Rebrin Kerstin, Sheppard Norman F, Steil Garry M
MicroCHIPS, Inc., Bedford, Massachusetts, USA.
J Diabetes Sci Technol. 2010 Sep 1;4(5):1087-98. doi: 10.1177/193229681000400507.
Estimates for delays in the interstitial fluid (ISF) glucose response to changes in blood glucose (BG) differ substantially among research groups. We review these findings along with arguments that continuous glucose monitoring (CGM) devices used to measure ISF delay contribute to the variability. We consider the impact of the ISF delay and review approaches to correct for it, including strategies pursued by the manufacturers of these devices. The focus on how the manufacturers have approached the problem is motivated by the observation that clinicians and researchers are often unaware of how the existing CGM devices process the ISF glucose signal.
Numerous models and simulations were used to illustrate problems related to measurement and correction of ISF glucose delay.
We find that (1) there is no evidence that the true physiologic ISF glucose delay is longer than 5-10 min and that the values longer than this can be explained by delays in CGM filtering routines; (2) the primary impact of the true ISF delay is on sensor calibration algorithms, making it difficult to estimate calibration factors and offset (OS) currents; (3) inaccurate estimates of the sensor OS current result in overestimation of sensor glucose at low values, making it difficult to detect hypoglycemia; (4) many device companies introduce nonlinear components into their filters, which can be expected to confound attempts by investigators to reconstruct BG using linear deconvolution; and (5) algorithms advocated by academic groups are seldom compared to algorithms pursued by industry, making it difficult to ascertain their value.
The absence of any direct comparisons between existing and new algorithms for correcting ISF delay and sensor OS current is, in part, due to the difficulty in extracting relevant details from industry patents and/or extracting unfiltered sensor signals from industry products. The model simulation environment, where all aspects of the signal can be derived, may be more appropriate for developing new filtering and calibration strategies. Nevertheless, clinicians, academic researchers, and the industry would benefit from collaborating when evaluating those strategies.
不同研究团队对组织间液（ISF）葡萄糖对血糖（BG）变化反应延迟的估计差异很大。我们回顾了这些研究结果，并讨论了用于测量ISF延迟的连续葡萄糖监测（CGM）设备导致变异性的相关观点。我们考虑了ISF延迟的影响，并回顾了校正该延迟的方法，包括这些设备制造商所采用的策略。关注制造商如何解决这一问题的动机在于，临床医生和研究人员往往不清楚现有CGM设备如何处理ISF葡萄糖信号。
使用了众多模型和模拟来说明与ISF葡萄糖延迟测量和校正相关的问题。
我们发现：（1）没有证据表明真正的生理性ISF葡萄糖延迟超过5 - 10分钟，超过此值的情况可由CGM过滤程序的延迟来解释；（2）真正的ISF延迟的主要影响在于传感器校准算法，使得难以估计校准因子和偏移（OS）电流；（3）传感器OS电流的不准确估计导致在低值时对传感器葡萄糖的高估，使得难以检测到低血糖；（4）许多设备公司在其过滤器中引入非线性成分，这可能会使研究人员使用线性反卷积重建BG的尝试变得复杂；（5）学术团体倡导的算法很少与行业所采用的算法进行比较，因此难以确定其价值。
现有和新的校正ISF延迟及传感器OS电流算法之间缺乏直接比较，部分原因在于难以从行业专利中提取相关细节和/或从行业产品中提取未过滤的传感器信号。信号所有方面都可推导的模型模拟环境可能更适合开发新的过滤和校准策略。尽管如此，临床医生、学术研究人员和行业在评估这些策略时进行合作将有所裨益。
