Search

Abstract Background Sepsis is common, deadly, and heterogenous. Prior analyses of patients with sepsis and septic shock in New York State showed a risk-adjusted association between more rapid antibiotic administration and bundled care completion, but not an intravenous fluid bolus, with reduced in-hospital mortality. However, it is unknown if clinically identifiable sepsis subtypes modify these associations. Methods Secondary analysis of patients with sepsis and septic shock enrolled in the New York State Department of Health cohort from January 1, 2015 to December 31, 2016. Patients were classified as clinical sepsis subtypes (α, β, γ, δ-types) using the Sepsis ENdotyping in Emergency CAre (SENECA) approach. Exposure variables included time to 3-h sepsis bundle completion, antibiotic administration, and intravenous fluid bolus completion. Then logistic regression models evaluated the interaction between exposures, clinical sepsis subtypes, and in-hospital mortality. Results 55,169 hospitalizations from 155 hospitals were included (34% α, 30% β, 19% γ, 17% δ). The α-subtype had the lowest (N = 1,905, 10%) and δ-subtype had the highest (N = 3,776, 41%) in-hospital mortality. Each hour to completion of the 3-h bundle (aOR, 1.04 [95%CI, 1.02–1.05]) and antibiotic initiation (aOR, 1.03 [95%CI, 1.02–1.04]) was associated with increased risk-adjusted in-hospital mortality. The association differed across subtypes (p-interactions

Abstract Objectives The primary objective is to evaluate the comparative effectiveness of COVID-19 specific monoclonal antibodies (mABs) with US Food and Drug Administration (FDA) Emergency Use Authorization (EUA), alongside UPMC Health System efforts to increase patient access to these mABs. Trial design Open-label, pragmatic, comparative effectiveness platform trial with response-adaptive randomization Participants We will evaluate patients who meet the eligibility criteria stipulated by the COVID-19 mAB EUAs who receive mABs within the UPMC Health System, including infusion centers and emergency departments. EUA eligibility criteria include patients with mild to moderate COVID-19,

Abstract Background Clinical and biologic phenotypes of sepsis are proposed in human studies, yet it is unknown whether prognostic or drug response phenotypes are present in animal models of sepsis. Using a biotelemetry-enhanced, murine cecal ligation and puncture (CLP) model, we determined phenotypes of polymicrobial sepsis prior to physiologic deterioration, and the association between phenotypes and outcome in a randomized trial of prompt or delayed antibiotics and fluids. Methods We performed a secondary analysis of male C57BL/6J mice in two observational cohorts and two randomized, laboratory animal experimental trials. In cohort 1, mice (n = 118) underwent biotelemetry-enhanced CLP, and we applied latent class mixed models to determine optimal number of phenotypes using clinical data collected between injury and physiologic deterioration. In cohort 2 (N = 73 mice), inflammatory cytokines measured at 24 h after deterioration were explored by phenotype. In a subset of 46 mice enrolled in two trials from cohort 1, we tested the association of phenotypes with the response to immediate (0 h) vs. delayed (2 to 4 h) antibiotics or fluids initiated after physiologic deterioration. Results Latent class mixture modeling derived a two-class model in cohort 1. Class 2 (N = 97) demonstrated a shorter time to deterioration (mean SD 7.3 (0.9) vs. 9.7 (3.2) h, p

Abstract Sepsis is a major contributor to the global burden of disease. The majority of sepsis cases and deaths are estimated to occur in low and middle-income countries. Barriers to reducing the global burden of sepsis include difficulty quantifying attributable morbidity and mortality, low awareness, poverty and health inequity, and under-resourced and low-resilience public health and acute health care delivery systems. Important differences in the populations at risk, infecting pathogens, and clinical capacity to manage sepsis in high and low-resource settings necessitate context-specific approaches to this significant problem. We review these challenges and propose strategies to overcome them. These strategies include strengthening health systems, accurately identifying and quantifying sepsis cases, conducting inclusive research, establishing data-driven and context-specific management guidelines, promoting creative clinical interventions, and advocacy.

Abstract All of medicine aspires to be precise, where a greater understanding of individual data will lead to personalized treatment and improved outcomes. Prompted by specific examples in oncology, the field of critical care may be tempted to envision that complex, acute syndromes could bend to a similar reductionist philosophy—where single mutations could identify and target our critically ill patients for treatment. However, precision medicine faces many challenges in critical care. These include confusion about terminology, uncertainty about how to divide patients into discrete groups, the challenges of multi-morbidity, scale, and the need for timely interventions. This review addresses these challenges and provides a translational roadmap spanning preclinical work to identify putative treatment targets, novel designs for clinical trials, and the integration of the electronic health record to implement precision critical care for all.