Systemic inflammatory response syndrome criteria in defining severe sepsis.
By K. Kaukonen, M. Bailey, D. Pilcher, D. Cooper, R. Bellomo. New England Journal of Medicine, 2015
1,056 citations recorded by the source corpus.
Subfields: Epidemiology, Immunology, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/9523035dad3ff689d4773bbafc57f814da1ae892
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In Epidemiology
- Mitchell M. Levy
- Greg S. Martin
- Derek C. Angus
- A. Rhodes
- Laura Evans
- Greg S. Corrado
- Michael D. Howell
- Atul J. Butte
In Immunology
Citations in the corpus
- Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach. (2016, methodology): “18,19 In addition, CDRs such as the Mortality in Emergency Department Sepsis score (MEDS); 20 the Rapid Emergency Medicine Score (REMS); 21 and the Confusion, Urea nitrogen, Respiratory Rate, Blood pressure, 65 years of age and older (CURB-65) 22,23 score are well described in the literature and…”
- The Pathogenesis of Sepsis and Potential Therapeutic Targets (2019, background): “Subsequently, CRP levels begin to decline, and this might be as a result of the remission of inflammation and as well as response to antibiotic treatment in the clinical setting [97].”
- Effect of Vitamin C Infusion on Organ Failure and Biomarkers of Inflammation and Vascular Injury in Patients With Sepsis and Severe Acute Respiratory Failure: The CITRIS-ALI Randomized Clinical Trial. (2019, background): “At 168 hours, median was 46 μM [IQR, 19-66] for vitamin C vs 29 μM for placebo [12-39], P < .”
- Assessment of Global Incidence and Mortality of Hospital-treated Sepsis. Current Estimates and Limitations. (2016, background): “(61) This diagnostic imprecision contributes to the heterogeneity observed in this meta-analysis and limits comparability of studies.”
- Scalable and accurate deep learning with electronic health records (2018, background): “False-negative predictions can miss significant numbers of clinically important events, leading to poor clinical outcomes [29].”
- Assessing the reporting of categorised quantitative variables in observational epidemiological studies (2017, background): “5 ≤ BMI < 25), overweight (25 ≤ BMI <30), and obese (BMI ≥ 30) and Kaukonen and colleagues [27] defined systemic inflammatory response syndrome (SIRS) status (present/absent) based on consensus statement of the American College of Chest Physicians and Society of Critical Care of Medicine.”
- Sepsis and septic shock. (2018, methodology): “36 Although traditionally the SIRS criteria have been used to describe the onset of sepsis, and they have been questioned for being too sensitive and not specific enough, Kaukonen and colleagues 44 found that SIRS signs might not be sensitive enough.”