6 research outputs found

    Molecular hazard identification of non-O157 Shiga toxin-producing Escherichia coli (STEC)

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    The complexity regarding Shiga toxin-producing Escherichia coli (STEC) in food safety enforcement as well as clinical care primarily relates to the current inability of an accurate risk assessment of individual strains due to the large variety in serotype and genetic content associated with (severe) disease. In order to classify the clinical and/or epidemic potential of a STEC isolate at an early stage it is crucial to identify virulence characteristics of putative pathogens from genomic information, which is referred to as ‘predictive hazard identification’. This study aimed at identifying associations between virulence factors, phylogenetic groups, isolation sources and seropathotypes. Most non-O157 STEC in the Netherlands belong to phylogroup B1 and are characterized by the presence of ehxA, iha and stx2, but absence of eae. The large variability in the number of virulence factors present among serogroups and seropathotypes demonstrated that this was merely indicative for the virulence potential. While all the virulence gene associations have been worked out, it appeared that there is no specific pattern that would unambiguously enable hazard identification for an STEC strain. However, the strong correlations between virulence factors indicate that these arrays are not a random collection but are rather specific sets. Especially the presence of eae was strongly correlated to the presence of many of the other virulence genes, including all non-LEE encoded effectors. Different stx-subtypes were associated with different virulence profiles. The factors ehxA and ureC were significantly associated with HUS-associated strains (HAS) and not correlated to the presence of eae. This indicates their candidacy as important pathogenicity markers next to eae and stx2a

    FROM CENTRAL PLACE TO NETWORK MODEL: THEORY AND EVIDENCE OF A PARADIGM CHANGE

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    While the deficiencies of the central place model have often been highlighted, no other paradigm has replaced it. However, recently some researchers have hinted at the development of a new model of spatial organisation, a network model. This model would hold most in polycentric urban regions. This paper discusses the features of this network model in comparison with the central place model. Moreover, it explores whether this model describes spatial reality better, thereby focusing on complementarity, a main feature of the model. The relationships within multi-location hospitals and universities of professional education (hogescholen), which spread their offer of care and study programmes over multiple, close-by cities, are analysed for this reason. Within the hospital care sector there is a clear trend towards complementarity, in line with the network model. The hogescholen sector provides a more ambiguous picture. The network model, however, still seems more appropriate than the central place model. Copyright (c) 2007 by the Royal Dutch Geographical Society KNAG.

    Death in hospital following ICU discharge : insights from the LUNG SAFE study

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    Altres ajuts: Italian Ministry of University and Research (MIUR)-Department of Excellence project PREMIA (PREcision MedIcine Approach: bringing biomarker research to clinic); Science Foundation Ireland Future Research Leaders Award; European Society of Intensive Care Medicine (ESICM), Brussels; St Michael's Hospital, Toronto; University of Milan-Bicocca, Monza, Italy.Background: To determine the frequency of, and factors associated with, death in hospital following ICU discharge to the ward. Methods: The Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE study was an international, multicenter, prospective cohort study of patients with severe respiratory failure, conducted across 459 ICUs from 50 countries globally. This study aimed to understand the frequency and factors associated with death in hospital in patients who survived their ICU stay. We examined outcomes in the subpopulation discharged with no limitations of life sustaining treatments ('treatment limitations'), and the subpopulations with treatment limitations. Results: 2186 (94%) patients with no treatment limitations discharged from ICU survived, while 142 (6%) died in hospital. 118 (61%) of patients with treatment limitations survived while 77 (39%) patients died in hospital. Patients without treatment limitations that died in hospital after ICU discharge were older, more likely to have COPD, immunocompromise or chronic renal failure, less likely to have trauma as a risk factor for ARDS. Patients that died post ICU discharge were less likely to receive neuromuscular blockade, or to receive any adjunctive measure, and had a higher pre- ICU discharge non-pulmonary SOFA score. A similar pattern was seen in patients with treatment limitations that died in hospital following ICU discharge. Conclusions: A significant proportion of patients die in hospital following discharge from ICU, with higher mortality in patients with limitations of life-sustaining treatments in place. Non-survivors had higher systemic illness severity scores at ICU discharge than survivors. Trial Registration: ClinicalTrials.gov NCT02010073

    Resolved versus confirmed ARDS after 24 h: insights from the LUNG SAFE study

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    Purpose: To evaluate patients with resolved versus confirmed ARDS, identify subgroups with substantial mortality risk, and to determine the utility of day 2 ARDS reclassification. Methods: Our primary objective, in this secondary LUNG SAFE analysis, was to compare outcome in patients with resolved versus confirmed ARDS after 24\ua0h. Secondary objectives included identifying factors associated with ARDS persistence and mortality, and the utility of day 2 ARDS reclassification. Results: Of 2377 patients fulfilling the ARDS definition on the first day of ARDS (day 1) and receiving invasive mechanical ventilation, 503 (24%) no longer fulfilled the ARDS definition the next day, 52% of whom initially had moderate or severe ARDS. Higher tidal volume on day 1 of ARDS was associated with confirmed ARDS [OR 1.07 (CI 1.01\u20131.13), P = 0.035]. Hospital mortality was 38% overall, ranging from 31% in resolved ARDS to 41% in confirmed ARDS, and 57% in confirmed severe ARDS at day 2. In both\ua0resolved and confirmed\ua0ARDS, age, non-respiratory SOFA score, lower PEEP and P/F ratio, higher peak pressure and respiratory rate were each\ua0associated with mortality. In confirmed ARDS, pH and the presence of immunosuppression or neoplasm were also associated\ua0with mortality. The increase in area under the receiver operating curve for ARDS reclassification on day 2 was marginal. Conclusions: ARDS, whether resolved or confirmed at day 2, has a high mortality rate. ARDS reclassification at day 2 has limited predictive value for mortality. The substantial mortality risk in severe confirmed ARDS suggests that complex interventions might best be tested in this population. Trial Registration: ClinicalTrials.gov NCT02010073. \ua9 2018, Springer-Verlag GmbH Germany, part of Springer Nature and ESICM

    Correction to: Potentially modifiable factors contributing to outcome from acute respiratory distress syndrome: the LUNG SAFE study

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    Correction to: Intensive Care Med (2016) 42:1865\u20131876 DOI 10.1007/s00134-016-4571-
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