Defining Posttraumatic Sepsis for Population-Level Research.
Defining Posttraumatic Sepsis for Population-Level Research.
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DOI：
10.1001/jamanetworkopen.2022.51445
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发表时间：
2023-01-03
影响因子：
13.8
通讯作者：
Brakenridge, Scott C.
中科院分区：
文献类型：
--
作者：
Stern, Katherine;Qiu, Qian;Weykamp, Michael;O'Keefe, Grant;Brakenridge, Scott C.
现有的管理数据方法通常用于质量和研究目的，充分捕捉脓毒症事件的危重患者创伤性损伤？在这项包括3194名成人的队列研究中，与使用国家创伤数据库和行政编码方法相比，使用自动化临床数据库（脓毒症和脓毒性休克的第三次国际共识定义[脓毒症-3]）标准识别出明显更多的脓毒症病例，发病率结局更差。这项研究的结果表明，行政分类方法错误分类和低估严重创伤患者的脓毒症事件，这表明需要新的分析方法，这一人群。多种分类方法用于从现有数据中识别脓毒症。在创伤人群中，尚不清楚管理方法与脓毒症分类的临床标准如何比较。描述创伤危重患者中3种脓毒症分类方法之间的一致性，并比较每种方法用于定义脓毒症时脓毒症相关的不良结局风险。这项回顾性队列研究使用了2012年1月1日至2020年12月31日期间收集的数据，这些数据来自16岁或以上的创伤性损伤患者，这些患者入住单机构1级创伤中心的重症监护室，需要有创机械通气至少3天。统计分析时间为2021年8月1日至2022年3月31日。医院获得性脓毒症，按3种方法分类：一种基于电子健康记录、国家创伤数据库（NTDB）以及显性和隐性医疗账单代码数据的新型自动化临床方法。主要结局为慢性危重病和住院死亡率。次要结局包括在重症监护室的天数、接受机械通气的天数、出院至专业护理或长期护理机构的天数以及出院回家无需协助的天数。在符合入选标准的3194名患者中，中位年龄为49岁（IQR，31-64岁），2380名（74%）为男性，2826名（88%）遭受严重钝器损伤（中位损伤严重程度评分，29 [IQR，21-38]）。在符合自动临床标准的747例患者（23%）中确定了脓毒症，118例（4%）符合NTDB标准，529例（17%）使用医疗账单代码。三因素一致性的Light κ值为0.16（95% CI，0.14-0.19）。根据自动化临床标准确定的脓毒症慢性危重病的校正相对风险为9.9（95%CI，8.0-12.3），根据NTDB确定的脓毒症为5.0（95%CI，3.4-7.3），根据医疗账单代码确定的脓毒症为4.5（95%CI，3.6-5.6）。根据自动化临床标准确定的败血症的院内死亡率的校正相对风险为1.3（95%CI，1.0-1.6），根据NTDB确定的败血症为2.7（95%CI，1.7-4.3），根据医疗账单代码确定的败血症为1.0（95%CI，0.7-1.2）。在这项对创伤重症患者的队列研究中，与使用电子健康记录数据的自动临床方法相比，管理方法错误分类了脓毒症，低估了脓毒症的发生率和严重程度。这项研究表明，脓毒症分类的自动化方法与脓毒症和脓毒性休克（脓毒症-3）临床标准的第三次国际共识定义一致是可行的，并可能改善现有的方法，以卫生服务和人口为基础的研究在这一人群中。本队列研究描述了创伤危重患者中3种脓毒症分类方法之间的一致性，并比较了每种方法用于定义脓毒症时脓毒症相关的不良结局风险。
Do existing administrative data methods commonly used for quality and research purposes adequately capture sepsis events in critically ill patients with traumatic injury? In this cohort study that included 3194 adults, using automated clinical database (Third International Consensus Definitions for Sepsis and Septic Shock [Sepsis-3]) criteria identified significantly more cases of sepsis, with worse morbidity outcomes, compared with using the National Trauma Data Bank and administrative coding methods. The results of this study suggest that administrative classification methods misclassify and underestimate sepsis events among severely injured patients with trauma, suggesting that new analytic approaches are needed for this population. Multiple classification methods are used to identify sepsis from existing data. In the trauma population, it is unknown how administrative methods compare with clinical criteria for sepsis classification. To characterize the agreement between 3 approaches to sepsis classification among critically ill patients with trauma and compare the sepsis-associated risk of adverse outcomes when each method was used to define sepsis. This retrospective cohort study used data collected between January 1, 2012, and December 31, 2020, from patients aged 16 years or older with traumatic injury, admitted to the intensive care unit of a single-institution level 1 trauma center and requiring invasive mechanical ventilation for at least 3 days. Statistical analysis was conducted from August 1, 2021, to March 31, 2022. Hospital-acquired sepsis, as classified by 3 methods: a novel automated clinical method based on data from the electronic health record, the National Trauma Data Bank (NTDB), and explicit and implicit medical billing codes. The primary outcomes were chronic critical illness and in-hospital mortality. Secondary outcomes included number of days in an intensive care unit, number of days receiving mechanical ventilation, discharge to a skilled nursing or long-term care facility, and discharge to home without assistance. Of 3194 patients meeting inclusion criteria, the median age was 49 years (IQR, 31-64 years), 2380 (74%) were male, and 2826 (88%) sustained severe blunt injury (median Injury Severity Score, 29 [IQR, 21-38]). Sepsis was identified in 747 patients (23%) meeting automated clinical criteria, 118 (4%) meeting NTDB criteria, and 529 (17%) using medical billing codes. The Light κ value for 3-way agreement was 0.16 (95% CI, 0.14-0.19). The adjusted relative risk of chronic critical illness was 9.9 (95% CI, 8.0-12.3) for sepsis identified by automated clinical criteria, 5.0 (95% CI, 3.4-7.3) for sepsis identified by the NTDB, and 4.5 (95% CI, 3.6-5.6) for sepsis identified using medical billing codes. The adjusted relative risk for in-hospital mortality was 1.3 (95% CI, 1.0-1.6) for sepsis identified by automated clinical criteria, 2.7 (95% CI, 1.7-4.3) for sepsis identified by the NTDB, and 1.0 (95% CI, 0.7-1.2) for sepsis identified using medical billing codes. In this cohort study of critically ill patients with trauma, administrative methods misclassified sepsis and underestimated the incidence and severity of sepsis compared with an automated clinical method using data from the electronic health record. This study suggests that an automated approach to sepsis classification consistent with Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) clinical criteria is feasible and may improve existing approaches to health services and population-based research in this population. This cohort study characterizes the agreement between 3 approaches to sepsis classification among critically ill patients with trauma and compares the sepsis-associated risk of adverse outcomes when each method is used to define sepsis.
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DOI：
10.1001/jama.2016.0288
发表时间：
2016-02-23
期刊：
JAMA
影响因子：
--
作者：
Seymour CW;Liu VX;Iwashyna TJ;Brunkhorst FM;Rea TD;Scherag A;Rubenfeld G;Kahn JM;Shankar-Hari M;Singer M;Deutschman CS;Escobar GJ;Angus DC
通讯作者：
Angus DC
影响因子：
15.2
作者：
Brant EB;Kennedy JN;King AJ;Gerstley LD;Mishra P;Schlessinger D;Shalaby J;Escobar GJ;Angus DC;Seymour CW;Liu VX
通讯作者：
Liu VX
影响因子：
8.8
作者：
Churpek, Matthew M.;Snyder, Ashley;Edelson, Dana P.
通讯作者：
Edelson, Dana P.
影响因子：
4.6
作者：
Mellhammar L;Kahn F;Whitlow C;Kander T;Christensson B;Linder A
通讯作者：
Linder A
影响因子：
22.4
作者：
LIGHT, RJ
通讯作者：
LIGHT, RJ