Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review.
Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review.
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DOI：
10.1002/jhm.2347
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发表时间：
2015-06
影响因子：
2.6
通讯作者：
Auerbach, Andrew D.
中科院分区：
文献类型：
--
作者：
Makam, Anil N.;Nguyen, Oanh K.;Auerbach, Andrew D.
尽管脓毒症的及时治疗改善了结果，但在实施循证治疗方面的延误是常见的。为了确定自动化的实时电子脓毒症警报是否可以：1)准确地识别脓毒症，以及2)改进过程措施和结果。我们系统地检索了MEDLINE、Embase、Cochrane图书馆和CINAHL，从数据库建立到2014年6月27日。包括对一个或两个预先指定的目标进行经验性评估的研究。两名独立的评价者提取了数据，并评估了偏见的风险。通过敏感度、特异度、阳性预测值(PPV)、阴性预测值(NPV)和似然比(LR)来衡量脓毒症诊断的准确性。通过脓毒症护理过程措施和结果的变化来评估有效性。在1,293篇引文中，8篇研究符合纳入标准，5篇关于脓毒症的识别(n=35,423)，5篇关于败血症警报的有效性(n=6,894)。虽然脓毒症警报阈值的定义各不相同，但大多数包括全身炎症反应综合征标准±休克的证据。诊断准确率差异较大，PPV20.5~53.8%，NPV76.5~99.7%，LR+1.2~145.8，LR-0.06~0.86。有少量证据表明流程措施(即抗生素升级)有所改善，但仅限于非危重护理环境中的患者；死亡率或住院时间没有相应的改善。关于误报警报造成的潜在危害，报告的数据最少。从电子健康数据派生的自动脓毒症警报可能会改善护理过程，但往往具有较差的阳性预测价值，并且不能改善死亡率或住院时间。
Although timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. To determine whether automated real-time electronic sepsis alerts can: 1) accurately identify sepsis, and 2) improve process measures and outcomes. We systematically searched MEDLINE, Embase, The Cochrane Library, and CINAHL from database inception through June 27, 2014. Included studies that empirically evaluated one or both of the prespecified objectives. Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive (PPV) and negative predictive values (NPV) and likelihood ratios (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. Of 1,293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n=35,423) and 5 for the effectiveness of sepsis alerts (n=6,894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5-53.8%, NPV 76.5-99.7%; LR+ 1.2-145.8; and LR- 0.06-0.86. There was modest evidence for improvement in process measures (i.e., antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts. Automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor positive predictive value and do not improve mortality or length of stay.
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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：
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
影响因子：
8.8
作者：
Siebig, Sylvia;Kuhls, Silvia;Wrede, Christian E.
通讯作者：
Wrede, Christian E.
影响因子：
120.7
作者：
Ferrer, Ricard;Artigas, Antonio;de la Torre-Prados, Maria Victoria
通讯作者：
de la Torre-Prados, Maria Victoria