Reduction in hospital-wide mortality after implementation of a rapidresponse team: a long-term cohort study

Introduction: Rapid response teams (RRTs) have been shown to reduce cardiopulmonary arrests outside the intensive care unit (ICU). Yet the utility of RRTs remains in question, as most large studies have failed to demonstrate a significant reduction in hospital-wide mortality after RRT implementation. Methods: A cohort design with historical controls was used to determine the effect on hospital-wide mortality of an RRT in which clinical judgment, in addition to vital-signs criteria, was widely promoted as a key trigger for activation. All nonprisoner patients admitted to a tertiary referral public teaching hospital from 2003 through 2008 were included. In total, 77, 021 admissions before RRT implementation (2003 through 2005) and 79, 013 admissions after RRT implementation (2006 through 2008) were evaluated. The a priori primary outcome was unadjusted hospital-wide mortality. A Poisson regression model was then used to adjust for hospital-wide mortality trends over time. Secondary outcomes defined a priori were unadjusted out-of-ICU mortality and out-of-ICU cardiopulmonary-arrest codes. Results: In total, 855 inpatient RRTs (10.8 per 1, 000 hospital-wide discharges) were activated during the 3-year postintervention period. Forty-seven percent of RRTs were activated for reasons of clinical judgment. Hospital-wide mortality decreased from 15.50 to 13.74 deaths per 1, 000 discharges after RRT implementation (relative risk, 0.887; 95% confidence interval (CI), 0.817 to 0.963; P = 0.004). After adjusting for inpatient mortality trends over time, the reduction in hospital-wide mortality remained statistically significant (relative risk, 0.825; 95% CI, 0.694 to 0.981; P = 0.029). Out-of-ICU mortality decreased from 7.08 to 4.61 deaths per 1, 000 discharges (relative risk, 0.651; 95% CI, 0.570 to 0.743; P < 0.001). Out-of-ICU cardiopulmonary-arrest codes decreased from 3.28 to 1.62 codes per 1, 000 discharges (relative risk, 0.493; 95% CI, 0.399 to 0.610; P < 0.001). Conclusions: Implementation of an RRT in which clinical judgment, in addition to vital-signs criteria, was widely cited as a rationale for activation, was associated with a significant reduction in hospital-wide mortality, out-of-ICU mortality, and out-of-ICU cardiopulmonary-arrest codes. The frequent use of clinical judgment as a criterion for RRT activation was associated with high RRT utilization

Criterion for traffic phases in single vehicle data and empirical test of a microscopic three-phase traffic theory

A microscopic criterion for distinguishing synchronized flow and wide moving jam phases in single vehicle data measured at a single freeway location is presented. Empirical local congested traffic states in single vehicle data measured on different days are classified into synchronized flow states and states consisting of synchronized flow and wide moving jam(s). Then empirical microscopic characteristics for these different local congested traffic states are studied. Using these characteristics and empirical spatiotemporal macroscopic traffic phenomena, an empirical test of a microscopic three-phase traffic flow theory is performed. Simulations show that the microscopic criterion and macroscopic spatiotemporal objective criteria lead to the same identification of the synchronized flow and wide moving jam phases in congested traffic. It is found that microscopic three-phase traffic models can explain both microscopic and macroscopic empirical congested pattern features. It is obtained that microscopic distributions for vehicle speed difference as well as fundamental diagrams and speed correlation functions can depend on the spatial co-ordinate considerably. It turns out that microscopic optimal velocity (OV) functions and time headway distributions are not necessarily qualitatively different, even if local congested traffic states are qualitatively different. The reason for this is that important spatiotemporal features of congested traffic patterns are it lost in these as well as in many other macroscopic and microscopic traffic characteristics, which are widely used as the empirical basis for a test of traffic flow models, specifically, cellular automata traffic flow models.Comment: 27 pages, 16 figure

Differences in the haematological profile of healthy 70 year old men and women: normal ranges with confirmatory factor analysis

<p>Abstract</p> <p>Background</p> <p>Reference ranges are available for different blood cell counts. These ranges treat each cell type independently and do not consider possible correlations between cell types.</p> <p>Methods</p> <p>Participants were identified from the Community Health Index as survivors of the 1947 Scottish Mental Survey, all born in 1936, who were resident in Lothian (potential n = 3,810) and invited to participate in the study. Those who consented were invited to attend a Clinical Research Facility where, amongst other assessments, blood was taken for full blood count. First we described cell count data and bivariate correlations. Next we performed principal components analysis to identify common factors. Finally we performed confirmatory factor analysis to evaluate suitable models explaining relationships between cell counts in men and women.</p> <p>Results</p> <p>We examined blood cell counts in 1027 community-resident people with mean age 69.5 (range 67.6-71.3) years. We determined normal ranges for each cell type using Q-Q plots which showed that these ranges were significantly different between men and women for all cell types except basophils. We identified three principal components explaining around 60% of total variance of cell counts. Varimax rotation indicated that these could be considered as erythropoietic, leukopoietic and thrombopoietic factors. We showed that these factors were distinct for men and women by confirmatory factor analysis: in men neutrophil count was part of a 'thrombopoietic' trait whereas for women it was part of a 'leukopoietic' trait.</p> <p>Conclusions</p> <p>First, normal ranges for haematological indices should be sex-specific; at present this only pertains to those associated with erythrocytes. Second, differences between individuals across a range of blood cell counts can be explained to a considerable extent by three major components, but these components are not the same in men and women.</p

Quantifying measures to limit wind driven resuspension of sediments for improvement of the ecological quality in some shallow Dutch lakes

Although phosphorus loadings are considered the main pressure for most shallow lakes, wind-driven resuspension can cause additional problems for these aquatic ecosystems. We quantified the potential effectiveness of measures to reduce the contribution of resuspended sediments, resulting from wind action, to the overall light attenuation for three comparable shallow peat lakes with poor ecological status in the Netherlands: Loosdrecht, Nieuwkoop, and Reeuwijk (1.8–2.7 m depth, 1.6–2.5 km fetch). These measures are: 1. wave reducing barriers, 2. water level fluctuations, 3. capping of the sediment with sand, and 4. combinations of above. Critical shear stress of the sediments for resuspension (Vcrit), size distribution, and optical properties of the suspended material were quantified in the field (June 2009) and laboratory. Water quality monitoring data (2002–2009) showed that light attenuation by organic suspended matter in all lakes is high. Spatial modeling of the impact of these measures showed that in Lake Loosdrecht limiting wave action can have significant effects (reductions from 6% exceedance to 2% exceedance of Vcrit), whereas in Lake Nieuwkoop and Lake Reeuwijk this is less effective. The depth distribution and shape of Lake Nieuwkoop and Lake Reeuwijk limit the role of wind-driven resuspension in the total suspended matter concentration. Although the lakes are similar in general appearance (origin, size, and depth range) measures suitable to improve their ecological status differ. This calls for care when defining the programme of measures to improve the ecological status of a specific lake based on experience from other lakes.

Dynamic summarization of bibliographic-based data

<p>Abstract</p> <p>Background</p> <p>Traditional information retrieval techniques typically return excessive output when directed at large bibliographic databases. Natural Language Processing applications strive to extract salient content from the excessive data. Semantic MEDLINE, a National Library of Medicine (NLM) natural language processing application, highlights relevant information in PubMed data. However, Semantic MEDLINE implements manually coded schemas, accommodating few information needs. Currently, there are only five such schemas, while many more would be needed to realistically accommodate all potential users. The aim of this project was to develop and evaluate a statistical algorithm that automatically identifies relevant bibliographic data; the new algorithm could be incorporated into a dynamic schema to accommodate various information needs in Semantic MEDLINE, and eliminate the need for multiple schemas.</p> <p>Methods</p> <p>We developed a flexible algorithm named Combo that combines three statistical metrics, the Kullback-Leibler Divergence (KLD), Riloff's RlogF metric (RlogF), and a new metric called PredScal, to automatically identify salient data in bibliographic text. We downloaded citations from a PubMed search query addressing the genetic etiology of bladder cancer. The citations were processed with SemRep, an NLM rule-based application that produces semantic predications. SemRep output was processed by Combo, in addition to the standard Semantic MEDLINE genetics schema and independently by the two individual KLD and RlogF metrics. We evaluated each summarization method using an existing reference standard within the task-based context of genetic database curation.</p> <p>Results</p> <p>Combo asserted 74 genetic entities implicated in bladder cancer development, whereas the traditional schema asserted 10 genetic entities; the KLD and RlogF metrics individually asserted 77 and 69 genetic entities, respectively. Combo achieved 61% recall and 81% precision, with an F-score of 0.69. The traditional schema achieved 23% recall and 100% precision, with an F-score of 0.37. The KLD metric achieved 61% recall, 70% precision, with an F-score of 0.65. The RlogF metric achieved 61% recall, 72% precision, with an F-score of 0.66.</p> <p>Conclusions</p> <p>Semantic MEDLINE summarization using the new Combo algorithm outperformed a conventional summarization schema in a genetic database curation task. It potentially could streamline information acquisition for other needs without having to hand-build multiple saliency schemas.</p

Elucidation of the Mode of Action of a New Antibacterial Compound Active against Staphylococcus aureus and Pseudomonas aeruginosa.

Nosocomial and community-acquired infections caused by multidrug resistant bacteria represent a major human health problem. Thus, there is an urgent need for the development of antibiotics with new modes of action. In this study, we investigated the antibacterial characteristics and mode of action of a new antimicrobial compound, SPI031 (N-alkylated 3, 6-dihalogenocarbazol 1-(sec-butylamino)-3-(3,6-dichloro-9H-carbazol-9-yl)propan-2-ol), which was previously identified in our group. This compound exhibits broad-spectrum antibacterial activity, including activity against the human pathogens Staphylococcus aureus and Pseudomonas aeruginosa. We found that SPI031 has rapid bactericidal activity (7-log reduction within 30 min at 4x MIC) and that the frequency of resistance development against SPI031 is low. To elucidate the mode of action of SPI031, we performed a macromolecular synthesis assay, which showed that SPI031 causes non-specific inhibition of macromolecular biosynthesis pathways. Liposome leakage and membrane permeability studies revealed that SPI031 rapidly exerts membrane damage, which is likely the primary cause of its antibacterial activity. These findings were supported by a mutational analysis of SPI031-resistant mutants, a transcriptome analysis and the identification of transposon mutants with altered sensitivity to the compound. In conclusion, our results show that SPI031 exerts its antimicrobial activity by causing membrane damage, making it an interesting starting point for the development of new antibacterial therapies

The antimicrobial effects of the alginate oligomer OligoG CF-5/20 are independent of direct bacterial cell membrane disruption

Concerns about acquisition of antibiotic resistance have led to increasing demand for new antimicrobial therapies. OligoG CF-5/20 is an alginate oligosaccharide previously shown to have antimicrobial and antibiotic potentiating activity. We investigated the structural modification of the bacterial cell wall by OligoG CF-5/20 and its effect on membrane permeability. Binding of OligoG CF-5/20 to the bacterial cell surface was demonstrated in Gram-negative bacteria. Permeability assays revealed that OligoG CF-5/20 had virtually no membrane-perturbing effects. Lipopolysaccharide (LPS) surface charge and aggregation were unaltered in the presence of OligoG CF-5/20. Small angle neutron scattering and circular dichroism spectroscopy showed no substantial change to the structure of LPS in the presence of OligoG CF-5/20, however, isothermal titration calorimetry demonstrated a weak calcium-mediated interaction. Metabolomic analysis confirmed no change in cellular metabolic response to a range of osmolytes when treated with OligoG CF-5/20. This data shows that, although weak interactions occur between LPS and OligoG CF-5/20 in the presence of calcium, the antimicrobial effects of OligoG CF-5/20 are not related to the induction of structural alterations in the LPS or cell permeability. These results suggest a novel mechanism of action that may avoid the common route in acquisition of resistance via LPS structural modification

Supreme activity of gramicidin S against resistant, persistent and biofilm cells of staphylococci and enterococci.

Three promising antibacterial peptides were studied with regard to their ability to inhibit the growth and kill the cells of clinical strains of Staphylococcus aureus, Enterococcus faecalis and Enterococcus faecium. The multifunctional gramicidin S (GS) was the most potent, compared to the membranotropic temporin L (TL), being more effective than the innate-defence regulator IDR-1018 (IDR). These activities, compared across 16 strains as minimal bactericidal and minimal inhibitory concentrations (MIC), are independent of bacterial resistance pattern, phenotype variations and/or biofilm-forming potency. For S. aureus strains, complete killing is accomplished by all peptides at 5 × MIC. For E. faecalis strains, only GS exhibits a rapid bactericidal effect at 5 × MIC, while TL and IDR require higher concentrations. The biofilm-preventing activities of all peptides against the six strains with the largest biofilm biomass were compared. GS demonstrates the lowest minimal biofilm inhibiting concentrations, whereas TL and IDR are consistently less effective. In mature biofilms, only GS completely kills the cells of all studied strains. We compare the physicochemical properties, membranolytic activities, model pharmacokinetics and eukaryotic toxicities of the peptides and explain the bactericidal, antipersister and antibiofilm activities of GS by its elevated stability, pronounced cell-penetration ability and effective utilization of multiple modes of antibacterial action

Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian Randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated by using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming available, and will facilitate this form of analysis. We describe some of the methodological issues that arise in this type of analysis, which we illustrate by considering how Mendelian Randomization could be used to estimate the causal impact of obesity, a complex trait, on healthcare costs. We describe some of the data sources that could be used for this type of analysis. We conclude by considering the challenges and opportunities offered by Mendelian Randomization for economic evaluation