论文标题
识别和分析败血症：ICU中败血症患者的回顾性研究
Identifying and Analyzing Sepsis States: A Retrospective Study on Patients with Sepsis in ICUs
论文作者
论文摘要
败血症占医院死亡人数的50％以上，相关费用在美国入院中排名最高。对疾病状态，严重程度和临床标记的了解的提高有可能显着改善患者预后并降低成本。我们开发了一个计算框架，该框架使用临床变量和模拟III数据库中的样本来鉴定败血症中的疾病状态。我们在败血症中识别六个不同的患者状态，每种状态与器官功能障碍的不同表现相关。我们发现，不同败血症状态的患者在统计学上是由不同人口和合并症特征的不同种群显着组成的。总的来说，我们的框架提供了败血症的整体视野，我们的发现为脓毒症的临床试验和治疗策略的未来开发提供了基础。
Sepsis accounts for more than 50% of hospital deaths, and the associated cost ranks the highest among hospital admissions in the US. Improved understanding of disease states, severity, and clinical markers has the potential to significantly improve patient outcomes and reduce cost. We develop a computational framework that identifies disease states in sepsis using clinical variables and samples in the MIMIC-III database. We identify six distinct patient states in sepsis, each associated with different manifestations of organ dysfunction. We find that patients in different sepsis states are statistically significantly composed of distinct populations with disparate demographic and comorbidity profiles. Collectively, our framework provides a holistic view of sepsis, and our findings provide the basis for future development of clinical trials and therapeutic strategies for sepsis.
