4 research outputs found

    Skin Imprinting in Silica Plates: A Potential Diagnostic Methodology for Leprosy Using High-Resolution Mass Spectrometry

    No full text
    Leprosy is a chronic infectious disease caused by Mycobacterium leprae, which primarily infects macrophages and Schwann cells, affecting skin and peripheral nerves. Clinically, the most common form of identification is through the observation of anesthetic lesions on skin; however, up to 30% of infected patients may not present this clinical manifestation. Currently, the gold standard diagnostic test for leprosy is based on skin lesion biopsy, which is invasive and presents low sensibility for suspect cases. Therefore, the development of a fast, sensible and noninvasive method that identifies infected patients would be helpful for assertive diagnosis. The aim of this work was to identify lipid markers in leprosy patients directly from skin imprints, using a mass spectrometric analytical strategy. For skin imprint samples, a 1 cm<sup>2</sup> silica plate was gently pressed against the skin of patients or healthy volunteers. Imprinted silica lipids were extracted and submitted to direct-infusion electrospray ionization high-resolution mass spectrometry (ESI-HRMS). All samples were differentiated using a lipidomics-based data workup employing multivariate data analysis, which helped electing different lipid markers, for example, mycobacterial mycolic acids, inflammatory and apoptotic molecules were identified as leprosy patients’ markers. Otherwise, phospholipids and gangliosides were pointed as healthy volunteers’ skin lipid markers, according to normal skin composition. Results indicate that silica plate skin imprinting associated with ESI-HRMS is a promising fast and sensible leprosy diagnostic method. With a prompt leprosy diagnosis, an early and effective treatment could be feasible and thus the chain of leprosy transmission could be abbreviated

    Population birth data and pandemic readiness in Europe

    Get PDF
    To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadThe SARS-CoV-2 pandemic exposed multiple shortcomings in national and international capacity to respond to an infectious disease outbreak. It is essential to learn from these deficiencies to prepare for future epidemics. One major gap is the limited availability of timely and comprehensive population-based routine data about COVID-19's impact on pregnant women and babies. As part of the Horizon 2020 PHIRI (Population Health Information Research Infrastructure) project on the use of population data for COVID-19 surveillance, the Euro-Peristat research network investigated the extent to which routine information systems could be used to assess the effects of the pandemic by constructing indicators of maternal and child health and of COVID-19 infection. The Euro-Peristat network brings together researchers and statisticians from 31 countries to monitor population indicators of perinatal health in Europe and periodically compiles data on a set of 10 core and 20 recommended indicators.Horizon 2020 Framework Programm

    Epidemiological characteristics, practice of ventilation, and clinical outcome in patients at risk of acute respiratory distress syndrome in intensive care units from 16 countries (PRoVENT): an international, multicentre, prospective study

    No full text
    Background Scant information exists about the epidemiological characteristics and outcome of patients in the intensive care unit (ICU) at risk of acute respiratory distress syndrome (ARDS) and how ventilation is managed in these individuals. We aimed to establish the epidemiological characteristics of patients at risk of ARDS, describe ventilation management in this population, and assess outcomes compared with people at no risk of ARDS. Methods PRoVENT (PRactice of VENTilation in critically ill patients without ARDS at onset of ventilation) is an international, multicentre, prospective study undertaken at 119 ICUs in 16 countries worldwide. All patients aged 18 years or older who were receiving mechanical ventilation in participating ICUs during a 1-week period between January, 2014, and January, 2015, were enrolled into the study. The Lung Injury Prediction Score (LIPS) was used to stratify risk of ARDS, with a score of 4 or higher defining those at risk of ARDS. The primary outcome was the proportion of patients at risk of ARDS. Secondary outcomes included ventilatory management (including tidal volume [VT] expressed as mL/kg predicted bodyweight [PBW], and positive end-expiratory pressure [PEEP] expressed as cm H2O), development of pulmonary complications, and clinical outcomes. The PRoVENT study is registered at ClinicalTrials.gov, NCT01868321. The study has been completed. Findings Of 3023 patients screened for the study, 935 individuals fulfilled the inclusion criteria. Of these critically ill patients, 282 were at risk of ARDS (30%, 95% CI 27–33), representing 0·14 cases per ICU bed over a 1-week period. VT was similar for patients at risk and not at risk of ARDS (median 7·6 mL/kg PBW [IQR 6·7–9·1] vs 7·9 mL/kg PBW [6·8–9·1]; p=0·346). PEEP was higher in patients at risk of ARDS compared with those not at risk (median 6·0 cm H2O [IQR 5·0–8·0] vs 5·0 cm H2O [5·0–7·0]; p&lt;0·0001). The prevalence of ARDS in patients at risk of ARDS was higher than in individuals not at risk of ARDS (19/260 [7%] vs 17/556 [3%]; p=0·004). Compared with individuals not at risk of ARDS, patients at risk of ARDS had higher in-hospital mortality (86/543 [16%] vs 74/232 [32%]; p&lt;0·0001), ICU mortality (62/533 [12%] vs 66/227 [29%]; p&lt;0·0001), and 90-day mortality (109/653 [17%] vs 88/282 [31%]; p&lt;0·0001). VT did not differ between patients who did and did not develop ARDS (p=0·471 for those at risk of ARDS; p=0·323 for those not at risk). Interpretation Around a third of patients receiving mechanical ventilation in the ICU were at risk of ARDS. Pulmonary complications occur frequently in patients at risk of ARDS and their clinical outcome is worse compared with those not at risk of ARDS. There is potential for improvement in the management of patients without ARDS. Further refinements are needed for prediction of ARDS
    corecore