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首页> 外文期刊>Journal of breath research >Non-invasive breath monitoring with eNose does not improve glucose diagnostics in critically ill patients in comparison to continuous glucose monitoring in blood
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Non-invasive breath monitoring with eNose does not improve glucose diagnostics in critically ill patients in comparison to continuous glucose monitoring in blood

机译：与Enoses的非侵袭性呼吸监测在血液中连续葡萄糖监测相比，不改善危重病患者的葡萄糖诊断

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Continuous glucose monitoring (CGM) can be beneficial in critically ill patients. Current CGM devices rely on subcutaneous or blood plasma glucose measurements and consequently there is an increased risk of infections and the possibility of loss of blood with each measurement. A potential method to continuously and non-invasively measure blood glucose levels is using exhaled breath. A correlation between blood glucose levels and volatile organic compounds (VOCs) in the exhaled breath was already reported. VOCs can be analyzed continuously using a so-called electronic nose (eNose). We hypothesize that continuous exhaled breath analysis using an eNose can be used to accurately predict blood glucose levels in intubated, mechanically ventilated ICU-patients. Mechanically ventilated patients whose blood glucose concentration was monitored with a CGM device were eligible. An eNose with four metal oxide sensors was used to continuously measure changes in exhaled breath. After pre-processing the data, several regression models were trained, consisting of: (1) only eNose sensor values; (2) only the 1st and 2nd principal components (PC) of eNose values; (3) eNose sensor values and last known blood glucose value as random effect; (4) 1st and 2nd PC of eNose sensor values and CGM value of one minute ago as fixed effect; (5) CGM value of one minute ago as fixed effect. Model performance was measured using the R-2 value, the akaike information criterion and the Clarke error grid. Twenty-three patients were included in the study and 1165 hours of measurements were collected. Performance was low in models 1, 2 and 3 with a mean R-2 of 0.07 [95%-CI: 0.00-0.28], 0.10 [95%-CI: 0.00-0.40] and 0.30 [0.02-0.79], respectively. Performance in models 4 and 5 was better with a mean R-2 of 0.77 [0.02-1.00]. Subsequently, eNose data in model 4 had no added value over using CGM only in model 5. Continuous exhaled breath analysis using this eNose cannot be used to accurately predict blood glucos
机译：连续葡萄糖监测（CGM）可以有益于危重病人。目前的CGM器件依赖于皮下或血浆血浆测量，因此感染风险增加以及每次测量的血液丧失的可能性。连续和非侵入性地测量血糖水平的潜在方法正在使用呼出的呼吸。已经报道了呼出气息中血糖水平和挥发性有机化合物（VOC）之间的相关性。可以使用所谓的电子鼻（Enose）连续分析VOC。我们假设使用ENOSE的连续呼出的呼气分析可用于精确预测插管，机械通风的ICU患者的血糖水平。用CGM装置监测血糖浓度的机械通风患者均有资格。使用四种金属氧化物传感器的产生用于连续测量呼出的呼吸变化。在预处理数据后，培训了几种回归模型，包括：（1）仅产生传感器值; （2）仅有1ST值的第1和第2主组件（PC）; （3）使传感器值和最后已知的血糖值作为随机效应; （4）第一和第2 PC的固化传感器值和1分钟前的CGM值作为固定效果; （5）一分钟的CGM值作为固定效果。使用R-2值，Akaike信息标准和Clarke错误网格测量模型性能。在研究中包含二十三名患者，收集1165小时的测量。模型1,2和3的性能低，平均R-2为0.07 [95％-ci：0.00-0.28]，0.10 [95％-ci：0.00-0.0.40]和0.30 [0.02-0.79]。模型4和5中的性能更好，平均R-2为0.77 [0.02-1.00]。随后，在模型4中的Enose数据在模型5中使用CGM没有增加的值。使用该ENOSE的连续呼出呼气分析不能用于准确预测血液灰松

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