Inferring Insulin Secretion Rate from Sparse Patient Glucose and Insulin Measures
Inferring Insulin Secretion Rate from Sparse Patient Glucose and Insulin Measures
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从稀疏患者血糖和胰岛素测量值推断胰岛素分泌率
DOI：
10.1101/2022.03.10.22272234
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发表时间：
2022
影响因子：
4
通讯作者：
Bruce J. Gluckman
中科院分区：
文献类型：
--
作者：
Rammah M. Abohtyra;Christine L. Chan;D. Albers;Bruce J. Gluckman
胰岛素分泌率 (ISR) 包含的信息可以提供个人对内分泌功能的定量了解。如果可以从测量中可靠地推断出 ISR，它可以用于理解和临床诊断血糖调节系统的问题。目的：本研究旨在开发一种基于模型的方法，以稳健的方式推断不同血糖状况人群的 ISR 和相关生理信息的参数化。开发的算法适用于密集或稀疏采样的血浆葡萄糖/胰岛素测量，其中稀疏性是根据相对于动态的最快时间尺度的采样时间来定义的。方法：开发了一种算法，用于参数化和验证不同房室模型的 ISR 功能形式，这些模型具有未知但可估计的 ISR 功能和描述胰岛素积累动态的吸收/衰减率。当测量 c 肽时，该方法和模型同样适用于 c 肽分泌率 (CSR)。拟合精度取决于测量轨迹的重建误差，以及测量 c 肽时 CSR 和 ISR 之间的关系。该算法应用于 17 名具有正常血糖调节系统的受试者和 9 名患有囊性纤维化相关糖尿病 (CFRD) 受试者的数据，其中在口服葡萄糖耐量试验 (OGTT) 过程中测量了葡萄糖、胰岛素和 C 肽。结果：对于 17 名对照受试者中的 12 名和 9 名 CFRD 受试者中的 7 名，这种基于模型的算法以相对较低的重建误差推断出 ISR 和 CSR 函数的参数化。我们证明，当存在可疑测量点时，可以用这种方法质疑排除它们的有效性。意义：一种新的估计方法可以通过胰岛素、C 肽和血浆葡萄糖浓度的稀疏测量来推断 ISR 和 CSR 功能特征以及血浆胰岛素和 C 肽吸收率。我们提出了一种根据重建误差询问和排除潜在错误 OGTT 测量点的方法。
The insulin secretion rate (ISR) contains information that can provide a personal, quantitative understanding of endocrine function. If the ISR can be reliably inferred from measurements, it could be used for understanding and clinically diagnosing problems with the glucose regulation system. Objective: This study aims to develop a model-based method for inferring a parametrization of the ISR and related physiological information among people with different glycemic conditions in a robust manner. The developed algorithm is applicable for both dense or sparsely sampled plasma glucose/insulin measurements, where sparseness is defined in terms of sampling time with respect to the fastest time scale of the dynamics. Methods: An algorithm for parametrizing and validating a functional form of the ISR for different compartmental models with unknown but estimable ISR function and absorption/decay rates describing the dynamics of insulin accumulation was developed. The method and modeling applies equally to c-peptide secretion rate (CSR) when c-peptide is measured. Accuracy of fit is reliant on reconstruction error of the measured trajectories, and when c-peptide is measured the relationship between CSR and ISR. The algorithm was applied to data from 17 subjects with normal glucose regulatory systems and 9 subjects with cystic fibrosis related diabetes (CFRD) in which glucose, insulin and c-peptide were measured in course of oral glucose tolerance tests (OGTT). Results: This model-based algorithm inferred parametrization of the ISR and CSR functional with relatively low reconstruction error for 12 of 17 control and 7 of 9 CFRD subjects. We demonstrate that when there are suspect measurements points, the validity of excluding them may be interrogated with this method. Significance: A new estimation method is available to infer the ISR and CSR functional profile along with plasma insulin and c-peptide absorption rates from sparse measurements of insulin, c-peptide, and plasma glucose concentrations. We propose a method to interrogate and exclude potentially erroneous OGTT measurement points based on reconstruction errors.
影响因子：
15.9
作者：
BERGMAN, RN;PHILLIPS, LS;COBELLI, C
通讯作者：
COBELLI, C
DOI：
10.1016/j.ajpath.2015.10.001
发表时间：
2016-02
期刊：
The FASEB Journal
影响因子：
--
作者：
J. Zullo;Jie Fan;Tala Azar;Wanyi Yen;Min Zeng;Jun Chen;Brian B. Ratliff;Jun Song;J. Tarbell;M. Goligorsky;B. Fu
通讯作者：
J. Zullo;Jie Fan;Tala Azar;Wanyi Yen;Min Zeng;Jun Chen;Brian B. Ratliff;Jun Song;J. Tarbell;M. Goligorsky;B. Fu
用于估计肝前胰岛素分泌的组合模型方法的批判性评估。
DOI：
10.1152/ajpendo.1998.274.1.e172
发表时间：
1998
期刊：
The American journal of physiology
影响因子：
--
作者：
Watanabe,RM;Steil,GM;Bergman,RN
通讯作者：
Bergman,RN