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不同糖尿病患者集群中典型糖尿病相关并发症的风险:九种风险因素分析

Risk of Typical Diabetes-Associated Complications in Different Clusters of Diabetic Patients: Analysis of Nine Risk Factors.

作者信息

Leutner Michael, Haug Nils, Bellach Luise, Dervic Elma, Kautzky Alexander, Klimek Peter, Kautzky-Willer Alexandra

机构信息

Department of Internal Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria.

Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria.

出版信息

J Pers Med. 2021 Apr 22;11(5):328. doi: 10.3390/jpm11050328.


DOI:10.3390/jpm11050328
PMID:33922088
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8143487/
Abstract

OBJECTIVES: Diabetic patients are often diagnosed with several comorbidities. The aim of the present study was to investigate the relationship between different combinations of risk factors and complications in diabetic patients. RESEARCH DESIGN AND METHODS: We used a longitudinal, population-wide dataset of patients with hospital diagnoses and identified all patients ( = 195,575) receiving a diagnosis of diabetes in the observation period from 2003-2014. We defined nine ICD-10-codes as risk factors and 16 ICD-10 codes as complications. Using a computational algorithm, cohort patients were assigned to clusters based on the risk factors they were diagnosed with. The clusters were defined so that the patients assigned to them developed similar complications. Complication risk was quantified in terms of relative risk (RR) compared with healthy control patients. RESULTS: We identified five clusters associated with an increased risk of complications. A combined diagnosis of arterial hypertension (aHTN) and dyslipidemia was shared by all clusters and expressed a baseline of increased risk. Additional diagnosis of (1) smoking, (2) depression, (3) liver disease, or (4) obesity made up the other four clusters and further increased the risk of complications. Cluster 9 (aHTN, dyslipidemia and depression) represented diabetic patients at high risk of angina pectoris "AP" (RR: 7.35, CI: 6.74-8.01), kidney disease (RR: 3.18, CI: 3.04-3.32), polyneuropathy (RR: 4.80, CI: 4.23-5.45), and stroke (RR: 4.32, CI: 3.95-4.71), whereas cluster 10 (aHTN, dyslipidemia and smoking) identified patients with the highest risk of AP (RR: 10.10, CI: 9.28-10.98), atherosclerosis (RR: 4.07, CI: 3.84-4.31), and loss of extremities (RR: 4.21, CI: 1.5-11.84) compared to the controls. CONCLUSIONS: A comorbidity of aHTN and dyslipidemia was shown to be associated with diabetic complications across all risk-clusters. This effect was amplified by a combination with either depression, smoking, obesity, or non-specific liver disease.

摘要

目的:糖尿病患者常被诊断出患有多种合并症。本研究的目的是调查糖尿病患者中不同风险因素组合与并发症之间的关系。 研究设计与方法:我们使用了一个包含医院诊断信息的纵向全人群数据集,确定了在2003年至2014年观察期内所有被诊断为糖尿病的患者(n = 195,575)。我们将9个ICD - 10编码定义为风险因素,16个ICD - 10编码定义为并发症。使用一种计算算法,根据队列患者被诊断出的风险因素将其分配到不同的组群中。组群的定义是,分配到这些组群中的患者会出现相似的并发症。与健康对照患者相比,并发症风险通过相对风险(RR)进行量化。 结果:我们确定了五个与并发症风险增加相关的组群。所有组群都存在动脉高血压(aHTN)和血脂异常的联合诊断,这表明了风险增加的基线情况。额外诊断出(1)吸烟、(2)抑郁症、(3)肝病或(4)肥胖构成了其他四个组群,并进一步增加了并发症风险。第9组(aHTN、血脂异常和抑郁症)代表了患心绞痛“AP”(RR:7.35,CI:6.74 - 8.01)、肾病(RR:3.18,CI:3.04 - 3.32)、多发性神经病变(RR:4.80,CI:4.23 - 5.45)和中风(RR:4.32,CI:3.95 - 4.71)风险较高的糖尿病患者,而第10组(aHTN、血脂异常和吸烟)确定的患者与对照组相比,患AP(RR:10.10,CI:9.28 - 10.98)、动脉粥样硬化(RR:4.07,CI:3.84 - 4.31)和肢体缺失(RR:4.21,CI:1.5 - 11.84)的风险最高。 结论:aHTN和血脂异常的合并症在所有风险组群中均显示与糖尿病并发症相关。与抑郁症、吸烟、肥胖或非特异性肝病中的任何一种合并,这种影响会被放大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/bfd488e212b3/jpm-11-00328-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/0487ae5e698c/jpm-11-00328-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/273c2f0f684b/jpm-11-00328-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/bfd488e212b3/jpm-11-00328-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/0487ae5e698c/jpm-11-00328-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/273c2f0f684b/jpm-11-00328-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bd1/8143487/bfd488e212b3/jpm-11-00328-g003.jpg

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本文引用的文献

[1]
Combinatorial K-Means Clustering as a Machine Learning Tool Applied to Diabetes Mellitus Type 2.

Int J Environ Res Public Health. 2021-2-17

[2]
Decompression of Multimorbidity Along the Disease Trajectories of Diabetes Mellitus Patients.

Front Physiol. 2021-1-5

[3]
Screening Model for Estimating Undiagnosed Diabetes among People with a Family History of Diabetes Mellitus: A KNHANES-Based Study.

Int J Environ Res Public Health. 2020-11-30

[4]
Sex-specific trends in smoking prevalence over seven years in different Austrian populations: results of a time-series cross-sectional analysis.

BMJ Open. 2020-9-9

[5]
Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study.

BMJ Open Diabetes Res Care. 2020-8

[6]
Obesity, clinical, and genetic predictors for glycemic progression in Chinese patients with type 2 diabetes: A cohort study using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank.

PLoS Med. 2020-7-28

[7]
Factors Associated with Risk of Diabetic Complications in Novel Cluster-Based Diabetes Subgroups: A Japanese Retrospective Cohort Study.

J Clin Med. 2020-7-2

[8]
Validation of distinct type 2 diabetes clusters and their association with diabetes complications in the DEVOTE, LEADER and SUSTAIN-6 cardiovascular outcomes trials.

Diabetes Obes Metab. 2020-9

[9]
Development and Validation of Two Self-Reported Tools for Insulin Resistance and Hypertension Risk Assessment in A European Cohort: The Feel4Diabetes-Study.

Nutrients. 2020-3-30

[10]
High-risk multimorbidity patterns on the road to cardiovascular mortality.

BMC Med. 2020-3-10

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