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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DOI：
10.3389/fphys.2022.893862
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发表时间：
2022
影响因子：
4
通讯作者：
Gluckman, Bruce J.
中科院分区：
文献类型：
--
作者：
Abohtyra, Rammah M.;Chan, Christine L.;Albers, David J.;Gluckman, Bruce J.
胰岛素分泌率（ISR）包含的信息可以提供对内分泌功能的个人定量了解。如果ISR可以从测量中可靠地推断出来，它可以用于理解和临床诊断葡萄糖调节系统的问题。 目的：本研究旨在开发一种基于模型的方法，用于以稳健的方式推断具有不同血糖状况的人之间的ISR和相关生理信息的参数化。所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，其中稀疏度是根据相对于动态的最快时间尺度的采样时间来定义的。 研究方法：开发了一种算法，用于参数化和验证不同房室模型的ISR函数形式，这些模型具有未知但可估计的ISR函数和描述胰岛素蓄积动力学的吸收/衰减速率。当测量C肽时，该方法和建模同样适用于C肽分泌速率（CSR）。拟合的准确性依赖于测量轨迹的重建误差，以及当测量c肽时CSR和ISR之间的关系。该算法被应用到17名受试者与正常的葡萄糖调节系统和9名受试者与囊性纤维化相关的糖尿病（CFRD），其中葡萄糖，胰岛素和C-肽的口服葡萄糖耐量试验（OGTT）过程中测量的数据。 结果如下：该模型为基础的算法推断参数化的ISR和CSR功能与相对较低的重建误差为12 17个控制和7 9面板堆石坝科目。我们证明，当有可疑的测量点，排除它们的有效性可以用这种方法进行询问。 重要性：一种新的估计方法可用于从胰岛素、c肽和血糖浓度的稀疏测量值推断ISR和CSR功能谱沿着血浆胰岛素和c肽吸收率。我们提出了一种方法来询问和排除潜在的错误OGTT测量点的基础上重建误差。
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.
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影响因子：
2
作者：
Topp, B;Promislow, K;Finegood, DT
通讯作者：
Finegood, DT
影响因子：
5.8
作者：
EATON, RP;ALLEN, RC;STANDEFER, J
通讯作者：
STANDEFER, J
DOI：
10.1016/s1521-690x(03)00042-3
发表时间：
2003-09-01
影响因子：
7.4
作者：
Pacini, G;Mari, A
通讯作者：
Mari, A
DOI：
10.1073/pnas.0230450100
发表时间：
2003-04-01
影响因子：
11.1
作者：
Farris, W;Mansourian, S;Guénette, S
通讯作者：
Guénette, S
影响因子：
56.9
作者：
STEINER, DF;CUNNINGHAM, D;ATEN, B
通讯作者：
ATEN, B