Analyses of longitudinal, hospital clinical laboratory data with application to blood glucose concentrations.
Analyses of longitudinal, hospital clinical laboratory data with application to blood glucose concentrations.
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DOI：
10.1002/sim.4352
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发表时间：
2011-11-30
影响因子：
2
通讯作者：
Miller, Randolph A.
中科院分区：
文献类型：
--
作者：
Schildcrout, Jonathan S.;Haneuse, Sebastien;Peterson, Josh F.;Denny, Joshua C.;Matheny, Michael E.;Waitman, Lemuel R.;Miller, Randolph A.
电子病历（EMR）系统为研究人员提供了调查广泛科学问题的机会。然而，与有目的的研究设计相反，EMR数据采集程序通常与任何特定假设不一致。因此，后续调查需要详细描述电子病历数据基础的临床程序和方案，并仔细考虑模型选择。例如，许多重症监护室目前实施胰岛素输注方案，以更好地控制患者的血糖水平。该方案使用先前的血糖水平来部分确定如何调整输液速率。这种反馈循环将时间相关的混淆引入到纵向分析中，即使它们对分析师来说并不总是显而易见的。在本文中，我们回顾了常用的纵向模型规范和解释，并展示了这些在基于医院的临床方案中是如何特别重要的。我们表明，各种模型之间的参数关系可以用来识别和表征时间相关混淆的影响，因此有助于解释看似不协调的结论。我们还回顾了在存在时间依赖性混淆的情况下重要的估计挑战，并展示了某些模型规范如何或多或少地容易受到偏差的影响。为了说明这些观点，我们根据重症监护病房的数据，对血糖水平和胰岛素剂量之间的关系进行了详细分析。
Electronic medical record (EMR) systems afford researchers with opportunities to investigate a broad range of scientific questions. In contrast to purposeful study designs, however, EMR data acquisition procedures typically do not align with any specific hypothesis. Subsequent investigations therefore require detailed characterization of clinical procedures and protocols that underlie EMR data, as well as careful consideration of model choice. For example, many intensive care units currently implement insulin infusion protocols to better control patients’ blood glucose levels. The protocols use prior glucose levels to determine, in part, how to adjust the infusion rate. Such feedback loops introduce time-dependent confounding into longitudinal analyses even though they may not always be evident to the analyst. In this paper, we review commonly used longitudinal model specifications and interpretations and show how these are particularly important in the presence of hospital-based clinical protocols. We show that parameter relationships among various models can be used to identify and characterize the impact of time-dependent confounding and therefore help explain seemingly incongruous conclusions. We also review important estimation challenges in the presence of time-dependent confounding and show how certain model specifications may be more or less susceptible to bias. To illustrate these points, we present a detailed analysis of the relationship between blood glucose levels and insulin doses on the basis of data from an intensive care unit.
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影响因子：
5
作者：
Haight, T;Tager, I;van der Laan, M
通讯作者：
van der Laan, M
影响因子：
158.5
作者：
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DOI：
10.1198/016214501753168154
发表时间：
2001-06-01
影响因子：
3.7
作者：
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作者：
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通讯作者：
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影响因子：
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作者：
Hernán, MA;Robins, JM
通讯作者：
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