Developing the surveillance algorithm for detection of failure to recognize and treat severe sepsis.
Developing the surveillance algorithm for detection of failure to recognize and treat severe sepsis.
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DOI：
10.1016/j.mayocp.2014.11.014
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发表时间：
2015-03
影响因子：
8.9
通讯作者：
Herasevich V
中科院分区：
文献类型：
--
作者：
Harrison AM;Thongprayoon C;Kashyap R;Chute CG;Gajic O;Pickering BW;Herasevich V
开发和测试一种自动监测算法(脓毒症嗅探器)，用于检测严重脓毒症，并监测未能及时识别和治疗严重脓毒症。我们使用第三转诊中心医疗重症监护病房(ICU)的电子病历数据库中的独立派生和验证队列进行了观察性诊断性能研究。纳入2013年1月1日至3月31日在内科ICU住院的所有18岁及以上患者(N=587)。严重败血症/感染性休克的标准是由2名训练有素的评审员与第三名超级评审员对观察者间存在分歧的情况进行手动评审。对假阳性和假阴性警报进行了关键评估，并进行了递归数据分割，以优化算法。一种基于怀疑感染、全身炎症反应综合征、器官低灌流和功能障碍以及休克标准的算法应用于验证队列时，敏感度为80%，特异度为96%。通过递归数据划分，低收缩压、全身性炎症反应综合征阳性和疑似感染被确定为最有预测价值。最后，117名警报阳性患者(171名严重脓毒症患者中的68%)延迟了识别和治疗，定义为在警报发出后2小时内没有测量乳酸和中心静脉压。优化的嗅探器准确识别了床边临床医生未能及时识别和治疗的严重脓毒症患者。
To develop and test an automated surveillance algorithm (sepsis “sniffer”) for the detection of severe sepsis and monitoring failure to recognize and treat severe sepsis in a timely manner. We conducted an observational diagnostic performance study using independent derivation and validation cohorts from an electronic medical record database of the medical intensive care unit (ICU) of a tertiary referral center. All patients aged 18 years and older who were admitted to the medical ICU from January 1 through March 31, 2013 (N=587), were included. The criterion standard for severe sepsis/septic shock was manual review by 2 trained reviewers with a third superreviewer for cases of interobserver disagreement. Critical appraisal of false-positive and false-negative alerts, along with recursive data partitioning, was performed for algorithm optimization. An algorithm based on criteria for suspicion of infection, systemic inflammatory response syndrome, organ hypoperfusion and dysfunction, and shock had a sensitivity of 80% and a specificity of 96% when applied to the validation cohort. In order, low systolic blood pressure, systemic inflammatory response syndrome positivity, and suspicion of infection were determined through recursive data partitioning to be of greatest predictive value. Lastly, 117 alert-positive patients (68% of the 171 patients with severe sepsis) had a delay in recognition and treatment, defined as no lactate and central venous pressure measurement within 2 hours of the alert. The optimized sniffer accurately identified patients with severe sepsis that bedside clinicians failed to recognize and treat in a timely manner.
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幸存的败血症运动：严重败血症和化粪池冲击管理的国际指南，2012年。
影响因子：
38.9
作者：
Dellinger RP;Levy MM;Rhodes A;Annane D;Gerlach H;Opal SM;Sevransky JE;Sprung CL;Douglas IS;Jaeschke R;Osborn TM;Nunnally ME;Townsend SR;Reinhart K;Kleinpell RM;Angus DC;Deutschman CS;Machado FR;Rubenfeld GD;Webb S;Beale RJ;Vincent JL;Moreno R;Surviving Sepsis Campaign Guidelines Committee including The Pediatric Subgroup
通讯作者：
Surviving Sepsis Campaign Guidelines Committee including The Pediatric Subgroup
影响因子：
120.7
作者：
SILBER, JH;ROSENBAUM, PR;WILLIAMS, SV
通讯作者：
WILLIAMS, SV
DOI：
10.1186/cc2959
发表时间：
2004-12
期刊：
Critical care (London, England)
影响因子：
--
作者：
Poeze M;Ramsay G;Gerlach H;Rubulotta F;Levy M
通讯作者：
Levy M
影响因子：
8.8
作者：
Sawyer, Amber M.;Deal, Eli N.;Kollef, Marin H.
通讯作者：
Kollef, Marin H.
影响因子：
158.5
作者：
Rivers, E;Nguyen, B;Tomlanovich, M
通讯作者：
Tomlanovich, M