Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014
By C. Rhee, Raymund B. Dantes, L. Epstein, David J Murphy, C. Seymour, Theodore J. Iwashyna, S. Kadri, Derek C. Angus, R. Danner, A. Fiore and 10 more. Journal of the American Medical Association (JAMA), 2017
1,648 citations recorded by the source corpus.
Subfields: Critical Care and Intensive Care Medicine, Epidemiology, Immunology
View Paper: https://www.semanticscholar.org/paper/0fd79ef6a22f7b25105306d364aa693eb4b33d8a
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In Critical Care and Intensive Care Medicine
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Citations in the corpus
- Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis (2022, methodology): “This approach follows the methods validated by many researchers in sepsis epidemiology 25–28 and used by Rudd and colleagues.”
- External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients. (2021, neutral): “Chronic kidney disease 7313 (19) 6332 (18) 981 (38) <.”
- Mortality in sepsis and septic shock in Europe, North America and Australia between 2009 and 2019— results from a systematic review and meta-analysis (2020, result): “5% for septic shock patients [6], while another retrospective cohort study using health record data reported 15% in hospital mortality for sepsis and septic shock [1].”
- Vital Signs: Epidemiology and Recent Trends in Methicillin-Resistant and in Methicillin-Susceptible Staphylococcus aureus Bloodstream Infections — United States (2019, background): “As has been previously shown with another infection-related condition (sepsis), clinical criteria using EHR data are immune to temporal variations in coding practices that can be significant (30), whereas death-certificate data are an insensitive measure of sepsis-related mortality (31).”
- Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning (2018, neutral): “t=0 γ(w tQ̂ e(Si t , A Hi t )− w t−1V̂ e(S Hi t )) (2)”
- Prevalence and Outcomes of Infection Among Patients in Intensive Care Units in 2017. (2020, methodology): “Because source data verification was not practical in this globalstudy,thefollowingstepsweretakentooptimizedataquality: (1) the case report forms were built based on the forms used in the earlier EPIC studies; (2) the case report forms were discussed at several investigator meetings; (3) plausible m”
- Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050 (2024, positive): “This approach follows the methods validated by many studies on the epidemiology of sepsis 26–29 and was used by Rudd and colleagues.”