Severe acute respiratory syndrome coronavirus 2 RNA contamination of inanimate surfaces and virus viability in a health care emergency unit

Objectives: To detect possible severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA contamination of inanimate surfaces in areas at high risk of aerosol formation by patients with coronavirus disease 2019 (COVID-19). Methods: Sampling was performed in the emergency unit and the sub-intensive care ward. SARS-CoV-2 RNA was extracted from swabbed surfaces and objects and subjected to real-time RT-PCR targeting RNA-dependent RNA polymerase and E genes. Virus isolation from positive samples was attempted in vitro on Vero E6 cells. Results: Twenty-six samples were collected and only two were positive for low-level SARS-CoV-2 RNA, both collected on the external surface of continuous positive airway pressure helmets. All transport media were inoculated onto susceptible cells, but none induced a cytopathic effect on day 7 of culture. Conclusions: Even though daily contact with inanimate surfaces and patient fomites in contaminated areas may be a medium of infection, our data obtained in real-life conditions suggest that it might be less extensive than hitherto recognized

Emergency Department and Out-of-Hospital Emergency System (112-AREU 118) integrated response to Coronavirus Disease 2019 in a Northern Italy centre

Since December 2019, the world has been facing the life-threatening disease, named Coronavirus disease-19 (COVID-19), recognized as a pandemic by the World Health Organization. The response of the Emergency Medicine network, integrating "out-of-hospital" and "hospital" activation, is crucial whenever the health system has to face a medical emergency, being caused by natural or human-derived disasters as well as by a rapidly spreading epidemic outbreak. We here report the Pavia Emergency Medicine network response to the COVID-19 outbreak. The "out-of-hospital" response was analysed in terms of calls, rescues and missions, whereas the "hospital" response was detailed as number of admitted patients and subsequent hospitalisation or discharge. The data in the first 5 weeks of the Covid-19 outbreak (February 21-March 26, 2020) were compared with a reference time window referring to the previous 5 weeks (January 17-February 20, 2020) and with the corresponding historical average data from the previous 5 years (February 21-March 26). Since February 21, 2020, a sudden and sustained increase in the calls to the AREU 112 system was noted (+\u2009440%). After 5 weeks, the number of calls and missions was still higher as compared to both the reference pre-Covid-19 period (+\u200948% and\u2009+\u200910%, respectively) and the historical control (+\u200953% and\u2009+\u200922%, respectively). Owing to the overflow from the neighbouring hospitals, which rapidly became overwhelmed and had to temporarily close patient access, the population served by the Pavia system more than doubled (from 547.251 to 1.135.977 inhabitants,\u2009+\u2009108%). To minimize the possibility of intra-hospital spreading of the infection, a separate "Emergency Department-Infective Disease" was created, which evaluated 1241 patients with suspected infection (38% of total ED admissions). Out of these 1241 patients, 58.0% (n\u2009=\u2009720) were admitted in general wards (n\u2009=\u2009629) or intensive care unit (n\u2009=\u200991). To allow this massive number of admissions, the hospital reshaped many general ward Units, which became Covid-19 Units (up to 270 beds) and increased the intensive care unit beds from 32 to 60. In the setting of a long-standing continuing emergency like the present Covid-19 outbreak, the integration, interaction and team work of the "out-of-hospital" and "in-hospital" systems have a pivotal role. The present study reports how the rapid and coordinated reorganization of both might help in facing such a disaster. AREU-112 and the Emergency Department should be ready to finely tune their usual cooperation to respond to a sudden and overwhelming increase in the healthcare needs brought about by a pandemia like the current one. This lesson should shape and reinforce the future

Low risk for SARS-CoV2 symptomatic infection and early complications in paediatric patients during the ongoing CoVID19 epidemics in Lombardy

134noreservedmixedRovida F.; Cereda D.; Novati S.; Licari A.; Triarico A.; Marseglia G. L.; Bruno R.; Baldanti F.; Mondelli M.; Brunetti E.; Di Matteo A.; Seminari E.; Maiocchi L.; Zuccaro V.; Pagnucco L.; Mariani B.; Ludovisi S.; Lissandrin R.; Parisi A.; Sacchi P.; Patruno S. F. A.; Michelone G.; Gulminetti R.; Zanaboni D.; Maserati R.; Orsolini P.; Vecchia M.; Sciarra M.; Asperges E.; Colaneri M.; Di Filippo A.; Sambo M.; Biscarini S.; Lupi M.; Roda S.; Pieri T. C.; Gallazzi I.; Sachs M.; Valsecchi P.; Perlini S.; Alfano C.; Bonzano M.; Briganti F.; Crescenzi G.; Falchi A. G.; Guarnone R.; Guglielmana B.; Maggi E.; Martino I.; Pettenazza P.; Pioli di Marco S.; Quaglia F.; Sabena A.; Salinaro F.; Speciale F.; Zunino I.; De Lorenzo M.; Secco G.; Dimitry L.; Cappa G.; Maisak I.; Chiodi B.; Sciarrini M.; Barcella B.; Resta F.; Moroni L.; Vezzoni G.; Scattaglia L.; Boscolo E.; Zattera C.; Tassi M. F.; Capozza V.; Vignaroli D.; Bazzini M.; Iotti G.; Mojoli F.; Belliato M.; Perotti L.; Mongodi S.; Tavazzi G.; Marseglia G.; Brambilla I.; Barbarini D.; Bruno A.; Cambieri P.; Campanini G.; Comolli G.; Corbella M.; Daturi R.; Furione M.; Monzillo E.; Paolucci S.; Parea M.; Percivalle E.; Piralla A.; Sarasini A.; Zavattoni M.; Adzasehoun G.; Bellotti L.; Cabano E.; Casali G.; Dossena L.; Frisco G.; Garbagnoli G.; Girello A.; Landini V.; Lucchelli C.; Maliardi V.; Pezzaia S.; Premoli M.; Bonetti A.; Caneva G.; Cassaniti I.; Corcione A.; Di Martino R.; Di Napoli A.; Ferrari A.; Ferrari G.; Fiorina L.; Giardina F.; Mercato A.; Novazzi F.; Ratano G.; Rossi B.; Sciabica I. M.; Tallarita M.; Vecchio Nepita E.; Calvi M.; Tizzoni M.; Nicora C.; Petronella V.; Marena C.; Muzzi A.; Lago P.Rovida, F.; Cereda, D.; Novati, S.; Licari, A.; Triarico, A.; Marseglia, G. L.; Bruno, R.; Baldanti, F.; Mondelli, M.; Brunetti, E.; Di Matteo, A.; Seminari, E.; Maiocchi, L.; Zuccaro, V.; Pagnucco, L.; Mariani, B.; Ludovisi, S.; Lissandrin, R.; Parisi, A.; Sacchi, P.; Patruno, S. F. A.; Michelone, G.; Gulminetti, R.; Zanaboni, D.; Maserati, R.; Orsolini, P.; Vecchia, M.; Sciarra, M.; Asperges, E.; Colaneri, M.; Di Filippo, A.; Sambo, M.; Biscarini, S.; Lupi, M.; Roda, S.; Pieri, T. C.; Gallazzi, I.; Sachs, M.; Valsecchi, P.; Perlini, S.; Alfano, C.; Bonzano, M.; Briganti, F.; Crescenzi, G.; Falchi, A. G.; Guarnone, R.; Guglielmana, B.; Maggi, E.; Martino, I.; Pettenazza, P.; Pioli di Marco, S.; Quaglia, F.; Sabena, A.; Salinaro, F.; Speciale, F.; Zunino, I.; De Lorenzo, M.; Secco, G.; Dimitry, L.; Cappa, G.; Maisak, I.; Chiodi, B.; Sciarrini, M.; Barcella, B.; Resta, F.; Moroni, L.; Vezzoni, G.; Scattaglia, L.; Boscolo, E.; Zattera, C.; Tassi, M. F.; Capozza, V.; Vignaroli, D.; Bazzini, M.; Iotti, G.; Mojoli, F.; Belliato, M.; Perotti, L.; Mongodi, S.; Tavazzi, G.; Marseglia, G.; Brambilla, I.; Barbarini, D.; Bruno, A.; Cambieri, P.; Campanini, G.; Comolli, G.; Corbella, M.; Daturi, R.; Furione, M.; Monzillo, E.; Paolucci, S.; Parea, M.; Percivalle, E.; Piralla, A.; Sarasini, A.; Zavattoni, M.; Adzasehoun, G.; Bellotti, L.; Cabano, E.; Casali, G.; Dossena, L.; Frisco, G.; Garbagnoli, G.; Girello, A.; Landini, V.; Lucchelli, C.; Maliardi, V.; Pezzaia, S.; Premoli, M.; Bonetti, A.; Caneva, G.; Cassaniti, I.; Corcione, A.; Di Martino, R.; Di Napoli, A.; Ferrari, A.; Ferrari, G.; Fiorina, L.; Giardina, F.; Mercato, A.; Novazzi, F.; Ratano, G.; Rossi, B.; Sciabica, I. M.; Tallarita, M.; Vecchio Nepita, E.; Calvi, M.; Tizzoni, M.; Nicora, C.; Petronella, V.; Marena, C.; Muzzi, A.; Lago, P

Continuous quality improvement in intensive care medicine. The GiViTI Margherita project - Report 2005

Aim. The assessment of the quality of intensive care medicine is mandatory in the modern healthcare system. In Italy, the GiViTI (Gruppo Italiano per la Valutazione degli Interventi in Terapia Intensiva) network is working in this field since 1991 and it now involves 295 out of the about 450 Italian intensive care units (ICU). In 2002 GiViTI launched a project for the continuous quality assessment and improvement that is now joined by 180 ICUs. Data collected in 2005 are analyzed and presented. Methods. All admitted patients were entered in a validated software, which performs a multitude of validity checks during the data entry. Data were further reviewed by the co-ordinating center; patients admitted in months with more than 10% of incomplete or inconsistent records in each ICU were excluded from the analysis. Each year, a multivariate logistic regression model is fitted to identify predictors of hospital mortality. Starting from the SAPS 2 and the 2004 GiViTI model predictions of hospital mortality, two calibration tables and curves are presented. Results. In 2005, 180 Italian ICUs collected data on 55 246 patients. After excluding those admitted in months with an unjustified lower recruitment rate or with less than 90% of complete and consistent data, we had 52 816 (95.6%) valid cases. Although the rough hospital mortality in 2005 was 1% higher than in 2004 (22.6% vs 21.5%), the adjusted mortality shows a statistically significant 4% reduction (obser-ved-to-expected ratio: 0.96; 95% CI: 0.94-0.97). Conclusion. Italian ICUs in 2005 performed better than in 2004, at a parity of patient severity

EBV DNA increase in COVID-19 patients with impaired lymphocyte subpopulation count

Objectives: The immunologic profile and opportunistic viral DNA increase were monitored in Italian patients with COVID-19 in order to identify markers of disease severity. Methods: A total of 104 patients infected with SARS-CoV-2 were evaluated in the study. Of them, 42/104 (40.4%) were hospitalized in an intensive care unit (ICU) and 62/104(59.6%) in a sub-intensive care unit (SICU). Human cytomegalovirus (HCMV) and Epstein-Barr virus (EBV), Parvovirus B19 and Human Herpesvirus 6 virus reactivations were determined by real-time PCR, and lymphocyte subpopulation counts were determined by flow cytometry. Results: Among opportunistic viruses, only EBV was consistently detected. EBV DNA was observed in 40/42 (95.2%) of the ICU patients and in 51/61 (83.6%) of the SICU patients. Comparing the two groups of patients, the EBV DNA median level among ICU patients was significantly higher than that observed in SICU patients. In parallel, a significant reduction of CD8 T cell and NK count in ICU patients as compared with SICU patients was observed (p < 0.05). In contrast, B cell count was significantly increased in ICU patients (p = 0.0172). Conclusions: A correlation between reduced CD8+ T cells and NK counts, EBV DNA levels and COVID-19 severity was observed. Other opportunistic viral infections were not observed. The relationship between EBV load and COVID-19 severity should be further evaluated in longitudinal studies

Detection of the SARS-CoV-2 in different biologic specimens from positive patients with COVID-19, in Northern Italy

Coronavirus disease 2019 (COVID-19) diagnosis is based on molecular detection of SARS-CoV-2 in respiratory samples such as nasal swab (NS). However, the evidence that NS in patients with pneumonia was sometimes negative raises the attention to collect other clinical specimens. SARS-CoV-2 was shown in 10.3% rectal swabs (RS), 7.7% plasma, 1% urine, and 0% feces from 143 NS-positive patients. Potential infection by fluids different from respiratory secretion is possible but unlikely

Cognitive reserve as a useful variable to address robotic or conventional upper limb rehabilitation treatment after stroke: a multicentre study of the Fondazione Don Carlo Gnocchi

Background and purpose: Rehabilitation plays a central role in stroke recovery. Besides conventional therapy, technological treatments have become available. The effectiveness and appropriateness of technological rehabilitation are not yet well defined; hence, research focused on different variables impacting recovery is needed. Results from the literature identified cognitive reserve (CR) as a variable impacting on the cognitive outcome. In this paper, the aim was to evaluate whether CR influences the motor outcome in patients after stroke treated with conventional or robotic therapy and whether it may influence one treatment rather than another. Methods: Seventy-five stroke patients were enrolled in five Italian neurological rehabilitation centres. Patients were assigned either to a robotic group, rehabilitation by means of robotic devices, or to a conventional group, where a traditional approach was used. Patients were evaluated at baseline and after rehabilitation treatment of 6\ua0weeks through the Action Research Arm Test (ARAT), the Motricity Index (MI) and the Barthel Index (BI). CR was assessed at baseline using the Cognitive Reserve Index (CRI) questionnaire. Results: Considering all patients, a weak correlation was found between the CRI related to leisure time and MI evolution (r = 0.276; P\ua0=\ua00.02). Amongst the patients who performed a robotic rehabilitation, a moderate correlation emerged between the CRI related to working activities and MI evolution (r = 0.422; P\ua0=\ua00.02). Conclusions: Our results suggest that CR may influence the motor outcome. For each patient, CR and its subcategories should be considered in the choice between conventional and robotic treatment