Comparative analysis of the thermal insulation performance of a façade enclosure integrated by vegetation under simultaneous windy and rainy climatic conditions

The literature offers some studies on the capacity of the greenery apparatus to decrease wind speed and regulate temperatures with the combination of the moisture retained by the plants and the air passing through them, but there is little on the maintenance of performance under particular weather conditions. The aim of this contri- bution is to verify the effectiveness of a vegetal façade in particularly windy conditions combined with rainy and/or high-irradiation events. The subject of the study is the enclosure of the Technology Innovation Centre for Development (itdUPM), on the Polytechnic University of Madrid, where a green wall prototype has been installed. For the purposes of the analysis, the environmental variables are examined and the monitoring data received from sensors positioned at the walls and skin of the insulated envelope are compared with the green face and without, comparing the differences in surface temperatures. These analyses are further examined by considering the correlation with different weather conditions. Experimentation shows a maintenance of per- formance, retaining an insulating capacity in all seasons, in both wind and rain, with results more evident in daylight hours. This contribute want to analyse the subtle variance between the performance of south and west facades. The strongest effect came forward during the summer season because the wall is affected by continuous irradiation on the south that is, also increased by hot weather

The impact of the SARS-CoV-2 pandemic on the workloads of UPMC advanced radiotherapy centers in Italy

GOALS The Advanced Radiotherapy Centers of UPMC San Pietro FBF of Rome (CC#1) and UPMC Villa Maria of Mirabella Eclano (CC#2) conducted a study to review variations in department workloads and workflows experienced during the pandemic. The potential relation between these variations and the new procedures introduced to prevent and contain the COVID-19 infection was also studied. MATERIALS AND METHODS The data used were obtained from reports present in the ARIA® system (v. 15.1 Varian Medical Systems, Palo Alto, CA, U.S.A.). To examine the workloads was used the Downtime, an indicator that directly quantifies the inactivity of the department, derived from the ratio between the daily stand-by time of the LINACs (TrueBeam STx®, Varian Medical Systems, Palo Alto, CA, U.S.A.) and the mean number of treatments performed every day. In order to examine the workflows and possible delays, we measured the time between the treatments ("Therapy intervals"). RESULTS The Downtime average at CC#1 slightly increased from 3.1% in 2019 to 3.8% in 2020. However, the monthly analysis shows significant reduction (March-April-May) and increase (November-December) peaks. At CC#2, the 2020 Downtime trend was fairly consistent (average value: 3.3%), with an increase during the first wave of the pandemic. The "5-10 min" Therapy intervals at CC#1, reviewed comparing the March-April-May 2020 quarter with 2019, were higher in the first months and lower in May; the "10-15 min" intervals were stable; the ">20 min" intervals slightly increased in March 2020. At CC#2, the trend in 2020 decreased during the months of higher health care emergency and increased during the summer months. CONCLUSIONS The fact that the trends of the indicators show peaks only during the periods of major health care emergency indicates an impact of the pandemic, both on the workload and on the workflow. However, they also highlight the staff's ability to rapidly adapt to the new procedures, without affecting the overall performance of the both centers

Assessing spleen stiffness by point shear‐wave elastography: Is it feasible and reproducible in patients with chronic liver disease? Is it useful to predict portal hypertension?

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Increased network centrality of the anterior insula in early abstinence from alcohol

Abnormal resting-state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph-theoretical analyses, enabling improved resolution and fine-grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large-scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region-specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular-supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.This work was supported by the European Union's Horizon 2020 research and innovation programme (668863-SyBil-AA), the ERA-Net NEURON programme (FKZ 01EW1112-TRANSALC) and Deutsche Forschungsgemeinschaft (center grants SFB636 and TRR 265 subproject B0867). SC acknowledges the Spanish State Research Agency through the Severo Ochoa Programme for Centres of Excellence in R&D (SEV-2017-0723) and the Ministerio de Economía y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-1-R and BFU2015-64380-C2-2-R.Open Access Funding provided by Istituto Italiano di Tecnologia within the CRUI-CARE Agreement.Peer reviewe

Indicatori di qualità quantitativi e percorsi di cura automatizzati in radioterapia

INTRODUZIONE I successi della moderna radioterapia sono spesso guidati da elevati standard di qualità. Questo studio punta a valutare percorsi di cura automatizzati e personalizzabili per definire nuovi indicatori di qualità quantitativi in radioterapia oncologica, al fine di ottimizzare l’efficienza e la sicurezza dei servizi erogati. MATERIALI E METODI Per questo studio, sono stati coinvolti due centri oncologici internazionali appartenenti allo stesso network (UPMC San Pietro di Roma (CC#1) ed UPMC Villa Maria di Mirabella Eclano (CC#2)), entrambi dotati di un acceleratore lineare ed uno scanner TC.  L’analisi dei dati ha preso in considerazione il periodo compreso tra gennaio 2019 e dicembre 2019. Seguendo il workflow delle attività di entrambi i centri, nello sviluppo della cartella clinica elettronica, sono stati creati dei modelli automatizzati adattabili alle differenti tipologie di trattamento, e quindi personalizzabili per ciascun paziente: utilizzando il software ARIA v15 (Varian Medical System, CA, Palo Alto, USA), abbiamo convertito tutti gli step del percorso di cura del paziente in moduli che hanno la possibilità di essere collegati per andare a formare il processo di cura del paziente stesso. I “Carepaths” infatti, rappresentano dei moduli in un processo automatizzato all’interno dei quali sono presenti attività (“task”) e appuntamenti (“appointment”), aventi dei tempi di esecuzione ben definiti entro i quali devono essere completati elettronicamente. Per avere un riferimento in merito alle prestazioni in termini quantitativi riguardo i centri, abbiamo focalizzato l’attenzione su tre fattori: percentuale di attività completate in relazione al tempo di esecuzione, giorni trascorsi e compliance dello staff con l’utilizzo di questo sistema automatizzato. RISULTATI La misurazione delle attività completate consente di definire la conformità del processo automatizzato ai percorsi assistenziali, mentre le tempistiche del completamento delle attività consentono di determinare le aree di miglioramento. In questo studio, i "Timeout" vengono sempre eseguiti con puntualità, ma i risultati su "Peer Review" e "Treatment Approval" non sono soddisfacenti. Un tempo di ritardo definito ci consente di tenere traccia delle attività in modo preciso, e l’analisi di questi valori in entrambi i centri oncologici presi in analisi, ci consente di capire se il tempo di consegna per le attività è appropriato o se c'è un margine di miglioramento. Tutti i dati osservati mostrano che la percentuale di attività completate in entrambi i centri oncologici e i tempi trascorsi per il completamento delle stesse sono differenti. CONCLUSIONI I percorsi assistenziali automatizzati, con i relativi moduli, possono essere uno strumento valido ed efficiente per misurare le attività in un reparto di radioterapia oncologica, soprattutto se utilizzati come strumento di miglioramento continuo della qualità delle prestazioni

Impatto della pandemia da SARS-CoV-2 sui workload di due centri UPMC di radioterapia ad alta specializzazione in Italia

OBIETTIVI I Centri di Radioterapia UPMC San Pietro FBF di Roma (CC#1) e UPMC Villa Maria di Mirabella Eclano (CC#2) hanno condotto uno studio con l’obiettivo di analizzare le variazioni avvenute durante la pandemia sui workload e i workflow di reparto. È stato, inoltre, ricercato l’eventuale nesso tra queste e l’introduzione di nuove procedure per la prevenzione e il contenimento del contagio da Covid-19. MATERIALI E METODI I dati utilizzati sono stati ricavati da reports presenti nel sistema ARIA (V.15.1 Varian Medical System, CA, Palo Alto, USA). Per esaminare i workload è stato utilizzato il Downtime, un indicatore che quantifica direttamente l'inattività del reparto, ricavato dal rapporto tra il tempo di standby giornaliero dei LINAC (TrueBeam STx®, Varian Medical System, CA, Palo Alto, USA) e la media di trattamenti giornalieri effettuati. Per esaminare workflow ed eventuali ritardi tra le attività, sono stati valutati gli intervalli di tempo tra una terapia e la successiva (Intervalli di terapia). RISULTATI Il Downtime nel CC#1 ha subìto un leggero aumento del valore medio dal 3.1% del 2019 al 3.8% del 2020, tuttavia l’analisi mensile mostra consistenti picchi di riduzione (marzo-aprile-maggio) e di incremento (novembre-dicembre). Per il CC#2 il trend del Downtime nel 2020 è abbastanza regolare (valore medio del 3,3%), con un incremento durante la prima ondata della pandemia. Gli Intervalli di terapia di “5-10 min” nel CC#1, analizzati confrontando il trimestre marzo-aprile-maggio 2020 col 2019, risultano maggiori per i primi mesi e ridotti a maggio; quelli di “10-15” min risultano stabili; quelli “>20 min” sono leggermente aumentati a marzo 2020. Per il CC#2 il trend nel 2020 decresce nei mesi di maggiore emergenza sanitaria e incrementa nei mesi estivi. CONCLUSIONI Il fatto che i trend degli indicatori utilizzati abbiano dei picchi esclusivamente in corrispondenza dei periodi di maggiore emergenza sanitaria, è indice di un certo impatto – sia in termini di workload che di workflow – della pandemia, ma anche della capacità del personale di adattarsi in breve tempo alle nuove procedure da eseguire, senza inficiare sul rendimento generale dei Centri

Epidemiology, Clinical Features and Prognostic Factors of Pediatric SARS-CoV-2 Infection: Results From an Italian Multicenter Study

Background: Many aspects of SARS-CoV-2 infection in children and adolescents remain unclear and optimal treatment is debated. The objective of our study was to investigate epidemiological, clinical and therapeutic characteristics of pediatric SARS-CoV-2 infection, focusing on risk factors for complicated and critical disease. Methods: The present multicenter Italian study was promoted by the Italian Society of Pediatric Infectious Diseases, involving both pediatric hospitals and general pediatricians/family doctors. All subjects under 18 years of age with documented SARS-CoV-2 infection and referred to the coordinating center were enrolled from March 2020. Results: As of 15 September 2020, 759 children were enrolled (median age 7.2 years, IQR 1.4; 12.4). Among the 688 symptomatic children, fever was the most common symptom (81.9%). Barely 47% of children were hospitalized for COVID-19. Age was inversely related to hospital admission (p < 0.01) and linearly to length of stay (p = 0.014). One hundred forty-nine children (19.6%) developed complications. Comorbidities were risk factors for complications (p < 0.001). Viral coinfections, underlying clinical conditions, age 5\u20139 years and lymphopenia were statistically related to ICU admission (p < 0.05). Garazzino et al. SARS-CoV-2 in Children and Adolescents Conclusions: Complications of COVID-19 in children are related to comorbidities and increase with age. Viral co-infections are additional risk factors for disease progression and multisystem inflammatory syndrome temporarily related to COVID-19 (MIS-C) for ICU admission

COVID-19 in Infants Less than 3 Months: Severe or Not Severe Disease?

Compared to adults, severe or fatal COVID-19 disease is much less common in children. However, a higher risk for progression has been reported in infants. Different pediatric COVID-19 severity scores are reported in the literature