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A Multibiomarker-Based Outcome Risk Stratification Model for Adult Septic Shock

机译:成人化粪池休克基于多兆板的结果风险分层模型

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Objectives: Clinical trials in septic shock continue to fail due, in part, to inequitable and sometimes unknown distribution of baseline mortality risk between study arms. Investigators advocate that interventional trials in septic shock require effective outcome risk stratification. We derived and tested a multibiomarker-based approach to estimate mortality risk in adults with septic shock. Design: Previous genome-wide expression studies identified 12 plasma proteins as candidates for biomarker-based risk stratification. The current analysis used banked plasma samples and clinical data from existing studies. Biomarkers were assayed in plasma samples obtained from 341 subjects with septic shock within 24 hours of admission to the ICU. Classification and regression tree analysis was used to generate a decision tree predicting 28-day mortality based on a combination of both bio-markers and clinical variables. The derived tree was first tested in an independent cohort of 331 subjects, then calibrated using all subjects (n = 672), and subsequently validated in another independent cohort (n = 209). Setting: Multiple ICUs in Canada, Finland, and the United States. Subjects: Eight hundred eighty-one adults with septic shock or severe sepsis. Intervention: None. Measurements and Main Results: The derived decision tree included five candidate biomarkers, admission lactate concentration, age, and chronic disease burden. In the derivation cohort, sensitivity for mortality was 94% (95% Cl, 87-97), specificity was 56% (50-63), positive predictive value was 50% (43-57), and negative predictive value was 95% (89-98). Performance was comparable in the test cohort. The calibrated decision tree had the following test characteristics in the validation cohort: sensitivity 85% (76-92), specificity 60% (51-69), positive predictive value 61% (52-70), and negative predictive value 85% (75-91). Conclusions: We have derived, tested, calibrated, and validated a risk stratification tool and found that it reliably estimates the probability of mortality in adults with septic shock.
机译:目的:化粪池休克的临床试验继续失效,部分原因是在研究手臂之间不公平,有时未知的基线死亡风险分布。调查人员主张化脓性休克中的介入试验需要有效的结果风险分层。我们衍生和测试了基于多兆板基的方法来估计具有脓毒症休克成年人的死亡率风险。设计:以前的基因组表达研究确定了12个血浆蛋白作为基于生物标志物的风险分层的候选者。目前的分析使用了来自现有研究的银币等离子体样本和临床数据。将生物标志物在从341个受试者中获得的血浆样品中的血浆样品,在入场后24小时内的脓毒症休克。分类和回归树分析用于基于生物标记和临床变量的组合产生预测28天死亡率的决策树。首先在331个受试者的独立队列中测试衍生的树,然后使用所有受试者(n = 672)校准,随后在另一个独立的队列(n = 209)中验证。设置:加拿大,芬兰和美国的多思士。主题:八百八十一位成年人,脓毒症休克或严重败血症。干预:没有。测量和主要结果:衍生的决策树包括五个候选生物标志物,入学乳酸浓度,年龄和慢性病负担。在衍生队队列中,死亡率的敏感性为94%(95%Cl,87-97),特异性为56%(50-63),阳性预测值为50%(43-57),负预测值为95% (89-98)。性能在测试队列中可比。校准的决策树在验证队列中具有以下测试特性:灵敏度85%(76-92),特异性60%(51-69),阳性预测值61%(52-70),以及负预测值85%( 75-91)。结论:我们引导了,测试,校准并验证了风险分层工具,并发现它可靠地估计成年人的死亡率的概率窒息。

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