Identifying pre-sepsis opportunities for early, targeted intervention

确定败血症前早期、有针对性的干预的机会

• 批准号: 10457826
• 负责人: Vincent Liu
• 金额: $ 38.85万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10457826
• 关键词: Accident and Emergency department; Caring; Cessation of life; Characteristics; Computerized Medical Record; Data; Early treatment; Evaluation; Future; Goals; Health system; Hospital Departments; Hospitals; Infection; Informatics; Intervention; Laboratories; Methods; Organ failure; Patient Care; Patients; Persons; Pre-hospital setting; Process; Public Health; Randomized Clinical Trials; Risk; Sepsis; Symptoms; adverse outcome; authority; design; global health; high risk; improved; improved outcome; innovation; mortality; novel; predictive modeling; prevent; programs; septic patients; treatment guidelines

PROJECT SUMMARY Sepsis kills an estimated 6 million people worldwide every year. Sepsis also contributes to as many as 50% of US hospital deaths. Early treatment is the only universally recognized modifiable factor for improving sepsis mortality. Thus, current treatment guidelines focus heavily on early sepsis care immediately following hospital presentation. However, key national and global health authorities also emphasize the need to identify even earlier pre-hospital opportunities to predict, recognize, or treat sepsis. Little is known about the presentation, pace, and profile of infection in pre-sepsis patients. Understanding these characteristics could enable novel pre-hospital approaches designed to mitigate, or even prevent, sepsis. Using an innovative translational informatics approach, this project will identify and characterize pre-sepsis opportunities for early, targeted intervention. To achieve this goal, my laboratory leverages comprehensive electronic medical record data, advanced informatics methods, and the evaluation of novel care programs. Through this proposal, we will develop and validate prediction models that identify patients in common pre-hospital settings at the highest risk of impending sepsis, organ failure, and mortality. In the process, we will characterize the sepsis-related symptom profiles that portend the highest risk of adverse outcomes. Findings will have broad and immediate implications for patients, clinicians, and health systems. These results will also inform the design of sepsis public health programs and future randomized clinical trials aimed at improving outcomes for this devastating condition.

项目总结