Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016

By A. Rhodes, Laura Evans, W. Alhazzani, Mitchell M. Levy, M. Antonelli, R. Ferrer, Anand Kumar, J. Sevransky, C. Sprung, Mark E. Nunnally and 49 more. 2017

7,369 citations recorded by the source corpus.

Subfields: Critical Care and Intensive Care Medicine, Epidemiology, Immunology

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Citations in the corpus

Reinforcement Learning in Healthcare: A Survey (2019, background): “Unfortunately, only a few of these interventions could be supported by high quality evidence from randomised controlled trials or meta-analyses [187], especially when it comes to development of potentially new therapies for complex ICU syndromes, such as sepsis [188] and acute”
Deep Reinforcement Learning for Sepsis Treatment (2017, background): “While international efforts attempt to provide general guidance for treating sepsis, physicians at the bedside still lack efﬁcient tools to provide individualized real-term decision support [10].”
Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach (2017, background): “While international efforts attempt to provide general guidance for treating sepsis, physicians at the bedside still lack efﬁcient tools to provide individualized real-term decision support (Rhodes et al., 2017).”
Surviving Sepsis Campaign: Guidelines on the Management of Critically Ill Adults with Coronavirus Disease 2019 (COVID-19) (2020, positive): “Accordingly, we used, as sources of indirect evidence, data on Middle East Respiratory Syndrome Coronavirus (MERS-CoV), Severe Acute Respiratory Syndrome (SARS), and other coronaviruses; in the same way, we considered, as indirect evidence, published data on supportive care in the ICU from studies o”
The Surviving Sepsis Campaign Bundle: 2018 update (2018, methodology): “Table 1 Bundle elements with strength of recommendations and under‐pinning quality of evidence [12, 13]”
Early Neuromuscular Blockade in the Acute Respiratory Distress Syndrome (2019, neutral): “6,8,9 16-18 To capture potential differences in late sequelae, assessors who were unaware of the group assignment interviewed surviving patients or their proxies at 3, 6, and 12 months after randomization.”
Glycemic Characteristics and Clinical Outcomes of COVID-19 Patients Hospitalized in the United States (2020, neutral): “035 Median age in years (range) 65 (24-95) 61 (18-101) .”
Enhancing Recovery From Sepsis (2018, positive): “Early Hospital Treatment for Sepsis Early hospital care for sepsis focuses on prompt recognition, treatment with broad-spectrum antibiotics, elimination of infectious sources (eg, removing infected indwellingcatheters), and resuscitation with intravenous fluids and vasopressors for patients with low”
High risk of thrombosis in patients with severe SARS-CoV-2 infection: a multicenter prospective cohort study (2020, background): “As is the case with sepsis, prophylactic anticoagulation of patients with severe COVID-19 may be recommended [6].”
The Pathogenesis of Sepsis and Potential Therapeutic Targets (2019, methodology): “In other words, the qSOFA maybe oversensitive and exhibits a low specificity, which may lead to an overdiagnosis of sepsis; therefore, the qSOFA predictive value is suggested to be lower than other commonly used scoring systems [14,17,18].”