基于空腹和餐后血浆葡萄糖和胰岛素浓度的聚类分析

IF 0.7 4区 医学 Q4 ENDOCRINOLOGY & METABOLISM International Journal of Diabetes in Developing Countries Pub Date : 2024-03-07 DOI:10.1007/s13410-024-01322-8
Miguel Altuve, Erika Severeyn
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引用次数: 0

摘要

目的 血浆葡萄糖和胰岛素浓度是用于诊断代谢性疾病,尤其是糖尿病前期和糖尿病的临床指标。本文利用空腹和餐后 2 小时内采集的血浆葡萄糖和胰岛素数据进行了聚类分析。方法通过改变输入 k-means 聚类算法的属性,从一个属性(空腹葡萄糖)到四个属性(空腹和餐后葡萄糖和胰岛素),进行了不同的聚类实验。根据肘法和剪影法,选择了三个聚类来进行聚类实验。结果显示,一个聚类由糖尿病前期患者组成,另一个聚类由糖尿病患者组成,而没有糖尿病前期和糖尿病的受试者被分配到一个单独的聚类中。尽管没有将年龄作为一个属性,但我们观察到三个群组中的受试者年龄范围各不相同。此外,我们还发现空腹和餐后胰岛素水平之间以及空腹和餐后葡萄糖水平之间存在明显的相关性,这表明这些变量之间存在一致的关系,并突出了它们在葡萄糖代谢中的相互依存性。此外,尽管年龄并非考虑的属性,但在聚类中观察到的不同年龄范围表明,年龄可能在糖尿病的发生和发展过程中起着一定的作用。此外,空腹和餐后胰岛素与血糖水平的关联在包括糖尿病患者的群组中表现得更为明显,因为糖尿病患者的胰岛素分泌或作用受到影响。
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Cluster analysis based on fasting and postprandial plasma glucose and insulin concentrations

Objective

Plasma glucose and insulin concentrations are clinical markers used to diagnose metabolic diseases, particularly prediabetes and diabetes. In this paper, we conducted a cluster analysis using plasma glucose and insulin data collected during both fasting and 2-h postprandial periods.

Methods

Different clustering experiments were performed by changing the attributes, from one (fasting glucose) to four (fasting and postprandial glucose and insulin) attributes input to a k-means clustering algorithm. Based on the elbow and silhouette methods, three clusters were chosen to perform the clustering experiments. The Pearson correlation coefficient was utilized to evaluate the association between the levels of glucose and insulin within each created cluster.

Results

Results show that one cluster comprised individuals with prediabetes, another cluster consisted of individuals with diabetes, while subjects without prediabetes and diabetes were assigned to a separate cluster. Despite not being used as an attribute, we observed varying age ranges among subjects in the three clusters. Furthermore, significant correlations were found between fasting and postprandial insulin levels, as well as between fasting and postprandial glucose levels, suggesting a consistent relationship between these variables, and highlighting their interdependence in the context of glucose metabolism.

Conclusion

The clustering analysis successfully differentiated individuals into distinct clusters based on their metabolic conditions, confirming that the approach effectively captured the underlying patterns in the plasma glucose and insulin data. Furthermore, despite not being a considered attribute, the varying age ranges observed within the clusters indicate that age may play a role in the development and progression of diabetes. Additionally, the fasting and postprandial associations in insulin and glucose levels exhibited greater strength in the cluster encompassing individuals with diabetes, where insulin production or action is compromised.

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来源期刊
CiteScore
1.60
自引率
0.00%
发文量
109
审稿时长
6 months
期刊介绍: International Journal of Diabetes in Developing Countries is the official journal of Research Society for the Study of Diabetes in India. This is a peer reviewed journal and targets a readership consisting of clinicians, research workers, paramedical personnel, nutritionists and health care personnel working in the field of diabetes. Original research articles focusing on clinical and patient care issues including newer therapies and technologies as well as basic science issues in this field are considered for publication in the journal. Systematic reviews of interest to the above group of readers are also accepted.
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