Increasing the reliability of fully automated surveillance for central line–associated bloodstream infections

OBJECTIVETo increase reliability of the algorithm used in our fully automated electronic surveillance system by adding rules to better identify bloodstream infections secondary to other hospital-acquired infections.METHODSIntensive care unit (ICU) patients with positive blood cultures were reviewed. Central line–associated bloodstream infection (CLABSI) determinations were based on 2 sources: routine surveillance by infection preventionists, and fully automated surveillance. Discrepancies between the 2 sources were evaluated to determine root causes. Secondary infection sites were identified in most discrepant cases. New rules to identify secondary sites were added to the algorithm and applied to this ICU population and a non-ICU population. Sensitivity, specificity, predictive values, and kappa were calculated for the new models.RESULTSOf 643 positive ICU blood cultures reviewed, 68 (10.6%) were identified as central line–associated bloodstream infections by fully automated electronic surveillance, whereas 38 (5.9%) were confirmed by routine surveillance. New rules were tested to identify organisms as central line–associated bloodstream infections if they did not meet one, or a combination of, the following: (I) matching organisms (by genus and species) cultured from any other site; (II) any organisms cultured from sterile site; (III) any organisms cultured from skin/wound; (IV) any organisms cultured from respiratory tract. The best-fit model included new rules I and II when applied to positive blood cultures in an ICU population. However, they didn’t improve performance of the algorithm when applied to positive blood cultures in a non-ICU population.CONCLUSIONElectronic surveillance system algorithms may need adjustment for specific populations.Infect. Control Hosp. Epidemiol. 2015;36(12):1396–1400</jats:sec

Electronic surveillance for healthcare-associated central line-associated bloodstream infections outside the intensive care unit

Background.Manual surveillance for central line-associated bloodstream infections (CLABSIs) by infection prevention practitioners is time-consuming and often limited to intensive care units (ICUs). An automated surveillance system using existing databases with patient-level variables and microbiology data was investigated.Methods.Patients with a positive blood culture in 4 non-ICU wards at Barnes-Jewish Hospital between July 1, 2005, and December 31, 2006, were evaluated. CLABSI determination for these patients was made via 2 sources; a manual chart review and an automated review from electronically available data. Agreement between these 2 sources was used to develop the best-fit electronic algorithm that used a set of rules to identify a CLABSI. Sensitivity, specificity, predictive values, and Pearson's correlation were calculated for the various rule sets, using manual chart review as the reference standard.Results.During the study period, 391 positive blood cultures from 331 patients were evaluated. Eighty-five (22%) of these were confirmed to be CLABSI by manual chart review. The best-fit model included presence of a catheter, blood culture positive for known pathogen or blood culture with a common skin contaminant confirmed by a second positive culture and the presence of fever, and no positive cultures with the same organism from another sterile site. The best-performing rule set had an overall sensitivity of 95.2%, specificity of 97.5%, positive predictive value of 90%, and negative predictive value of 99.2% compared with intensive manual surveillance.Conclusions.Although CLABSIs were slightly overpredicted by electronic surveillance compared with manual chart review, the method offers the possibility of performing acceptably good surveillance in areas where resources do not allow for traditional manual surveillance.</jats:sec

Re-engineering a NiFe hydrogenase to increase the H2 production bias while maintaining native levels of O2 tolerance

Naturally occurring oxygen tolerant NiFe membrane bound hydrogenases have a conserved catalytic bias towards hydrogen oxidation which limits their technological value. We present an Escherichia coli Hyd-1 amino acid exchange that apparently causes the catalytic rate of H2 production to double but does not impact the O2 tolerance

Measuring Lattice Strain in Three Dimensions through Electron Microscopy

The three-dimensional (3D) atomic structure of nanomaterials, including strain, is crucial to understand their properties. Here, we investigate lattice strain in Au nanodecahedra using electron tomography. Although different electron tomography techniques enabled 3D characterizations of nanostructures at the atomic level, a reliable determination of lattice strain is not straightforward. We therefore propose a novel model-based approach from which atomic coordinates are

Long-Term Type 1 Diabetes Enhances In-Stent Restenosis after Aortic Stenting in Diabetes-Prone BB Rats

Type 1 diabetic patients have increased risk of developing in-stent restenosis following endovascular stenting. Underlying pathogenetic mechanisms are not fully understood partly due to the lack of a relevant animal model to study the effect(s) of long-term autoimmune diabetes on development of in-stent restenosis. We here describe the development of in-stent restenosis in long-term (~7 months) spontaneously diabetic and age-matched, thymectomized, nondiabetic Diabetes Prone BioBreeding (BBDP) rats (n = 6-7 in each group). Diabetes was suboptimally treated with insulin and was characterized by significant hyperglycaemia, polyuria, proteinuria, and increased HbA1c levels. Stented abdominal aortas were harvested 28 days after stenting. Computerized morphometric analysis revealed significantly increased neointima formation in long-term diabetic rats compared with nondiabetic controls. In conclusion, long-term autoimmune diabetes in BBDP rats enhances in-stent restenosis. This model can be used to study the underlying pathogenetic mechanisms of diabetes-enhanced in-stent restenosis as well as to test new therapeutic modalities

Assessment of animal hosts of pathogenic Leptospira in northern Tanzania

Funding: This work was supported by the Wellcome Trust (grant number 096400/Z/11/Z; https://wellcome.ac.uk/). JEBH, VPM, JAC, and SC received support from the Research Councils UK, UK Department for International Development, and UK Biotechnology and Biological Sciences Research Council (BBSRC) (grant numbers BB/J010367/1, BB/L018926, BB/L017679, BB/L018845; http://www.bbsrc.ac.uk/). JAC and VPM also received support from the US National Institutes of Health (NIH)-National Science Foundation (NSF) Ecology and Evolution of Infectious Disease program (R01TW009237; https://www.fic.nih.gov/programs/pages/ecology-infectious-diseases.aspx). MM received support from the BBSRC East of Scotland Bioscience Doctoral Training Partnership (http://www.eastscotbiodtp.ac.uk/). MJM received support from a University of Otago Frances G. Cotter Scholarship and a University of Otago MacGibbon PhD Travel Fellowship (http://www.otago.ac.nz/). VPM and JAC received support from the US National Institutes of Health National Institute for Allergy and Infectious (grant number R01 AI121378; https://www.niaid.nih.gov/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data Availability: Datasets supporting this manuscript are available through: http://dx.doi.org/10.5525/gla.researchdata.582. Unique sequences generated through this study are available through GenBank (accession numbers MF955862 to MF955882).Peer reviewedPublisher PD

An Assessment of CO2 Storage and Sea‐Air Fluxes for the Atlantic Ocean and Mediterranean Sea Between 1985 and 2018

As part of the second phase of the Regional Carbon Cycle Assessment and Processes project (RECCAP2), we present an assessment of the carbon cycle of the Atlantic Ocean, including the Mediterranean Sea, between 1985 and 2018 using global ocean biogeochemical models (GOBMs) and estimates based on surface ocean carbon dioxide (CO2) partial pressure (pCO2 products) and ocean interior dissolved inorganic carbon observations. Estimates of the basin-wide long-term mean net annual CO2 uptake based on GOBMs and pCO2 products are in reasonable agreement (−0.47 ± 0.15 PgC yr−1 and −0.36 ± 0.06 PgC yr−1, respectively), with the higher uptake in the GOBM-based estimates likely being a consequence of a deficit in the representation of natural outgassing of land derived carbon. In the GOBMs, the CO2 uptake increases with time at rates close to what one would expect from the atmospheric CO2 increase, but pCO2 products estimate a rate twice as fast. The largest disagreement in the CO2 flux between GOBMs and pCO2 products is found north of 50°N, coinciding with the largest disagreement in the seasonal cycle and interannual variability. The mean accumulation rate of anthropogenic CO2 (Cant) over 1994–2007 in the Atlantic Ocean is 0.52 ± 0.11 PgC yr−1 according to the GOBMs, 28% ± 20% lower than that derived from observations. Around 70% of this Cant is taken up from the atmosphere, while the remainder is imported from the Southern Ocean through lateral transport