Objectives: Results of pre-post intervention studies of sepsis early warning systems have been mixed, and randomized clinical trials showing efficacy in the emergency department setting are lacking. Additionally, early warning systems can be resource-intensive and may cause unintended consequences such as antibiotic or IV fluid overuse. We assessed the impact of a pharmacist and provider facing sepsis early warning systems on timeliness of antibiotic administration and sepsis-related clinical outcomes in our setting.
Design: A randomized, controlled quality improvement initiative.
Setting: The main emergency department of an academic, safety-net healthcare system from August to December 2019.
Patients: Adults presenting to the emergency department.
Intervention: Patients were randomized to standard sepsis care or standard care augmented by the display of a sepsis early warning system-triggered flag in the electronic health record combined with electronic health record-based emergency department pharmacist notification.
Measurements And Main Results: The primary process measure was time to antibiotic administration from arrival. A total of 598 patients were included in the study over a 5-month period (285 in the intervention group and 313 in the standard care group). Time to antibiotic administration from emergency department arrival was shorter in the augmented care group than that in the standard care group (median, 2.3 hr [interquartile range, 1.4-4.7 hr] vs 3.0 hr [interquartile range, 1.6-5.5 hr]; p = 0.039). The hierarchical composite clinical outcome measure of days alive and out of hospital at 28 days was greater in the augmented care group than that in the standard care group (median, 24.1 vs 22.5 d; p = 0.011). Rates of fluid resuscitation and antibiotic utilization did not differ.
Conclusions: In this single-center randomized quality improvement initiative, the display of an electronic health record-based sepsis early warning system-triggered flag combined with electronic health record-based pharmacist notification was associated with shorter time to antibiotic administration without an increase in undesirable or potentially harmful clinical interventions.
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Viruses
January 2025
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Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
Crimean-Congo hemorrhagic fever (CCHF) is a serious tick-borne disease with a wide geographical distribution. Classified as a level 4 biosecurity risk pathogen, CCHF can be transmitted cross-species due to its aerosol infectivity and ability to cause severe hemorrhagic fever outbreaks with high morbidity and mortality. However, current methods for detecting anti-CCHFV antibodies are limited.
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January 2025
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.
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January 2025
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China.
Water pipelines in water diversion projects can leak, leading to soil deformation and ground subsidence, necessitating research into soil deformation monitoring technology. This study conducted model tests to monitor soil deformation around leaking buried water pipelines using distributed fiber optic strain sensing (DFOSS) technology based on optical frequency domain reflectometry (OFDR). By arranging strain measurement fibers in a pipe-soil model, we investigated how leak location, leak size, pipe burial depth, and water flow velocity affect soil strain field monitoring results.
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January 2025
Department Neuromed & Movement Science, Norwegian University of Science & Technology (NTNU), 7034 Trondheim, Norway.
The rising burden of type 2 diabetes mellitus (T2DM) is a growing global public health problem, particularly prominent in developing countries. The early detection of T2DM and prediabetes is vital for reversing the outcome of disease, allowing early intervention. In the past decade, various microbiome-metabolome studies have attempted to address the question of whether there are any common microbial patterns that indicate either prediabetic or diabetic gut microbial signatures.
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