The impact of illness in patients with moderate to severe gastro-esophageal reflux disease

BACKGROUND: Gastro-esophageal reflux disease (GERD) is a common disease. It impairs health related quality of life (HRQL). However, the impact on utility scores and work productivity in patients with moderate to severe GERD is not well known. METHODS: We analyzed data from 217 patients with moderate to severe GERD (mean age 50, SD 13.7) across 17 Canadian centers. Patients completed three utility instruments – the standard gamble (SG), the feeling thermometer (FT), and the Health Utilities Index 3 (HUI 3) – and several HRQL instruments, including Quality of Life in Reflux and Dyspepsia (QOLRAD) and the Medical Outcomes Short Form-36 (SF-36). All patients received a proton pump inhibitor, esomeprazole 40 mg daily, for four to six weeks. RESULTS: The mean scores on a scale from 0 (dead) to 1 (full health) obtained for the FT, SG, and HUI 3 were 0.67 (95% CI, 0.64 to 0.70), 0.76 (95% CI, 0.75 to 0.80), and 0.80 (95% CI, 0.77 to 0.82) respectively. The mean scores on the SF-36 were lower than the previously reported Canadian and US general population mean scores and work productivity was impaired. CONCLUSION: GERD has significant impact on utility scores, HRQL, and work productivity in patients with moderate to severe disease. Furthermore, the FT and HUI 3 provide more valid measurements of HRQL in GERD than the SG. After treatment with esomeprazole, patients showed improved HRQL

Competence Centre ICDI per Open Science, FAIR, ed EOSC - Mission, Strategia e piano d'azione

This document presents the mission and strategy of the Italian Competence Centre on Open Science, FAIR, and EOSC. The Competence Centre is an initiative born within the Italian Computing and Data Infrastructure (ICDI), a forum created by representatives of major Italian Research Infrastructures and e-Infrastructures, with the aim of promoting sinergies at the national level, and optimising the Italian participation to European and global challenges in this field, including the European Open Science Cloud (EOSC), the European Data Infrastructure (EDI) and HPC. This working paper depicts the mission and objectives of the ICDI Competence Centre, a network of experts with various skills and competences that are supporting the national stakeholders on topics related to Open Science, FAIR principles application and participation to the EOSC. The different actors and roles are described in the document as well as the activities and services offered, and the added value each stakeholder can find the in Competence Centre. The tools and services provided, in particular the concept for the portal, though which the Centre will connect to the national landscape and users, are also presented

Sviluppo di algoritmi di diagnostica predittiva in impianti fotovoltaici

Il sempre maggior sviluppo di fonti rinnovabili, in particolare del fotovoltaico, ha introdotto nuove problematiche, di gestione e manutenzione degli impianti, sempre più rilevanti in un contesto di sistema energetico complesso. In particolare una delle maggiori criticità risiede nel monitoraggio dell’elevato numero di impianti presenti in Italia e nel Mondo al fine di garantire, per ognuno di essi, un corretto funzionamento all’interno di un sistema integrato. In particolare il 15 dicembre 2015 (COP21), data della conferenza sul clima di Parigi, ha visto concretizzarsi il primo vero accordo mondiale e giuridicamente vincolante sul clima. L’accordo definisce un piano d’azione globale al fine di evitare i cambiamenti climatici in atto limitando il riscaldamento globale al di sotto di 2°C. Questo obiettivo può essere raggiunto soprattutto attraverso una significativa elettrificazione dei sistemi termici esistenti mediante l’introduzione di sistemi di produzione di energia da fonti rinnovabili. Questo, unito ad una significativa riduzione dei costi di questa tecnologia, sta portando alla transizione da una logica di produzione e utilizzo centralizzata dell'energia a una distribuita. La generazione, infatti, apparterrà sempre di più alla piccola e media generazione distribuita sul territorio rispetto alla grande centralizzata. La svolta, in Italia, è arrivata con il fotovoltaico e con le prime incentivazioni del Conto Energia che sono state protagoniste dell’espansione sia del numero degli impianti, sia della potenza installata. A fine 2016 si trovavano in Italia oltre 700.000 impianti fotovoltaici, per una potenza complessiva di 19.283 MW che hanno generato, nello stesso anno, una produzione effettiva di energia elettrica di 22.104 GWh (gli impianti di piccola taglia (potenza inferiore o uguale a 20 kW) costituiscono oltre il 90% degli impianti totali installati in Italia e rappresentano il 20% della potenza complessiva nazionale.). La fonte rinnovabile che nel 2016 ha fornito il contributo più importante alla produzione elettrica effettiva è quella idraulica (42% della produzione elettrica da FER), seguita dalla fonte solare (oltre il 20%), dalle bioenergie (18%), dalla fonte eolica (14%) e da quella geotermica (6%). Tutte fonti distribuite che sono state installate in massima parte ed escluse l'idroelettrico e il geotermico, negli ultimi dieci anni. Nonostante ciò il sistema di trasmissione e distribuzione dell’energia non ha avuto alcun sentore di default. Questo è stato reso, in parte, possibile grazie alla raccolta e all’analisi di dati provenienti dagli impianti stessi. È quindi evidente come un sistema di monitoraggio dei singoli impianti sia ormai imprescindibile per garantire il corretto funzionamento dell’intero sistema elettrico. Dalla disponibilità dei dati di ogni singolo impianto nasce quindi la possibilità non solo di monitorarne il corretto funzionamento ma anche di eseguire un’analisi predittiva su due differenti livelli: • Predizione potenza prodotta dall’impianto; • Predizione del verificarsi di un guasto che comprometterebbe il corretto funzionamento dei dispositivi costituenti l’impianto fotovoltaico. In particolare la sola produttività dell’impianto risulta essere un’informazione generica per individuare eventuali problematiche riguardanti l’impianto e per eseguire un’identificazione esatta del tipo di guasto. Pertanto è necessario, mediante nuovi e ancora più avanzati algoritmi, pianificare una strategia di rilevamento e diagnosi dei guasti in grado di migliorare le efficienze del sistema fotovoltaico, evitare gli elevati costi di manutenzione e perdite di energia prodotta, con ripercussioni sia a livello di impianto che di sistema elettrico, e ridurre i rischi legati alla sicurezza. Nello specifico in questo elaborato si è voluto verificare la possibilità, partendo da uno storico di dati, di predire, per differenti orizzonti temporali, la futura presenza di un guasto lato inverter. Il sempre maggiore interesse, da parte di ricercatori e professionisti alle tematiche della diagnosi, hanno portato allo sviluppo di diverse tecniche di rilevamento dei guasti che possono essere raggruppate in due diverse famiglie: algoritmi basati sul modello e altri basati sui dati. Nel nostro studio la disponibilità di serie storiche ha consentito l’addestramento di modelli di diagnostica statistica. Tali modelli, inferendo la correlazione tra ingresso (variabili d’input) ed uscita (funzionamento in condizioni nominali o in presenza di guasto) hanno consentito la classificazione di ogni pattern d’ingresso nelle due classi di nostro interesse, Fault – No Fault. La scelta del tipo di modello utilizzato è ricaduta sui modelli statistici in quanto consentono di far fronte alla sempre più elevata complessità impiantistica e alla natura fortemente non lineare del nostro problema, che non potrebbero essere descritti, se non con rilevanti sforzi, mediante metodi fisici. Vengono quindi presentati due differenti algoritmi su base statistica: Rete Neurale (NN) e Autoencoders (AE), mediante i quali si è cercato di rilevare “l’impronta” del guasto per diversi orizzonti temporali. Durante l’analisi si è verificato come l’orizzonte temporale di previsione del guasto e la sensibilità del modello, intesa come capacità di rilevare in maniera corretta la futura presenza di guasto, siano notevolmente influenzati dalla statistica disponibile. In una prima fase, al fine di testare le capacità dei vari algoritmi, si è utilizzata una simulazione Montecarlo in modo da avere dei primi risultati che fossero il più possibile mediati sull’intero data set disponibile, dopodiché in un’ottica di funzionamento Online è stato sviluppato un approccio di tipo ensemble. Come accennato in precedenza una delle problematiche più rilevanti nello sviluppo dei modelli è risultata essere la limitata statistica, ovvero il ridotto numero delle istanze dei guasti rispetto a quelle identificate dal funzionamento in condizioni nominali; per fare fronte a ciò sono stati utilizzati diversi algoritmi di ricampionamento, oversampling e undersampling, dei data set. Nell’intera ottica di sviluppo degli algoritmi si è cercato, fin dalle prime fasi, di implementare modelli in grado di generalizzare il loro funzionamento in maniera del tutto indipendente dalla taglia, tecnologia e storico dati dell’impianto in modo che potesse essere assicurato un loro funzionamento per una più ampia casistica possibile

The development of a brief screener for autism using item response theory

Background: Brief screening instruments focusing on autism spectrum disorder (ASD) that can be administered in primary care are scarce; there is a need for shorter and more precise instruments. The Autism-Tics, AD/HD and other Comorbidities inventory (A-TAC) has previously been validated for ASD reporting excellent validity. This study aims to determine the psychometric properties of each item in the ASD domain (17 items) in the A-TAC using item response theory (IRT), and thereby construct and validate a short form that could be used as a screening instrument in the general population. Methods: Since 2004, parents of all 9-year-old Swedish twins have been invited to participate in a telephone interview in the Child and Adolescent Twin Study in Sweden (CATSS). The CATSS is linked to the National Patient Register (NPR), which includes data from in- and outpatient care. Data on ASD (A-TAC) collected in CATSS were compared with diagnoses from the NPR. Diagnoses that had been made both before (previous validity) and after (predictive validity) the interviews were included. The sample was divided into a developmental sample and a validation sample. An IRT model was fitted to the developmental sample and item parameters were used to select a subset of items for the short form. The performance of the proposed short form was examined in the validation sample by the use of receiver operation characteristic curves. Results: Four items which were able to discriminate among individuals with more autism traits were deemed sufficient for use in the short form. The values of the area under the receiver operating characteristic curve for a clinical diagnosis of ASD was.95 (previous validity) and.72 (predictive validity). Conclusions: The proposed short form with 4 out of the original 17 items from A-TAC, showed excellent previous validity while the predictive validity was fair. The validity of the short form was in agreement with previous validations of the full ASD domain. The short form can be a valuable screening instrument in primary care settings in order to identify individuals in need for further assessment and for use in epidemiological studies

L'Avenir de Luchon : journal scientifique, littéraire, annonces et réclames : guide général des baigneurs et des touristes aux eaux thermales, bains de mer de la France et de l'étranger

18 janvier 19031903/01/18 (N2)-1903/01/18.Appartient à l’ensemble documentaire : MidiPyren

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147-173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%-60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into "Boolean quantum features," inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores ( IPGS p h 1 and IPGS p h 2 ). By applying a logistic regression with both IPGS, ( IPGS p h 2 (or indifferently IPGS p h 1 ) and age as inputs, we reached an accuracy of 84%-86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147-173) by a factor of 10%

Life History of Aggression scores are predicted by childhood hyperactivity, conduct disorder, adult substance abuse, and low cooperativeness in adult psychiatric patients.

The prevention of aggressive behaviours is a core priority for psychiatric clinical work, but the association between the diagnostic concepts used in psychiatry and aggression remains largely unknown. Outpatients referred for psychiatric evaluations of childhood-onset neuropsychiatric disorders (n=178) and perpetrators of violent crimes referred to pre-trial forensic psychiatric investigations (n=92) had comprehensive, instrument-based, psychiatric assessments, including the Life History of Aggression (LHA) scales. Total and subscale LHA scores were compared to the categorical and dimensional diagnoses of childhood and adult DSM-IV axis I and II mental disorders, general intelligence (IQ), Global Assessment of Functioning (GAF), and personality traits according to the Temperament and Character Inventory (TCI). Overall, the two groups had similar LHA scores, but the offender group scored higher on the Antisocial subscale. Higher total LHA scores were independently associated with the hyperactivity facet of attention-deficit/hyperactivity disorder (AD/HD), childhood conduct disorder, substance-related disorders, and low scores on the Cooperativeness character dimension according to the TCI. IQ and GAF-scores were negatively correlated with the LHA subscale Self-directed aggression. Autistic traits were inversely correlated with aggression among outpatients, while the opposite pattern was noted in the forensic group. The findings call for assessments of aggression-related behaviours in all psychiatric settings

The Work Productivity and Activity Impairment Questionnaire for Patients with Gastroesophageal Reflux Disease (WPAI-GERD): Responsiveness to Change and English Language Validation

Background: A validated productivity questionnaire, the Work Productivity and Activity Impairment questionnaire for Gastroesophageal Reflux Disease (WPAI-GERD), exists for Swedish patients with GERD. Objective: To assess responsiveness to change of the WPAI-GERD and construct validity of the English language version. Methods: We used the WPAI-GERD in a before-after treatment clinical study of Canadian GERD patients with moderate or severe symptoms treated with esomeprazole 40mg once daily for 4 weeks. We measured productivity variables including GERD-specific absence from work, reduced productivity while at work and reduced productivity while carrying out regular daily activities other than work during the preceding week. Results: The analysis included 217 patients, of whom 71% (n_=_153) were employed. Before treatment, employed patients reported an average 0.9 hours of absence from work due to GERD and 14.0% reduced work productivity (5.8 hours equivalent) in the previous week, as well as 21.0% reduced productivity in daily activities (all patients). After treatment, the corresponding figures decreased to 0.3 hours, 3.0% (1.1 hours equivalent) and 4.9%, respectively. Thus, the improvement (difference from start of treatment) in productivity was 0.6 hours (p_=_0.011) for absence from work and 11.0% units (p_Coronary-disorders, Gastro-oesophageal-reflux, Pharmaceutical-services, Randomised-controlled-trials

The Work Productivity and Activity Impairment Questionnaire for Patients with Gastroesophageal Reflux Disease (WPAI-GERD): Responsiveness to Change and English Language Validation

Background: A validated productivity questionnaire, the Work Productivity and Activity Impairment questionnaire for Gastroesophageal Reflux Disease (WPAI-GERD), exists for Swedish patients with GERD. Objective: To assess responsiveness to change of the WPAI-GERD and construct validity of the English language version. Methods: We used the WPAI-GERD in a before-after treatment clinical study of Canadian GERD patients with moderate or severe symptoms treated with esomeprazole 40mg once daily for 4 weeks. We measured productivity variables including GERD-specific absence from work, reduced productivity while at work and reduced productivity while carrying out regular daily activities other than work during the preceding week. Results: The analysis included 217 patients, of whom 71% (n_=_153) were employed. Before treatment, employed patients reported an average 0.9 hours of absence from work due to GERD and 14.0% reduced work productivity (5.8 hours equivalent) in the previous week, as well as 21.0% reduced productivity in daily activities (all patients). After treatment, the corresponding figures decreased to 0.3 hours, 3.0% (1.1 hours equivalent) and 4.9%, respectively. Thus, the improvement (difference from start of treatment) in productivity was 0.6 hours (p_=_0.011) for absence from work and 11.0% units (p_Coronary-disorders, Gastro-oesophageal-reflux, Pharmaceutical-services, Randomised-controlled-trials