首页> 外文期刊>Journal of Diabetes Science and Technology >Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods
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Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

机译:重症患者连续血糖监测数据的复杂性:连续血糖监测设备,传感器位置和去趋势波动分析方法

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Background: Critically ill patients often experience high levels of insulin resistance and stress-induced hyperglycemia, which may negatively impact outcomes. However, evidence surrounding the causes of negative outcomes remains inconclusive. Continuous glucose monitoring (CGM) devices allow researchers to investigate glucose complexity, using detrended fluctuation analysis (DFA), to determine whether it is associated with negative outcomes. The aim of this study was to investigate the effects of CGM device type/calibration and CGM sensor location on results from DFA. Methods: This study uses CGM data from critically ill patients who were each monitored concurrently using Medtronic iPro2s on the thigh and abdomen and a Medtronic Guardian REAL-Time on the abdomen. This allowed interdevice/calibration type and intersensor site variation to be assessed. Detrended fluctuation analysis is a technique that has previously been used to determine the complexity of CGM data in critically ill patients. Two variants of DFA, monofractal and multifractal, were used to assess the complexity of sensor glucose data as well as the precalibration raw sensor current. Monofractal DFA produces a scaling exponent ( H ), where H is inversely related to complexity. The results of multifractal DFA are presented graphically by the multifractal spectrum. Results: From the 10 patients recruited, 26 CGM devices produced data suitable for analysis. The values of H from abdominal iPro2 data were 0.10 (0.03–0.20) higher than those from Guardian REAL-Time data, indicating consistently lower complexities in iPro2 data. However, repeating the analysis on the raw sensor current showed little or no difference in complexity. Sensor site had little effect on the scaling exponents in this data set. Finally, multifractal DFA revealed no significant associations between the multifractal spectrums and CGM device type/calibration or sensor location. Conclusions: Monofractal DFA results are dependent on the device/calibration used to obtain CGM data, but sensor location has little impact. Future studies of glucose complexity should consider the findings presented here when designing their investigations.
机译:背景:重症患者通常会经历高水平的胰岛素抵抗和压力诱发的高血糖症,这可能会对结果产生负面影响。但是,围绕不良结果原因的证据尚无定论。连续葡萄糖监测(CGM)设备使研究人员可以使用去趋势波动分析(DFA)研究葡萄糖的复杂性,以确定其是否与阴性结果有关。这项研究的目的是研究CGM设备类型/校准和CGM传感器位置对DFA结果的影响。方法:本研究使用危重患者的CGM数据,每位患者均通过大腿和腹部的Medtronic iPro2s以及腹部的Medtronic Guardian REAL-Time进行了同时监测。这允许评估设备间/校准类型和传感器间位置变化。去趋势波动分析是一种先前已用于确定危重患者CGM数据复杂性的技术。 DFA的两个变体(单形和多形)用于评估传感器葡萄糖数据的复杂性以及预校准的原始传感器电流。单形DFA产生缩放指数(H),其中H与复杂度成反比。多重分形谱图以图形方式显示了多重分形DFA的结果。结果:从招募的10位患者中,有26台CGM设备产生了适合分析的数据。腹部iPro2数据的H值比Guardian REAL-Time数据的H值高0.10(0.03-0.20),表明iPro2数据的复杂性始终较低。但是,对原始传感器电流进行重复分析表明,复杂度几乎没有差异。传感器位置对该数据集中的缩放指数影响很小。最后,多重分形DFA显示多重分形光谱与CGM设备类型/校准或传感器位置之间没有显着关联。结论:单形DFA结果取决于用于获取CGM数据的设备/校准,但传感器位置几乎没有影响。未来的葡萄糖复杂性研究在设计研究时应考虑此处介绍的发现。

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