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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Tight glycemic control in critical care - The leading role of insulin sensitivity and patient variability: A review and model-based analysis
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Tight glycemic control in critical care - The leading role of insulin sensitivity and patient variability: A review and model-based analysis

机译：重症监护中严格的血糖控制-胰岛素敏感性和患者变异性的主导作用：综述和基于模型的分析

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Tight glycemic control (TGC) has emerged as a major research focus in critical care due to its potential to simultaneously reduce both mortality and costs. However, repeating initial successful TGC trials that reduced mortality and other outcomes has proven difficult with more failures than successes. Hence, there has been growing debate over the necessity of TGC, its goals, the risk of severe hypoglycemia, and target cohorts. This paper provides a review of TGC via new analyses of data from several clinical trials, including SPRINT, Glucontrol and a recent NICU study. It thus provides both a review of the problem and major background factors driving it, as well as a novel model-based analysis designed to examine these dynamics from a new perspective. Using these clinical results and analysis, the goal is to develop new insights that shed greater light on the leading factors that make TGC difficult and inconsistent, as well as the requirements they thus impose on the design and implementation of TGC protocols. A model-based analysis of insulin sensitivity using data from three different critical care units, comprising over 75,000h of clinical data, is used to analyse variability in metabolic dynamics using a clinically validated model-based insulin sensitivity metric (S I). Variation in S I provides a new interpretation and explanation for the variable results seen (across cohorts and studies) in applying TGC. In particular, significant intra- and inter-patient variability in insulin resistance (1/S I) is seen be a major confounder that makes TGC difficult over diverse cohorts, yielding variable results over many published studies and protocols. Further factors that exacerbate this variability in glycemic outcome are found to include measurement frequency and whether a protocol is blind to carbohydrate administration.
机译：严格的血糖控制（TGC）已成为重症监护的主要研究重点，因为它具有同时降低死亡率和成本的潜力。然而，事实证明，要重复进行最初的成功的TGC试验以降低死亡率和其他结果是困难的，失败多于成功。因此，关于TGC的必要性，其目标，严重低血糖的风险以及目标人群的争论越来越多。本文通过对包括SPRINT，Glucontrol和最近的NICU研究在内的多个临床试验的数据进行了新的分析，对TGC进行了综述。因此，它既提供了对问题和驱动其的主要背景因素的回顾，还提供了一种新颖的基于模型的分析，旨在从新的角度检查这些动态。利用这些临床结果和分析，目标是开发新的见解，从而更深入地了解导致TGC困难和不一致的主要因素，以及由此对TGC协议的设计和实施提出的要求。使用来自三个不同重症监护病房的数据进行的基于模型的胰岛素敏感性分析，包括超过75,000h的临床数据，用于通过临床验证的基于模型的胰岛素敏感性度量（S I）分析代谢动力学的变异性。 S I的变化为应用TGC时（在整个队列和研究中）看到的可变结果提供了新的解释和解释。特别是，胰岛素抵抗（1 / S I）的患者内和患者间显着差异被认为是一个主要的混杂因素，这使得TGC在不同人群中难以进行，并在许多已发表的研究和方案中产生了可变的结果。发现加剧血糖结果变异性的其他因素包括测量频率以及方案是否不接受碳水化合物治疗。

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