SUMMARYBackground.Bloodstream infection (BSI) is a major cause of morbidity and mortality throughout the world. Rapid identification of bloodstream pathogens is a laboratory practice that supports strategies for rapid transition to direct targeted therapy by providing for timely and effective patient care. In fact, the more rapidly that appropriate antimicrobials are prescribed, the lower the mortality for patients with sepsis. Rapid identification methods may have multiple positive impacts on patient outcomes, including reductions in mortality, morbidity, hospital lengths of stay, and antibiotic use. In addition, the strategy can reduce the cost of care for patients with BSIs.Objectives.The purpose of this review is to evaluate the evidence for the effectiveness of three rapid diagnostic practices in decreasing the time to targeted therapy for hospitalized patients with BSIs. The review was performed by applying the Centers for Disease Control and Prevention's (CDC's) Laboratory Medicine Best Practices Initiative (LMBP) systematic review methods for quality improvement (QI) practices and translating the results into evidence-based guidance (R. H. Christenson et al., Clin Chem 57:816–825, 2011, http://dx.doi.org/10.1373/clinchem.2010.157131).Search strategy.A comprehensive literature search was conducted to identify studies with measurable outcomes. A search of three electronic bibliographic databases (PubMed, Embase, and CINAHL), databases containing “gray” literature (unpublished academic, government, or industry evidence not governed by commercial publishing) (CIHI, NIHR, SIGN, and other databases), and the Cochrane database for English-language articles published between 1990 and 2011 was conducted in July 2011.Dates of search.The dates of our search were from 1990 to July 2011.Selection criteria.Animal studies and non-English publications were excluded. The search contained the following medical subject headings: bacteremia; bloodstream infection; time factors; health care costs; length of stay; morbidity; mortality; antimicrobial therapy; rapid molecular techniques, polymerase chain reaction (PCR); in situ hybridization, fluorescence; treatment outcome; drug therapy; patient care team; pharmacy service, hospital; hospital information systems; Gram stain; pharmacy service; and spectrometry, mass, matrix-assisted laser desorption-ionization. Phenotypic as well as the following key words were searched: targeted therapy; rapid identification; rapid; Gram positive; Gram negative; reduce(ed); cost(s); pneumoslide; PBP2; tube coagulase; matrix-assisted laser desorption/ionization time of flight; MALDI TOF; blood culture; EMR; electronic reporting; call to provider; collaboration; pharmacy; laboratory; bacteria; yeast; ICU; and others. In addition to the electronic search being performed, a request for unpublished quality improvement data was made to the clinical laboratory community.Main results.Rapid molecular testing with direct communication significantly improves timeliness compared to standard testing. Rapid ...

Objective To examine the extent to which the perception of sweet and other flavours is associated with liking and disliking of flavoured electronic cigarettes (e-cigarettes). Methods 31 participants (13 females/18 males; 12 sole/19 dual users) vaped 6 commercially available flavours of blu Tanks: Classic Tobacco (CT), Magnificent Menthol (MM), Cherry Crush (CC), Vivid Vanilla (VV), Piña Colada (PC) and Peach Schnapps (PS); all ‘medium’ strength, 12 mg/mL nicotine concentration. For each flavoured e-cigarette, participants first rated liking/disliking on the Labeled Hedonic Scale, followed by perceived intensities of sweetness, coolness, bitterness, harshness and specific flavour on the generalised version of the Labeled Magnitude Scale. The psychophysical testing was conducted individually in an environmental chamber. Results PC was perceived as sweetest and liked the most; CT was perceived as least sweet and liked the least. Across all flavours, liking was correlated with sweetness (r=0.31), coolness (r=0.25), bitterness (r=−0.25) and harshness (r=−0.29, all p<0.001). Specifically, liking was positively correlated with sweetness of PS (r=0.56, p=0.001) and PC (r=0.36, p=0.048); and with coolness of MM, CT and VV (r=0.41–0.52, p<0.05). In contrast, harshness was negatively correlated with liking for CC, PC and PS (r=0.37–0.40, p<0.05). In a multivariate model, sweetness had the greatest positive impact on liking followed by coolness; harshness had the greatest negative impact on liking. Conclusions Our findings indicate that bitterness and harshness, most likely from nicotine, have negative impacts on the liking of e-cigarettes, but the addition of flavourants that elicit sweetness or coolness generally improves liking. The results suggest that flavours play an important role in e-cigarette preference and most likely use.

Atmospheric concentrations of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and pesticides were compared at Brule River and Eagle Harbor, two rural sites on Lake Superior that are part of the Integrated Atmospheric Deposition Network (IADN). Brule River lies 40 km southwest of Duluth, MN, a small industrial city, and Eagle Harbor is in Michigan's upper peninsula, 400 km east of Brule River. Pesticide and PCB concentrations were similar at both sites. Day-by-day regression analyses of the data showed that PAH concentrations, an indication of urban contamination, were significantly higher at Brule Riverthan at Eagle Harbor. Concentration ranges for all compounds at both sites were well within global background levels, despite the differences observed between the two sites. Clearly, pollution from Duluth is influencing PAH concentrations at Brule River more than at Eagle Harbor.

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Data through 2001 from the Integrated Atmospheric Deposition Network (IADN) were used to investigate the causes of variability in gas-phase polychlorinated biphenyl (PCB) and pesticide concentrations measured near Lakes Michigan, Erie, and Superior. A multiple linear regression model that incorporates temperature and time was used explain the variability in the concentrations. Our approach used autocorrelation analyses of the residuals to help us determine the effectiveness of the regression. Autocorrelation plots forthe in-use pesticide lindane indicated that an agricultural application cycle was also present in the regression residual data at all sites. The addition of parameters for this effect to the regression equation accounted for, on average, 16% more of the variability in the data. Similar analyses forthe in-use pesticide endosulfan did not show an agricultural application effect. The banned compounds DDT and chlordane showed that temperature and time correctly accounted for the variability in the atmospheric concentrations of these compounds at all sites. In contrast to the other compounds, PCBs and hexachlorobenzene showed strong residual autocorrelation patterns near Lake Michigan of an unknown origin.