would otherwise die.

Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models.

The response to the COVID-19 pandemic has been highly variable. Governments have applied different mitigation policies with varying effect on social and economic measures, over time. This article presents a methodology for examining the effect of mobility restriction measures and the association between health and population activity data. As case studies, we refer to the pre-vaccination experience in Italy and Israel. Facing the pandemic, Israel and Italy implemented different policy measures and experienced different population behavioral patterns. Data from these countries are used to demonstrate the proposed methodology. The analysis we introduce in this paper is a staged approach using Bayesian Networks and Structural Equations Models. The goal is to assess the impact of pandemic management and mitigation policies on pandemic spread and population activity. The proposed methodology models data from health registries and Google mobility data and then shows how decision makers can conduct scenario analyses to help design adequate pandemic management policies.

Dynamic Mixed Data Analysis and Visualization.

One of the consequences of the big data revolution is that data are more heterogeneous than ever. A new challenge appears when mixed-type data sets evolve over time and we are interested in the comparison among individuals. In this work, we propose a new protocol that integrates robust distances and visualization techniques for dynamic mixed data. In particular, given a time t∈T={1,2,…,N}, we start by measuring the proximity of n individuals in heterogeneous data by means of a robustified version of Gower's metric (proposed by the authors in a previous work) yielding to a collection of distance matrices {D(t),∀t∈T}. To monitor the evolution of distances and outlier detection over time, we propose several graphical tools: First, we track the evolution of pairwise distances via line graphs; second, a dynamic box plot is obtained to identify individuals which showed minimum or maximum disparities; third, to visualize individuals that are systematically far from the others and detect potential outliers, we use the proximity plots, which are line graphs based on a proximity function computed on {D(t),∀t∈T}; fourth, the evolution of the inter-distances between individuals is analyzed via dynamic multiple multidimensional scaling maps. These visualization tools were implemented in the Shinny application in R, and the methodology is illustrated on a real data set related to COVID-19 healthcare, policy and restriction measures about the 2020-2021 COVID-19 pandemic across EU Member States.

Deepening Well-Being Evaluation with Different Data Sources: A Bayesian Networks Approach.

In this paper, we focus on a Bayesian network s approach to combine traditional survey and social network data and official statistics to evaluate well-being. Bayesian networks permit the use of data with different geographical levels (provincial and regional) and time frequencies (daily, quarterly, and annual). The aim of this study was twofold: to describe the relationship between survey and social network data and to investigate the link between social network data and official statistics. Particularly, we focused on whether the big data anticipate the information provided by the official statistics. The applications, referring to Italy from 2012 to 2017, were performed using ISTAT's survey data, some variables related to the considered time period or geographical levels, a composite index of well-being obtained by Twitter data, and official statistics that summarize the labor market.

Modeling Provincial Covid-19 Epidemic Data Using an Adjusted Time-Dependent SIRD Model.

In this paper, we develop a forecasting model for the spread of COVID-19 infection at a provincial (i.e., EU NUTS-3) level in Italy by using official data from the Italian Ministry of Health integrated with data extracted from daily official press conferences of regional authorities and local newspaper websites. This data integration is needed as COVID-19 death data are not available at the NUTS-3 level from official open data channels. An adjusted time-dependent SIRD model is used to predict the behavior of the epidemic; specifically, the number of susceptible, infected, deceased, recovered people and epidemiological parameters. Predictive model performance is evaluated using comparison with real data.

Are Epidemiological Estimates Able to Describe the Ability of Health Systems to Cope with COVID-19 Epidemic?

INTRODUCTION: The coronavirus disease 2019 (COVID-19) epidemic is an infectious disease which was declared a pandemic and hit countries worldwide from the beginning of the year 2020. Despite the emergency vigilance plans, health systems in all countries experienced a different ratio of lethality, amount of admissions to intensive care units and quarantine management of positive patients. The aim of this study is to investigate whether some epidemiological estimates could have been useful in understanding the capacity of the Italian Regional Health Services to manage the COVID-19 epidemic. METHODS: We have compared data between two different Italian regions in the Northern part of Italy (Lombardy and Veneto) and the national data to determine whether different health strategies might be significant in explaining dissimilar patterns of the COVID-19 epidemic in Italy. Data have been extracted from a public database and were available only in an aggregated form. RESULTS: The regions in question displayed two different health policies to face the COVID-19 epidemic: while Veneto's health service was largely territorially oriented, Lombardy's strategy was more hospital-centered. DISCUSSION: The key to facing epidemics like this one consists in identifying solutions outside of hospitals. This however requires there be well-trained general practitioners and enough healthcare personnel working outside hospitals.

CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region.

The first case of Coronavirus Disease 2019 in Italy was detected on February the 20th in Lombardy region. Since that date, Lombardy has been the most affected Italian region by the epidemic, and its healthcare system underwent a severe overload during the outbreak. From a public health point of view, therefore, it is fundamental to provide healthcare services with tools that can reveal possible new health system stress periods with a certain time anticipation, which is the main aim of the present study. Moreover, the sequence of law decrees to face the epidemic and the large amount of news generated in the population feelings of anxiety and suspicion. Considering this whole complex context, it is easily understandable how people "overcrowded" social media with messages dealing with the pandemic, and emergency numbers were overwhelmed by the calls. Thus, in order to find potential predictors of possible new health system overloads, we analysed data both from Twitter and emergency services comparing them to the daily infected time series at a regional level. Particularly, we performed a wavelet analysis in the time-frequency plane, to finely discriminate over time the anticipation capability of the considered potential predictors. In addition, a cross-correlation analysis has been performed to find a synthetic indicator of the time delay between the predictor and the infected time series. Our results show that Twitter data are more related to social and political dynamics, while the emergency calls trends can be further evaluated as a powerful tool to potentially forecast new stress periods. Since we analysed aggregated regional data, and taking into account also the huge geographical heterogeneity of the epidemic spread, a future perspective would be to conduct the same analysis on a more local basis.

Monitoring emergency calls and social networks for COVID-19 surveillance. To learn for the future: The outbreak experience of the Lombardia region in Italy.

On 18th February the first Italian case of Coronavirus Induced Disease 2019 (COVID19) due to secondary transmission outside China was identified in Codogno, Lombardia region. In the following days the number of cases started to rise not only in Lombardia but also in other Italian regions, although Lombardia remained and it is still the most affected region in Italy. At the moment, 234801 cases have been identified in Italy, out of which 90070 in Lombardia region. The (Severe Acute Respiratory Syndrome Coronavirus 2) SARS CoV 2 outbreak in Italy has been characterized by a massive spread of news coming from both official and unofficial sources leading what has been defined as infodemia, an over-abundance of information - some accurate and some not - that has made hard for people to find trustworthy sources and reliable guidance needed. Infodemia on SARS CoV 2 created the perfect field to build uncertainty in the population, which was scared and not prepared to face this outbreak. It is understandable how the rapid increase of the cases' number , the massive spread of news and the adoption of laws to face this outbreak led to a feeling of anxiety in the population whose everyday life changed very quickly. A way to assess the dynamic burden of social anxiety is a context analysis of major social networks activities over the Internet. To this aim Twitter represents a possible ideal tool since the focused role of the tweets according to the more urgent needs of information and communication rather than general aspects of social projection and debate as in the case of Facebook, which could provide slower responses for the fast individual and social context evolution dynamics.  Aim of the paper is to analyse the most common reasons for calling and outcomes. Furthermore, the joint analysis with Twitter trends related to emergency services might be useful to understand possible correlations with epidemic trends and predict new outbreaks.

Heterogeneity of COVID-19 outbreak in Italy.

An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started in December 2019 in China and was declared a pandemic on 11.03.2020 by WHO. Italy is one of the most afflicted Country by this epidemic with 136,110 confirmed cases and 16,654 deaths on 9.4.2020 (at the same date, the Ministry of Health was reporting 143,626 cases).  During these few months the National Health Service have made a great effort to cope with the increasing request of intensive care beds and all the elective activities in hospital have been suspended. Data from the different Italian regions shows different patterns of positive and dead for this syndrome. Moreover, striking differences of the observed lethality of the infections among different areas were immediately evident from the epidemic reports. It will be of critical relevance to understand the expected evolution of the first lock-down phase, driving the exhaustion of the Covid-19 outbreak.(www.actabiomedica.it).

Enteral versus intravenous approach for the sedation of critically ill patients: a randomized and controlled trial.

BACKGROUND: ICU patients must be kept conscious, calm, and cooperative even during the critical phases of illness. Enteral administration of sedative drugs might avoid over sedation, and would be as adequate as intravenous administration in patients who are awake, with fewer side effects and lower costs. This study compares two sedation strategies, for early achievement and maintenance of the target light sedation. METHODS: This was a multicenter, single-blind, randomized and controlled trial carried out in 12 Italian ICUs, involving patients with expected mechanical ventilation duration > 72 h at ICU admission and predicted mortality > 12% (Simplified Acute Physiology Score II > 32 points) during the first 24 h on ICU. Patients were randomly assigned to receive intravenous (midazolam, propofol) or enteral (hydroxyzine, lorazepam, and melatonin) sedation. The primary outcome was percentage of work shifts with the patient having an observed Richmond Agitation-Sedation Scale (RASS) = target RASS ±1. Secondary outcomes were feasibility, delirium-free and coma-free days, costs of drugs, length of ICU and hospital stay, and ICU, hospital, and one-year mortality. RESULTS: There were 348 patients enrolled. There were no differences in the primary outcome: enteral 89.8% (74.1-100), intravenous 94.4% (78-100), p = 0.20. Enteral-treated patients had more protocol violations: n = 81 (46.6%) vs 7 (4.2%), p < 0.01; more self-extubations: n = 14 (8.1%) vs 4 (2.4%), p = 0.03; a lighter sedative target (RASS = 0): 93% (71-100) vs 83% (61-100), p < 0.01; and lower total drug costs: 2.39 (0.75-9.78) vs 4.15 (1.20-20.19) €/day with mechanical ventilation (p = 0.01). CONCLUSIONS: Although enteral sedation of critically ill patients is cheaper and permits a lighter sedation target, it is not superior to intravenous sedation for reaching the RASS target. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01360346 . Registered on 25 March 2011.

An itinerant sensory approach to investigate consumers' perception and acceptability at a food exhibition.

In a food exhibition where several producers of the same product category are present at the same time, consumers usually have the opportunity to taste several free samples of the same product type, thus they can experience and compare the sensory characteristics of each and evaluate their liking for each sample tasted. This study assessed the potential of an itinerant sensory data collection in understanding the consumers' perception and acceptance of cheese during a multiple tasting experience at a food exhibition. Subjects tasted seven samples of Parmigiano Reggiano cheese aged for different times (24 and 36months) at seven producer stands and recorded their evaluations using tablets, on which an application specifically developed for this study was installed. This evaluation situation was defined as "pseudo-natural," in opposition to the "natural" and the "naturalistic" settings. The itinerant sensory session comprised a liking test, a rate-all-that-apply (RATA) test using a just about right (JAR) scale, a food pairing test, and a questionnaire. Consumers significantly (p<0.05) discriminated the cheeses as a function of the aging time, describing with different attributes the 24months (sweetness, fresh fruit, grass, yogurt, butter flavors, elasticity, and humidity) and the 36months (saltiness, bitterness, sourness, spicy, aromatic herbs, cheese rind flavors, crumbliness, granularity, hardness, and hotness) aged products. The combined application of regression models, Penalty-Lift analysis, and decision tree models in investigating the relationships between liking and the RATA data, provided results revealing that the attributes elasticity, sweetness, humidity, fresh fruit, and butter were the main drivers of liking. Whereas, the attributes sourness, bitterness, and hardness were the main drivers of dislike. Therefore, even though no significant differences in terms of liking were observed among the tested cheeses, consumers preferred the attributes more frequently perceived in the least aged products. In conclusion, the presented itinerant sensory approach had provided meaningful information to understand the consumers' cheese perception and acceptability. In the future, it could advantageously be applied for studying food perception in other situations in which subjects naturally choose or consume several products while freely moving from one to another (e.g. self-service restaurant).

Confrontation Naming and Reading Abilities at Primary School: A Longitudinal Study.

BACKGROUND: Confrontation naming tasks are useful in the assessment of children with learning and language disorders. OBJECTIVES: The aims of this study were (1) providing longitudinal data on confrontation naming; (2) investigating the role of socioeconomic status (SES), intelligence, age, and gender in confrontation naming; (3) identifying relationship between confrontation naming and reading abilities (fluency, accuracy, and comprehension). METHOD: A five-year longitudinal investigation of confrontation naming (i.e., the Boston Naming Test (BNT)) in a nonclinical sample of Italian primary school children was conducted (n = 126), testing them at the end of each school year, to assess nonverbal intelligence, confrontation naming, and reading abilities. RESULTS: Performance on the BNT emerged as a function of IQ and SES. Significant correlations between confrontation naming and reading abilities, especially comprehension, were found; BNT scores correlated better with reading fluency than with reading accuracy. CONCLUSIONS: The longitudinal data obtained in this study are discussed with regard to reading abilities, intelligence, age, gender, and socioeconomic status.

Bias reduction in repeated-measures observational studies by the use of propensity score: the case of enteral sedation for critically ill patients.

PURPOSE: Within the evidence-based medicine paradigm, randomized controlled trials represent the "gold standard" to produce reliable evidence. Indeed, planning and implementing randomized controlled trials in critical care medicine presents limitations because of intrinsic and structural problems. As a consequence, observational studies still occur frequently. In these cases, propensity score (PS) (probability of receiving a treatment conditional on observed covariates) is an increasingly used technique to adjust the results. Few studies addressed the specific issue of a PS correction of repeated-measures designs. MATERIALS AND METHODS: Three techniques for correcting the analysis of nonrandomized designs (matching, stratification, regression adjustment) are presented in a tutorial form and applied to a real case study: the comparison between intravenous and enteral sedative therapy in the intensive care unit setting. RESULTS: After showing the results before and after the use of PS, we suggest that such a tool allows to partially overcoming the bias associated with the observational nature of the study. It permits to correct the estimates for any observed covariate, while unobserved confounders cannot be controlled for. CONCLUSIONS: Propensity score represents a useful additional tool to estimate the effects of treatments in nonrandomized studies. In the case study, an enteral sedation approach was equally effective to an intravenous regime, allowing for a lower level of sedation and spare of resources.

Free and total plasma malondialdehyde in chronic renal insufficiency and in dialysis patients.

BACKGROUND: Available data about oxidative status in patients with end-stage renal disease (ESRD) or on dialysis are contradictory. The present cross-sectional study aimed to investigate the role of renal insufficiency and dialysis on lipid peroxidation. To separate the effects of uraemia from dialysis-induced stress, we enrolled 26 patients with renal insufficiency on conservative treatment (ESRD), 23 on peritoneal dialysis (PD), 30 on haemodialysis (HD) and 30 controls. METHODS: Plasma malondialdehyde (MDA) levels, both total (tMDA) and free (fMDA), were measured as indexes of oxidative stress by gas chromatography-mass spectrometry. Bound MDA (bMDA) levels were calculated as the difference between tMDA and fMDA. RESULTS: Total and bMDA concentrations were significantly higher in patients than in controls (ESRD > HD > PD). In PD and HD patients, fMDA levels were similar and significantly higher than in ESRD. Multivariate analysis, with tMDA, fMDA and bMDA as dependent variables, showed similar and significant tMDA and bMDA relations with residual renal function (t = -2.160, P = 0.035) and albumin (t = -2.049, P = 0.045). Erythropoietin dose affected only fMDA values (t = -2.178, P = 0.034). CONCLUSIONS: Free and bMDA concentrations identified different MDA patterns. Bound MDA, not excreted by kidneys, accounts alone for high tMDA concentrations in ESRD patients, while both fMDA and bMDA contribute to tMDA values in dialysis patients. These findings show that increased tMDA could be indicative not only of recent lipid peroxidation, and they also highlight the importance of evaluating free, bound and total MDA in patients with reduced renal function in order to assess their oxidative status.

The Rorschach test and Gilles de la Tourette's syndrome: a pilot case-control study.

BACKGROUND: To date only three studies, all lacking a control group, have investigated the personality style underlying tic disorders or Tourette's syndrome (TS), using the projective Rorschach test. Despite the recent controversy about its proper use in clinical practice and research, the Rorschach test may be useful to explore personality organization in TS. The research hypothesis under investigation in this exploratory study was that young TS patients exhibit a peculiar personality organization, with significantly increased indicators of poor emotional control, aggression, anxiety and depression, on the Rorschach test, compared to healthy controls. METHODS: We analyed the Rorschach protocols of 17 newly diagnosed paediatric TS patients and 17 age- and sex-matched healthy controls. RESULTS: Compared with the controls young TS patients recorded significantly lower mean percentages of F and F+ responses and a significantly higher number of FM and FC responses, thus showing reduced control of emotions and difficulty in integrating aggressivity. Furthermore, associations emerged between comorbidity with ADHD and increased emotional instability and between severity of tics and of OCD and a pattern of emotional hyper-control and application of rigid defensive mechanisms. CONCLUSIONS: These results seem to confirm the existence of a peculiar personality style in young TS patients and may have important implications, both pathogenetic and therapeutic.

Psychopathology in children and adolescents with Tourette's syndrome: a controlled study.

OBJECTIVE: Few controlled studies have considered, in paediatric subjects, associations between Tourette's syndrome (TS) and psychiatric/behavioural disorders. We conducted a case-control study to verify the reproducibility of the few data published on this topic to date. METHOD: Clinicians' impression (i.e. structured interviews and usual history taking), standardized psychiatric and behavioural rating scales (CBCL, TAI, CDI, CRS-R:L, Y-GTSS, CY-BOCS) were used to investigate these associations in 17 youngsters with TS and in 17 age- and sex-matched controls. RESULTS: The clinician's diagnoses revealed TS alone in 23.5% of the patients (4/17), TS plus attention-deficit/hyperactivity disorder (ADHD) in 11.8% (2/17), TS plus obsessive-compulsive disorder (OCD) in 41.2% (7/17), and TS plus ADHD and OCD in 23.5% (4/17). No control subject presented ADHD and/or OCD. These clinical findings were confirmed by Child Behaviour Check List (CBCL) results. The TS group, compared with the controls, recorded significantly higher CBCL scores in scales relating to the main comorbid conditions. No significant differences emerged on the Children's Depression Inventory or Test Anxiety Inventory. CONCLUSION: TS patients have a high prevalence of psychiatric and behavioural problems compared with controls. The CBCL is a rapid and useful screening-diagnostic instrument for highlighting the main psychiatric and behavioural problems in TS.