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

COVID-19 住院患者脓毒症的发生率、结果和预测因素

• 批准号: 10610089
• 负责人: Claire Shappell
• 金额: $ 0.25万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2023-08-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10610089
• 关键词: 2019-nCoV; Accounting; Acute Respiratory Distress Syndrome; Admission activity; Adult; Age; Anti-Inflammatory Agents; Award; Bacteremia; Bacterial Infections; Big Data; COVID-19; COVID-19 patient; COVID-19 risk; Caring; Centers for Disease Control and Prevention (U.S.); Cessation of life; Clinical; Clinical Data; Cohort Studies; Complex; Computer software; Consensus; Critical Care; Critical Illness; Data; Data Analyses; Data Science; Databases; Development; Diagnosis; Discipline of Nursing; Disease; Electronic Health Record; Epidemiologic Monitoring; Epidemiology; Event; Foundations; Functional disorder; Funding; Goals; Health; Healthcare Systems; Hospitalization; Hospitals; Human; Hypertension; Immune; Immune response; Incidence; Infection; Infectious Agent; Influenza; Intensive Care; International; Laboratories; Life; Lung; Mediating; Mentors; Mentorship; Methods; Mining; Modeling; Modernization; Multiple Organ Failure; Obesity; Organ; Outcome; Pathway interactions; Patient Triage; Patients; Physicians; Physiological; Pneumonia; Population trends; Prevention; Prevention strategy; Prognosis; Public Health; Public Policy; Race; Recommendation; Reporting; Research; Resource Allocation; Resources; Risk Factors; Risk Management; SARS-CoV-2 infection; Scientist; Sepsis; Septic Shock; Severity of illness; Societies; Statistical Data Interpretation; Structure; Test Result; Time; Tissues; Training; United States; Viral; Virus; Work; base; clinical diagnosis; comorbidity; coronavirus disease; data acquisition; demographics; evidence base; experience; health care service organization; healthcare-associated infections; improved; influenza infection; innovation; insight; model development; mortality; national surveillance; novel; novel virus; pandemic disease; pathogen; patient stratification; patient subsets; patient-clinician communication; predictive modeling; respiratory virus; risk stratification; severe COVID-19; skills

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.

SARS-COV-2引起广泛的疾病，从无症状感染到多器 失败和死亡。感染了患有SARS-COV-2的患者，这些患者在技术上符合器官功能障碍 第三个国际共识定义对败血症和败血性冲击，将败血症定义为失调 宿主对感染的反应导致威胁生命的感染。临床医生很少将严重的covid构造为 然而，败血症的事实是，这样做可以帮助快速传达这种情况的严重性和 援引现有的医院结构和管理途径，以优化针对这一病的病 患者。同时，严重的Covid-19可能具有独特的功能，可以将其与常规区分开 细菌败血症以及其他呼吸道病毒。 该提案的总体目的是表征Covid-19-的事件和结果。 相关的败血症，其危险因素以及它们与影响ZA或细菌感染的败血症相比。我们的 拟议的项目将根据CDC的成人利用败血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，具有五家医院的详细电子健康记录数据，一个 具有丰富经验的研究小组使用大数据来对 败血症，肺炎和其他医疗保健相关的流行病学，诊断，预防和治疗 在我们的提案的目标1中，我们将利用败血症监视的最先进方法来提供 严格估计COVID-19中败血症的严格估计，并在 与影响与影响或细菌感染相比，败血症的结果和危险因素。在AIM 2中，我们将 合并患者人口统计学，合并症，生命体征和实验室测试结果 为了预测Covid-19患者的败血症的发展，以提高风险 出现时患者的分层和更有效的医院资源分配。 拟议的工作将通过告知基于证据的比较来产生重要的公共卫生影响 Covid-19，IntralenceA和细菌败血症的指导公共政策。表征独特的特征 Covid-19的败血症还可以帮助提供更好的风险分层和管理策略，并产生 假设为严重的共同199的病理生理学。 该奖项还将使候选人克莱尔·沙佩尔（Claire Shappell）博士获得数据获取的基本技能 以及分析，预测建模，使用统计分析软件和授予技巧，使她能够 实现她成为具有专业知识的独立资助的身体科学家的长期目标 挖掘通过电子健康记录（EHRS）获得越来越丰富的临床和生理数据 为了表征人口趋势并确定重大护理改善的新机会。

项目成果

Use of Electronic Clinical Data to Track Incidence and Mortality for SARS-CoV-2-Associated Sepsis.

• DOI: 10.1001/jamanetworkopen.2023.35728
• 发表时间: 2023-09-05
• 期刊: JAMA NETWORK OPEN
• 影响因子: 13.8
• 作者: Shappell, Claire N.;Klompas, Michael;Chan, Christina;Chen, Tom;Kanjilal, Sanjat;Mckenna, Caroline;Rhee, Chanu
• 通讯作者: Rhee, Chanu

Prevalence, Clinical Characteristics, and Outcomes of Sepsis Caused by Severe Acute Respiratory Syndrome Coronavirus 2 Versus Other Pathogens in Hospitalized Patients With COVID-19.

• DOI: 10.1097/cce.0000000000000703
• 发表时间: 2022-05
• 期刊: Critical care explorations
• 作者: Shappell, Claire N.;Klompas, Michael;Kanjilal, Sanjat;Chan, Christina;Rhee, Chanu
• 通讯作者: Rhee, Chanu