Improving risk classification of critical illness with biomarkers: A simulation study
Improving risk classification of critical illness with biomarkers: A simulation study
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DOI：
10.1016/j.jcrc.2012.12.001
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发表时间：
2013-10-01
影响因子：
3.7
通讯作者：
Pepe, Margaret S.
中科院分区：
文献类型：
--
作者：
Seymour, Christopher W.;Cooke, Colin R.;Pepe, Margaret S.
目的：最佳分流的危重病患者的风险需要准确的风险预测，但很少有数据的性能标准所需的潜在的生物标志物是临床useful existence.Materials和Methods：我们研究了一个成年队列的nonarrest，非创伤性紧急医疗服务遇到运送到医院，从2002年至2006年。我们模拟假设的生物标志物越来越多地与危重病住院期间，并确定了生物标志物的强度和样本量，以提高风险分类超越最佳临床model.Results：57 647遭遇，3121（5.4%）住院危重病和54 526（94.6%）无危重病。增加一种中等强度的生物标志物（优势比，3.0，危重病）的临床模型，改善了区分（c统计，0.85 vs 0.8; P < .01）和重新分类（净改叙改进，0.15; 95%置信区间，0.13-0.18），最高风险类别的病例比例增加了+8.6%（95%置信区间，7.5%-10.8%）。在临床风险评分中引入生物标志物和生理变量之间的相关性并没有改变结果。净重新分类的统计学显着变化需要至少1000 subjects.Conclusions的样本量：临床模式的危重病分诊可以显着改善纳入生物标志物，但大量的样本量和生物标志物的强度可能需要。(C)2013 Elsevier Inc. All rights reserved.
Purpose: Optimal triage of patients at risk for critical illness requires accurate risk prediction, yet few data on the performance criteria required of a potential biomarker to be clinically useful exists.Materials and Methods: We studied an adult cohort of nonarrest, nontrauma emergency medical services encounters transported to a hospital from 2002 to 2006. We simulated hypothetical biomarkers increasingly associated with critical illness during hospitalization and determined the biomarker strength and sample size necessary to improve risk classification beyond a best clinical model.Results: Of 57 647 encounters, 3121 (5.4%) were hospitalized with critical illness and 54 526 (94.6%) without critical illness. The addition of a moderate-strength biomarker (odds ratio, 3.0, for critical illness) to a clinical model improved discrimination (c statistic, 0.85 vs 0.8; P < .01) and reclassification (net reclassification improvement, 0.15; 95% confidence interval, 0.13-0.18) and increased the proportion of cases in the highest-risk category by +8.6% (95% confidence interval, 7.5%-10.8%). Introducing correlation between the biomarker and physiological variables in the clinical risk score did not modify the results. Statistically significant changes in net reclassification required a sample size of at least 1000 subjects.Conclusions: Clinical models for triage of critical illness could be significantly improved by incorporating biomarkers, yet substantial sample sizes and biomarker strength may be required. (C) 2013 Elsevier Inc. All rights reserved.