To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers
of an area covered by the Dark Energy Survey, reaching a depth of 25–30
rms at a spatial resolution of
11–18 arcsec, resulting in a catalogue of
220 000 sources, of which
180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.
To determine the impact of electronic health record (EHR)–based interventions and test restriction on Clostridioides difficile tests (CDTs) and hospital-onset C. difficile infection (HO-CDI).
Quasi-experimental study in 3 hospitals.
957-bed academic (hospital A), 354-bed (hospital B), and 175-bed (hospital C) academic-affiliated community hospitals.
Three EHR-based interventions were sequentially implemented: (1) alert when ordering a CDT if laxatives administered within 24 hours (January 2018); (2) cancellation of CDT orders after 24 hours (October 2018); (3) contextual rule-driven order questions requiring justification when laxative administered or lack of EHR documentation of diarrhea (July 2019). In February 2019, hospital C implemented a gatekeeper intervention requiring approval for all CDTs after hospital day 3. The impact of the interventions on C. difficile testing and HO-CDI rates was estimated using an interrupted time-series analysis.
C. difficile testing was already declining in the preintervention period (annual change in incidence rate [IR], 0.79; 95% CI, 0.72–0.87) and did not decrease further with the EHR interventions. The laxative alert was temporally associated with a trend reduction in HO-CDI (annual change in IR from baseline, 0.85; 95% CI, 0.75–0.96) at hospitals A and B. The gatekeeper intervention at hospital C was associated with level (IRR, 0.50; 95% CI, 0.42-0.60) and trend reductions in C. difficile testing (annual change in IR, 0.91; 95% CI, 0.85–0.98) and level (IRR 0.42; 95% CI, 0.22–0.81) and trend reductions in HO-CDI (annual change in IR, 0.68; 95% CI, 0.50–0.92) relative to the baseline period.
Test restriction was more effective than EHR-based clinical decision support to reduce C. difficile testing in our 3-hospital system.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
We implemented universal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing of patients undergoing surgical procedures as a means to conserve personal protective equipment (PPE). The rate of asymptomatic coronavirus disease 2019 (COVID-19) was <0.5%, which suggests that early local public health interventions were successful. Although our protocol was resource intensive, it prevented exposures to healthcare team members.
Influenza A (H1N1) pdm09 became the predominant circulating strain in the United States during the 2013–2014 influenza season. Little is known about the epidemiology of severe influenza during this season.
A retrospective cohort study of severely ill patients with influenza infection in intensive care units in 33 US hospitals from September 1, 2013, through April 1, 2014, was conducted to determine risk factors for mortality present on intensive care unit admission and to describe patient characteristics, spectrum of disease, management, and outcomes.
A total of 444 adults and 63 children were admitted to an intensive care unit in a study hospital; 93 adults (20.9%) and 4 children (6.3%) died. By logistic regression analysis, the following factors were significantly associated with mortality among adult patients: older age (>65 years, odds ratio, 3.1 [95% CI, 1.4–6.9], P=.006 and 50–64 years, 2.5 [1.3–4.9], P=.007; reference age 18–49 years), male sex (1.9 [1.1–3.3], P=.031), history of malignant tumor with chemotherapy administered within the prior 6 months (12.1 [3.9–37.0], P<.001), and a higher Sequential Organ Failure Assessment score (for each increase by 1 in score, 1.3 [1.2–1.4], P<.001).
Risk factors for death among US patients with severe influenza during the 2013–2014 season, when influenza A (H1N1) pdm09 was the predominant circulating strain type, shifted in the first postpandemic season in which it predominated toward those of a more typical epidemic influenza season.
Infect. Control Hosp. Epidemiol. 2015;36(11):1251–1260
This paper presents the use of data clustering methods applied to the analysis results of a design-stage, functional failure reasoning tool. A system simulation using qualitative descriptions of component behaviors and a functional reasoning tool are used to identify the functional impact of a large set of potential single and multiple fault scenarios. The impact of each scenario is collected as the set of categorical function “health” states for each component-level function in the system. This data represents the space of potential system states. The clustering and statistical tools presented in this paper are used to identify patterns in this system state space. These patterns reflect the underlying emergent failure behavior of the system. Specifically, two data analysis tools are presented and compared. First, a modified k-means clustering algorithm is used with a distance metric of functional effect similarity. Second, a statistical approach known as latent class analysis is used to find an underlying probability model of potential system failure states. These tools are used to reason about how the system responds to complex fault scenarios and assists in identifying potential design changes for fault mitigation. As computational power increases, the ability to reason with large sets of data becomes as critical as the analysis methods used to collect that data. The goal of this work is to provide complex system designers with a means of using early design simulation data to identify and mitigate potential emergent failure behavior.
A freestanding, 911-receiving emergency department was implemented at Bellevue Hospital Center during the recovery efforts after Hurricane Sandy to compensate for the increased volume experienced at nearby hospitals. Because inpatient services at several hospitals remained closed for months, emergency volume increased significantly. Thus, in collaboration with the New York State Department of Health and other partners, the Health and Hospitals Corporation and Bellevue Hospital Center opened a freestanding emergency department without on-site inpatient care. The successful operation of this facility hinged on key partnerships with emergency medical services and nearby hospitals. Also essential was the establishment of an emergency critical care ward and a system to monitor emergency department utilization at affected hospitals. The results of this experience, we believe, can provide a model for future efforts to rebuild emergency care capacity after a natural disaster such as Hurricane Sandy. (Disaster Med Public Health Preparedness. 2014;0:1-4)
The core clinical competencies in anesthesiology can be pretty blurry - just how do they apply to real life? This book answers this question, incorporating the core clinical competencies into an engaging format that anesthesiologists like - case studies. So, far from being a 'dry and dusty volume of forgotten lore', this book actually makes learning the competencies fun! Written in the same engaging style as a number of other anesthesia books (specifically, the Board Stiff opus) by leading anesthesiologists from leading medical centers across the United States, this book will bring the core clinical competencies to life for medical students.