Background: Clinical deterioration regularly occurs in hospitalized patients potentially resulting in life threatening events. Early warning scores (EWS), like the Modified Early Warning Score (MEWS), assist care givers in assessing patients' clinical situation, but cannot alert for deterioration between measurements. New devices, like the ViSi Mobile (VM) and HealthPatch (HP) allow for continuous monitoring and can alert deterioration in an earlier phase. VM and HP were tested regarding MEWS calculation compared to nurse measurements, and detection of high MEWS in periods between nurse observations.
Methods: This quantitative study was part of a randomized controlled trial. Sixty patients of the surgical and internal medicine ward with a minimal expected hospitalization time of three days were randomized to VM or HP continuous monitoring in addition to regular nurse MEWS measurements for 24-72 h.
Results: Median VM and HP MEWS were higher than nurse measurements (2.7 vs. 1.9 and 1.9 vs. 1.3, respectively), predominantly due to respiratory rate measurement differences. During 1282 h VM and 1886 h HP monitoring, 71 (14 patients) and 32 (7 patients) high MEWS periods were detected during the non-observed periods. Time between VM or HP based high MEWS and next regular nurse measurement ranged from 0 to 9 (HP) and 10 (VM) hours.
Conclusions: Both VM and HP are promising for continuous vital sign monitoring and may be more accurate than nurses. High MEWS can be detected in hospitalized patients around the clock and clinical deterioration at an earlier phase during unobserved periods.
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http://dx.doi.org/10.1016/j.resuscitation.2019.01.017 | DOI Listing |
Eur Radiol Exp
November 2024
Department of Radiology, Charité-Universitätsmedizin Berlin, Campus Mitte, Humboldt-Universität zu Berlin, Freie Universität Berlin, Berlin, Germany.
Background: Dual-energy computed tomography (DECT) is a noninvasive diagnostic tool for gouty arthritis. This study aimed to compare two postprocessing techniques for monosodium urate (MSU) detection: conventional two-material decomposition and material map-based decomposition.
Methods: A raster phantom and an ex vivo biophantom, embedded with four different MSU concentrations, were scanned in two high-end CT scanners.
EClinicalMedicine
November 2024
Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Background: Clinical severity scores can identify patients at risk of severe disease and death, and improve patient management. The modified early warning score (MEWS), the quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and the Universal Vital Assessment (UVA) were developed as risk-stratification tools, but they have not been fully validated in low-resource settings where fever and infectious diseases are frequent reasons for health care seeking. We assessed the performance of MEWS, qSOFA, and UVA in predicting mortality among febrile patients in the Lao PDR, Malawi, Mozambique, and Zimbabwe.
View Article and Find Full Text PDFAlzheimers Res Ther
October 2024
Institute of Cardiovascular Science, Faculty of Population Health, University College London, 69-75 Chenies Mews, London, WC1E 6HX, UK.
Nano Lett
October 2024
University of Hamburg, Institute of Physical Chemistry, Grindelallee 117, 20146 Hamburg, Germany.
JAMA Netw Open
October 2024
Section of General Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Importance: Early warning decision support tools to identify clinical deterioration in the hospital are widely used, but there is little information on their comparative performance.
Objective: To compare 3 proprietary artificial intelligence (AI) early warning scores and 3 publicly available simple aggregated weighted scores.
Design, Setting, And Participants: This retrospective cohort study was performed at 7 hospitals in the Yale New Haven Health System.
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