309 research outputs found

    Traditional transfusion practices are changing

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    Schochl and co-authors have described a 5-year retrospective study that outlines a novel, important and controversial transfusion concept in seriously injured trauma patients. Traditionally, clinicians have been taught to use a serial approach, resuscitating hypovolemic trauma patients with a form of crystalloid or colloid, followed by red blood cells (RBCs), then fresh frozen plasma (FFP), and lastly platelets. The data supporting this widely accepted approach are remarkably weak. Conversely, Schochl and colleagues, in an innovative, retrospective study, describe the use of fibrinogen concentrate, plasma complex concentrate, RBCs, FFP, and platelets driven by a thromboelastometry-based algorithm. Finally, it appears that transfusion therapy is becoming driven by physiology

    REVISITING ENGEL'S LAW: EXAMINING EXPENDITURE PATTERNS FOR FOOD AT HOME AND AWAY FROM HOME

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    Expenditure patterns were examined for food partitioned into food at home and away from home to test the veracity of Engel's law. The analysis employed several functional forms and a Heckman two-step methodology to account for censored-response bias. Engel's law was verified in every case.Consumer/Household Economics,

    X-Ray Diffraction Powder Data for Steroids: Supplement VIII

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    This supplement continues a series of publications which began as a separate section, with the Dec. 1958 issue, and has been supplemented periodically since then. Other publications have been March 1961 (Supplement I) Sept. 1962 (Supp. II): March 1963 (Supp. Ill): March 1964 (Supp. IV): Dec. 1964 (Supp. V): Sept. 1965 (Supp. VI) and Dec. 1966 (Supp. VII)

    Seismic Monitoring and Baseline Microseismicity in the Rome Trough, Eastern Kentucky

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    In the central and eastern United States, felt earthquakes likely triggered by fluid injection from oil and gas production or wastewater disposal have dramatically increased in frequency since the onset of the unconventional shale gas and oil boom. In the Rome Trough of eastern Kentucky, fracture stimulations and wastewater injection are ongoing and occur near areas of historical seismic activity. Unlike in surrounding and nearby states (Ohio, West Virginia, and Arkansas), in Kentucky, no seismic events related to subsurface fluid injections have been reported as felt or detected by regional seismic networks, including the Kentucky Seismic and Strong-Motion Network. Oil and gas development of the deep Cambrian Rogersville Shale in the Rome Trough is in a very early stage, and will require horizontal drilling and high-volume hydraulic fracturing. To characterize natural seismicity rates and the conditions that might lead to induced or triggered events, the Kentucky Geological Survey is conducting a collaborative study, the Eastern Kentucky Microseismic Monitoring Project, prior to large-scale oil and gas production and wastewater injection. A temporary network of broadband seismographs was deployed near dense clusters of Class II wastewater-injection wells and near the locations of new, deep oil and gas test wells in eastern Kentucky. Network installation began in mid-2015 and by November 2015, 12 stations were operating, with data acquired in real time and jointly with regional network data. Additional stations were installed between June 2016 and October 2017 in targeted locations. The network improved the monitoring sensitivity near wastewater-injection wells and deep oil and gas test wells by approximately an entire unit of magnitude: With the temporary network, the detectable magnitudes range from 0.7 to 1.0, and without it, the detectable magnitudes range from 1.5 to 1.9. Using the real-time recordings of this network in tandem with the recordings of other temporary and permanent regional seismic stations, we generated a catalog of local seismicity and developed a calibrated magnitude scale. At the time this report was prepared, 151 earthquakes had been detected and located, 38 of which were in the project area, defined as the region bounded by 37.1°N to 38.7°N latitude and 84.5°W to 82.0°W longitude. Only six earthquakes occurred in the Rome Trough of eastern Kentucky, none of which were reported in regional monitoring agency catalogs, and none of which appear to be associated with the deep Rogersville Shale test wells that were completed during the time the network was in operation or with wastewater-injection wells

    Early Prediction of Massive Transfusion for Patients With Traumatic Hemorrhage: Development of a Multivariable Machine Learning Model

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    OBJECTIVE: Develop a novel machine learning (ML) model to rapidly identify trauma patients with severe hemorrhage at risk of early mortality. BACKGROUND: The critical administration threshold (CAT, 3 or more units of red blood cells in a 60-minute period) indicates severe hemorrhage and predicts mortality, whereas early identification of such patients improves survival. METHODS: Patients from the PRospective, Observational, Multicenter, Major Trauma Transfusion and Pragmatic, Randomized Optimal Platelet, and Plasma Ratio studies were identified as either CAT+ or CAT-. Candidate variables were separated into 4 tiers based on the anticipated time of availability during the patient\u27s assessment. ML models were created with the stepwise addition of variables and compared with the baseline performance of the assessment of blood consumption (ABC) score for CAT+ prediction using a cross-validated training set and a hold-out validation test set. RESULTS: Of 1245 PRospective, Observational, Multicenter, Major Trauma Transfusion and 680 Pragmatic, Randomized Optimal Platelet and Plasma Ratio study patients, 1312 were included in this analysis, including 862 CAT+ and 450 CAT-. A CatBoost gradient-boosted decision tree model performed best. Using only variables available prehospital or on initial assessment (Tier 1), the ML model performed superior to the ABC score in predicting CAT+ patients [area under the receiver-operator curve (AUC = 0.71 vs 0.62)]. Model discrimination increased with the addition of Tier 2 (AUC = 0.75), Tier 3 (AUC = 0.77), and Tier 4 (AUC = 0.81) variables. CONCLUSIONS: A dynamic ML model reliably identified CAT+ trauma patients with data available within minutes of trauma center arrival, and the quality of the prediction improved as more patient-level data became available. Such an approach can optimize the accuracy and timeliness of massive transfusion protocol activation
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