Variable performance of models for predicting methicillin-resistant Staphylococcus aureus carriage in European surgical wards

BACKGROUND: Predictive models to identify unknown methicillin-resistant Staphylococcus aureus (MRSA) carriage on admission may optimise targeted MRSA screening and efficient use of resources. However, common approaches to model selection can result in overconfident estimates and poor predictive performance. We aimed to compare the performance of various models to predict previously unknown MRSA carriage on admission to surgical wards. METHODS: The study analysed data collected during a prospective cohort study which enrolled consecutive adult patients admitted to 13 surgical wards in 4 European hospitals. The participating hospitals were located in Athens (Greece), Barcelona (Spain), Cremona (Italy) and Paris (France). Universal admission MRSA screening was performed in the surgical wards. Data regarding demographic characteristics and potential risk factors for MRSA carriage were prospectively collected during the study period. Four logistic regression models were used to predict probabilities of unknown MRSA carriage using risk factor data: 'Stepwise' (variables selected by backward elimination); 'Best BMA' (model with highest posterior probability using Bayesian model averaging which accounts for uncertainty in model choice); 'BMA' (average of all models selected with BMA); and 'Simple' (model including variables selected >50% of the time by both Stepwise and BMA approaches applied to repeated random sub-samples of 50% of the data). To assess model performance, cross-validation against data not used for model fitting was conducted and net reclassification improvement (NRI) was calculated. RESULTS: Of 2,901 patients enrolled, 111 (3.8%) were newly identified MRSA carriers. Recent hospitalisation and presence of a wound/ulcer were significantly associated with MRSA carriage in all models. While all models demonstrated limited predictive ability (mean c-statistics <0.7) the Simple model consistently detected more MRSA-positive individuals despite screening fewer patients than the Stepwise model. Moreover, the Simple model improved reclassification of patients into appropriate risk strata compared with the Stepwise model (NRI 6.6%, P = .07). CONCLUSIONS: Though commonly used, models developed using stepwise variable selection can have relatively poor predictive value. When developing MRSA risk indices, simpler models, which account for uncertainty in model selection, may better stratify patients' risk of unknown MRSA carriage

Phylogeny of culex theileri virus flavivirus in Spain, Myanmar, Portugal and Turkey

Objective: To study the genetic diversity of Culex theileri flavivirus and the spread of this virus among Spain, Portugal and Turkey. Methods: A database consisting of 55 sequences of the NS5/3’UTR region of Culex theileri flavivirus group downloaded from GenBank were aligned and manual edited with Bioedit. ModelTest v. 3.7 was used to select the simplest evolutionary model that adequately fitted the sequence data. Maximum likelihood analysis was performed using MEGA7. The phylogenetic signal of the dataset was investigated by the likelihood mapping analysis. Results: The phylogenetic tree showed three clusters. Myanmar sequences clusterd together with Turkish sequences, Spain and Portugal strains grouped together and two Turkish sequences grouped separately. Selective pressure analysis showed a moderate percentage of sites (22.5%) under pervasive negative selection and only 1% under pervasive positive selection. The sites subject to selective pressure in CTFV RdRp NS5 fragments have been located onto the predicted three-dimensional structure. Conclusions: Phylogenetic and evolutionary analysis can be an important tool for understanding the evolutionary impact of the probable contemporary existence between non-pathogenic and pathogenic flaviviruses among these vectors

Variable performance of models for predicting methicillin-resistant Staphylococcus aureus carriage in European surgical wards

Predictive models to identify unknown methicillin-resistant Staphylococcus aureus (MRSA) carriage on admission may optimise targeted MRSA screening and efficient use of resources. However, common approaches to model selection can result in overconfident estimates and poor predictive performance. We aimed to compare the performance of various models to predict previously unknown MRSA carriage on admission to surgical wards

Mayaro virus infection, the next epidemic wave after Zika? Evolutionary and structural analysis

Objective: To evaluate the evolution of the pathogen Mayaro virus, causing Mayaro fever (a mosquito-borne disease) and to perform selective pressure analysis and homology modelling. Methods: Nine different datasets were built, one for each protein (from protein C to non-structural protein 4) and the last one for the complete genome. Selective pressure and homology modelling analyses were applied. Results: Two main clades (A and B) were pointed in the maximum likelihood tree. The clade A included five Brazilian sequences sampled from 1955 to 2015. The Brazilian sequence sampled in 2014 significantly clustered with the Haitian sequence sampled in 2015. The clade B included the remaining 27 sequences sampled in the Central and Southern America from 1957 to 2013. Selective pressure analysis revealed several sites under episodic diversifying selection in envelope surface glycoprotein E1, non-structural protein 1 and non- structural protein 3 with a posterior probability P≤0.01. Homology modelling showed different sites modified by selective pressure and some protein-protein interaction sites at high interaction propensity. Conclusion: Maximum likelihood analysis confirmed the Mayaro virus previous circulation in Haiti and the successful spread to the Caribbean and USA. Selective pressure analysis revealed a strong presence of negatively selected sites, suggesting a probable purging of deleterious polymorphisms in functional genes. Homology model showed the position 31, under selective pressure, located in the edge of the ADP-ribose binding site predicting to possess a high potential of protein-protein interaction and suggesting the possible chance for a protective vaccine, thus preventing Mayaro virus urbanization as with Chikungunya virus

The CuCl2/Al2O3 Catalyst Investigated in Interaction with Reagents

Alumina supported CuCl2, the basic catalyst for ethylene oxychlorination, has been investigated by UV-Vis spectroscopy, EPR, EXAFS and XANES in a wide range (0.25-9.0 wt%) of Cu concentration. We have evidenced that, at low Cu content, the formation of a surface aluminate species takes place. The formation of this surface copper aluminate stops at 0.95 wt% Cu / 100 m2; at higher Cu concentrations excess copper chloride precipitates directly from solution during the drying step forming an highly dispersed CuCl2.H2O, phase, overlapping progressively the surface aluminate. Depletion tests and IR spectroscopy of adsorbed NO have demonstrated that the latter is the only active phase. A complete catalytic cycle has then been performed on CuCl2/Al2O3 catalyst. EPR, XANES and EXAFS, have been used to demonstrate that the ethylene oxychlorination reaction: C2H4 + 2HCl + ½ O2 --> C2H4Cl2 + H2O follows a three steps mechanism: (i) reduction of CuCl2 to CuCl (2CuCl2 + C2H4 --> C2H4Cl2 + 2CuCl), (ii) oxidation of CuCl to give an oxychloride (2CuCl + ½ O2 --> Cu2OCl2) and (iii) closure of the catalytic circle by rechlorination with HCl, restoring the original CuCl2 (Cu2OCl2 + 2HCl --> 2CuCl2 + H2O). Finally, we have shown that time resolved, in situ, spectroscopy is a very promising technique to investigate the interplay between catalyst activity and oxidation state of copper

Variable performance of models for predicting methicillin-resistant Staphylococcus aureus carriage in European surgical wards

BACKGROUND: Predictive models to identify unknown methicillin-resistant Staphylococcus aureus (MRSA) carriage on admission may optimise targeted MRSA screening and efficient use of resources. However, common approaches to model selection can result in overconfident estimates and poor predictive performance. We aimed to compare the performance of various models to predict previously unknown MRSA carriage on admission to surgical wards. METHODS: The study analysed data collected during a prospective cohort study which enrolled consecutive adult patients admitted to 13 surgical wards in 4 European hospitals. The participating hospitals were located in Athens (Greece), Barcelona (Spain), Cremona (Italy) and Paris (France). Universal admission MRSA screening was performed in the surgical wards. Data regarding demographic characteristics and potential risk factors for MRSA carriage were prospectively collected during the study period. Four logistic regression models were used to predict probabilities of unknown MRSA carriage using risk factor data: 'Stepwise' (variables selected by backward elimination); 'Best BMA' (model with highest posterior probability using Bayesian model averaging which accounts for uncertainty in model choice); 'BMA' (average of all models selected with BMA); and 'Simple' (model including variables selected >50% of the time by both Stepwise and BMA approaches applied to repeated random sub-samples of 50% of the data). To assess model performance, cross-validation against data not used for model fitting was conducted and net reclassification improvement (NRI) was calculated. RESULTS: Of 2,901 patients enrolled, 111 (3.8%) were newly identified MRSA carriers. Recent hospitalisation and presence of a wound/ulcer were significantly associated with MRSA carriage in all models. While all models demonstrated limited predictive ability (mean c-statistics <0.7) the Simple model consistently detected more MRSA-positive individuals despite screening fewer patients than the Stepwise model. Moreover, the Simple model improved reclassification of patients into appropriate risk strata compared with the Stepwise model (NRI 6.6%, P = .07). CONCLUSIONS: Though commonly used, models developed using stepwise variable selection can have relatively poor predictive value. When developing MRSA risk indices, simpler models, which account for uncertainty in model selection, may better stratify patients' risk of unknown MRSA carriage

Hand hygiene practices and adherence determinants in surgical wards across Europe and Israel: A multicenter observational study

We examined hand hygiene practices in surgical wards in 9 countries in Europe and Israel through direct practice observation. There was marked interhospital variation in hand hygiene compliance (range, 14%-76%), as well as glove and alcohol-based handrub use. After multivariable analysis, surgical subspecialty, professional category, type of care activity, and workload were independently associated with compliance. Hand hygiene practices are influenced by numerous factors, and a tailored approach may be required to improve practices

Käytännön kosteikkosuunnittelu

Maatalouden vesiensuojelua edistetään monin tavoin. Ravinteita ja eroosioainesta sisältäviä valumavesiä pyritään puhdistamaan erilaisissa kosteikoissa. Tämä opas on kirjoitettu avuksi pienimuotoisten kosteikkojen perustamiseen. Oppaassa esitetään käytännönläheisesti kosteikon toteuttamisen eri vaiheet paikan valinnasta suunnitteluun ja rakentamiseen. Vuonna 2010 julkaistun painoksen tiedot on saatettu ajantasalle. Julkaisu on toteutettu osana Tehoa maatalouden vesiensuojeluun (TEHO) -hanketta ja päivitetty TEHO Plus -hankkeen toimesta. Oppaan toivotaan lisäävän kiinnostusta kosteikkojen suunnitteluun ja edelleen niiden rakentamiseen