Incidence, Outcomes, and Predictors of Sepsis in Hospitalized Patients with COVID-19

SARS-CoV-2引起一系列疾病，从无症状感染到多器官感染 失败和死亡。从技术上讲，感染SARS-CoV-2的患者出现器官功能障碍 第三种国际共识的脓毒症和感染性休克的定义，它将脓毒症定义为一种调节失调 宿主对感染的反应导致危及生命的感染。临床医生很少将严重的新冠肺炎定为 然而，脓毒症，尽管这样做可以帮助迅速传达病情的严重性和 调用现有的医院结构和管理路径来优化对这一病情严重的子集的护理 病人。与此同时，重症新冠肺炎可能有一些独特的特征，使其有别于常规的 细菌性败血症以及其他呼吸道病毒感染。 这项提案的总体目标是描述新冠肺炎的发生率和结果- 相关的脓毒症，其危险因素，以及这些与流感或细菌感染引起的脓毒症的比较。我们的 拟议的项目将利用基于疾控中心成人的脓毒症和器官功能障碍的客观定义 败血症事件标准，一个大型数据库，其中有来自五家医院的详细电子健康记录数据，以及一个 具有丰富使用大数据经验的研究团队，可在以下方面进行创新和有影响力的研究 败血症、肺炎和其他医疗保健相关疾病的流行病学、诊断、预防和治疗 感染。在我们建议的目标1中，我们将利用最先进的方法监测败血症，以提供 对新冠肺炎脓毒症发病率的严格估计，并使循证比较 新冠肺炎引起的败血症与流感或细菌感染的转归和危险因素。在目标2中，我们将 包括患者的人口统计资料、合并症、生命体征和当时可用的实验室检测结果 介绍为了预测新冠肺炎患者脓毒症的发展，从而改善风险 在陈述时对患者进行分层，并更有效地分配医院资源。 拟议的工作将通过提供基于证据的比较来对公共卫生产生重要影响 新冠肺炎，流感，细菌败血症，以指导公共政策。描述了的显著特征 新冠肺炎中的脓毒症也可以帮助提供更好的风险分层和管理策略，并产生 重症新冠肺炎的病理生理学假说。 该奖项还将使候选人克莱尔·沙佩尔博士获得数据获取方面的基本技能 和分析，预测性建模，统计分析软件的使用，以及资质，使她能够 实现她的长期目标，成为一名独立资助的内科科学家，拥有 通过电子健康记录(EHR)挖掘日益丰富的临床和生理数据 以确定人口趋势，并确定改善危重疾病护理的新机会。

SARS-CoV-2 causes a wide spectrum of illness ranging from asymptomatic infection to multiorgan failure and death. Patients infected with SARS-CoV-2 who develop organ dysfunction technically meet the Third International Consensus Definitions of Sepsis and Septic Shock, which define sepsis as a dysregulated host response to infection leading to life-threatening infection. Clinicians rarely frame severe COVID-19 as sepsis, however, despite the fact that doing so could help rapidly convey the seriousness of the condition and invoke existing hospital structures and management pathways to optimize care for this very ill subset of patients. At the same time, severe COVID-19 likely has unique features that differentiate it from routine bacterial sepsis as well as from other respiratory viruses. The overall objective of this proposal is to characterize the incidence and outcomes for COVID-19- associated sepsis, its risk factors, and how these compare to sepsis from influenza or bacterial infections. Our proposed project will leverage objective definitions of sepsis and organ dysfunction based on CDC’s Adult Sepsis Event criteria, a large database with detailed electronic health record data from five hospitals, and a research group with extensive experience using big data to conduct innovative and impactful studies on epidemiology, diagnosis, prevention, and treatment of sepsis, pneumonia, and other healthcare-associated infections. In Aim 1 of our proposal, we will utilize state-of-the-art methods in sepsis surveillance to provide rigorous estimates of sepsis incidence in COVID-19 and enable evidence-based comparisons between outcomes and risk factors for sepsis due to COVID-19 versus influenza or bacterial infections. In Aim 2, we will incorporate patient demographics, comorbidities, vital signs, and laboratory test results available at the time of presentation in order to predict the development of sepsis in patients with COVID-19, allowing improved risk stratification of patients at the time of presentation and more efficient hospital resource allocation. The proposed work will have important public health impact by informing evidence-based comparisons of COVID-19, influenza, and bacterial sepsis to guide public policy. Characterizing the distinctive features of sepsis in COVID-19 could also help inform better risk stratification and management strategies and generate hypotheses into the pathophysiology of severe COVID-19. The award will also enable the candidate, Dr. Claire Shappell, to gain essential skills in data acquisition and analysis, predictive modeling, use of statistical analysis software, and grantsmanship, enabling her to achieve her long term objective of becoming an independently-funded physician-scientist with expertise in mining the increasingly abundant clinical and physiologic data available via electronic health records (EHRs) in order to characterize population trends and identify novel opportunities for care improvement in critical illness.