High-Fidelity Simulation Nurse Training Reduces Unplanned Interruption of Continuous Renal Replacement Therapy Sessions in Critically Ill Patients: The SimHeR Randomized Controlled Trial

BACKGROUND: Although continuous renal replacement therapy (CRRT) is common, unplanned interruptions (UI) often limit its usefulness. In many units, nurses are responsible for CRRT management. We hypothesized that a nurse training program based on high-fidelity simulation would reduce the rate of interrupted sessions. METHODS: We performed a 2-phase (training and evaluation), randomized, single-center, open study: During the training phase, intensive care unit nurses underwent a 6-hour training program and were randomized to receive (intervention) or not (control) an additional high-fidelity simulation training (6 hours). During the evaluation phase, management of CRRT sessions was randomized to either intervention or control nurses. Sessions were defined as UI if they were interrupted and the interruption was not prescribed in writing more than 3 hours before. RESULTS: Study nurses had experience with hemodialysis, but no experience with CRRT before training. Intervention nurses had higher scores than control nurses on the knowledge tests (grade, median [Q1-Q3], 14 [10.5-15] vs 11 [10-12]/20; P = .044). During a 13-month period, 106 sessions were randomized (n = 53/group) among 50 patients (mean age 70 ± 13 years, mean simplified acute physiology II score 69 [54-96]). Twenty-one sessions were not analyzed (4 were not performed and 17 patients died during sessions). Among the 42 intervention and 43 control sessions analyzed, 25 (59%) and 38 (88%) were labeled as UI (relative risk [95% CI], 0.67 [0.51-0.88]; P = .002). Intervention nurses required help significantly less frequently (0 [0-1] vs 3 [1-4] times/session; P < .0001). The 2 factors associated with UI in multilevel mixed-effects logistic regression were Sequential Organ Failure Assessment score (odds ratio [95% CI], 0.81 [0.65-99]; P = .047) and the intervention group (odds ratio, 0.19 [0.05-0.73]; P = .015). CONCLUSIONS: High-fidelity simulation nurse training reduced the rate of UI of CRRT sessions and the need for nurses to request assistance. This intervention may be particularly useful in the context of frequent nursing staff turnover

Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses

1H NMR (nuclear magnetic resonance spectroscopy) has been used for metabolomic analysis of ‘Riesling’ and ‘Mueller-Thurgau’ white wines from the German Palatinate region. Diverse two-dimensional NMR techniques have been applied for the identification of metabolites, including phenolics. It is shown that sensory analysis correlates with NMR-based metabolic profiles of wine. 1H NMR data in combination with multivariate data analysis methods, like principal component analysis (PCA), partial least squares projections to latent structures (PLS), and bidirectional orthogonal projections to latent structures (O2PLS) analysis, were employed in an attempt to identify the metabolites responsible for the taste of wine, using a non-targeted approach. The high quality wines were characterized by elevated levels of compounds like proline, 2,3-butanediol, malate, quercetin, and catechin. Characterization of wine based on type and vintage was also done using orthogonal projections to latent structures (OPLS) analysis. ‘Riesling’ wines were characterized by higher levels of catechin, caftarate, valine, proline, malate, and citrate whereas compounds like quercetin, resveratrol, gallate, leucine, threonine, succinate, and lactate, were found discriminating for ‘Mueller-Thurgau’. The wines from 2006 vintage were dominated by leucine, phenylalanine, citrate, malate, and phenolics, while valine, proline, alanine, and succinate were predominantly present in the 2007 vintage. Based on these results, it can be postulated the NMR-based metabolomics offers an easy and comprehensive analysis of wine and in combination with multivariate data analyses can be used to investigate the source of the wines and to predict certain sensory aspects of wine

Influence of segregation on the measurement of stress in thin films

International audienceThe force that a deposited film A exerts on its substrate B is usually written as the sum of volumetric and surface and interface contributions. In the simplest case pseudomorphous film, absence of segregation, volumetric and surface contributions can be easily separated through simple force measurements. In this article, we show that, in the presence of segregation, only simultaneous in situ stress, strain, and composition measurements allow the proper analysis of stress establishment in thin films. For this purpose, we discuss how segregation influences both volumetric and surface stresses. More precisely, we show that 1 the separation between a surface and a volumetric stress can be meaningless when segregation occurs; 2 one should carefully distinguish between the true physical thickness and the deposited thickness; 3 surface strain should be accounted for in the analysis of the experimental diffraction data; and 4 when the elastic modulus misfit between film and substrate cannot be neglected the total stress depends explicitly on the shape of the concentration profile

Influence of the substrate on the solid-state reaction of ultra-thin Ni film with a In0.53_{0.53}Ga0.47_{0.47}As under-layer by means of full 3D reciprocal space mapping

International audienceWe studied the solid-state reaction of Ni thin films with InGaAs layers grown on InP or Si substrates. The inter-metallics obtained carried an hexagonal structure, but yielded a difference in orientation regarding either the substrates or the annealing temperature