2 型糖尿病慢性肾病的预测因素和模型:文献综述

Yan Yang, Bixia Yang, Bin Wang, Hua Zhou, Min Yang, Bicheng Liu
{"title":"2 型糖尿病慢性肾病的预测因素和模型:文献综述","authors":"Yan Yang,&nbsp;Bixia Yang,&nbsp;Bin Wang,&nbsp;Hua Zhou,&nbsp;Min Yang,&nbsp;Bicheng Liu","doi":"10.1002/ctd2.355","DOIUrl":null,"url":null,"abstract":"<p>Diabetes mellitus (DM) has become a major chronic disease seriously affecting human health. Type 2 diabetes mellitus (T2DM) accounts for about 90% of DM patients, which is the largest type. Approximately 25–35% of T2DM patients develop kidney disease, which not only impacts the survival rate and quality of life but also, to the family and society, are of great economic burden. Early identification of high-risk T2DM patients with kidney disease is crucial for initiating targeted prevention and treatment measures in time to reduce or delay the occurrence and progression of diabetic kidney disease. Previous studies have identified a variety of clinical predictors for the progression of renal function in T2DM patients, including proteinuria, estimated glomerular filtration rate, blood glucose, blood pressure, serum uric acid, dyslipidemia, obesity, smoking, duration of DM, age, gender, race, family history of DM, and diabetic retinopathy. Clinical prediction models based on conventional clinical indicators are instrumental in evaluating the risk of kidney disease in T2DM patients, assisting in patient risk stratification. This article systematically reviews the clinical prediction factors and prediction models associated with the progression of renal function in T2DM patients, providing a comprehensive and current reference for improved clinical assessment of the risk of renal function progression.</p>","PeriodicalId":72605,"journal":{"name":"Clinical and translational discovery","volume":"4 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ctd2.355","citationCount":"0","resultStr":"{\"title\":\"Prediction factors and models for chronic kidney disease in type 2 diabetes mellitus: A review of the literature\",\"authors\":\"Yan Yang,&nbsp;Bixia Yang,&nbsp;Bin Wang,&nbsp;Hua Zhou,&nbsp;Min Yang,&nbsp;Bicheng Liu\",\"doi\":\"10.1002/ctd2.355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Diabetes mellitus (DM) has become a major chronic disease seriously affecting human health. Type 2 diabetes mellitus (T2DM) accounts for about 90% of DM patients, which is the largest type. Approximately 25–35% of T2DM patients develop kidney disease, which not only impacts the survival rate and quality of life but also, to the family and society, are of great economic burden. Early identification of high-risk T2DM patients with kidney disease is crucial for initiating targeted prevention and treatment measures in time to reduce or delay the occurrence and progression of diabetic kidney disease. Previous studies have identified a variety of clinical predictors for the progression of renal function in T2DM patients, including proteinuria, estimated glomerular filtration rate, blood glucose, blood pressure, serum uric acid, dyslipidemia, obesity, smoking, duration of DM, age, gender, race, family history of DM, and diabetic retinopathy. Clinical prediction models based on conventional clinical indicators are instrumental in evaluating the risk of kidney disease in T2DM patients, assisting in patient risk stratification. This article systematically reviews the clinical prediction factors and prediction models associated with the progression of renal function in T2DM patients, providing a comprehensive and current reference for improved clinical assessment of the risk of renal function progression.</p>\",\"PeriodicalId\":72605,\"journal\":{\"name\":\"Clinical and translational discovery\",\"volume\":\"4 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ctd2.355\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical and translational discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ctd2.355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and translational discovery","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ctd2.355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

糖尿病(DM)已成为严重影响人类健康的主要慢性疾病。2 型糖尿病(T2DM)约占 DM 患者的 90%,是最大的类型。约 25%-35% 的 T2DM 患者会发展成肾脏疾病,这不仅影响患者的生存率和生活质量,还会给家庭和社会带来巨大的经济负担。早期发现高危 T2DM 肾病患者,对于及时启动有针对性的预防和治疗措施,减少或延缓糖尿病肾病的发生和发展至关重要。以往的研究发现了多种T2DM患者肾功能进展的临床预测指标,包括蛋白尿、估计肾小球滤过率、血糖、血压、血清尿酸、血脂异常、肥胖、吸烟、DM病程、年龄、性别、种族、DM家族史和糖尿病视网膜病变。基于常规临床指标的临床预测模型有助于评估 T2DM 患者的肾病风险,帮助患者进行风险分层。本文系统回顾了与 T2DM 患者肾功能进展相关的临床预测因素和预测模型,为改进肾功能进展风险的临床评估提供了全面、最新的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Prediction factors and models for chronic kidney disease in type 2 diabetes mellitus: A review of the literature

Diabetes mellitus (DM) has become a major chronic disease seriously affecting human health. Type 2 diabetes mellitus (T2DM) accounts for about 90% of DM patients, which is the largest type. Approximately 25–35% of T2DM patients develop kidney disease, which not only impacts the survival rate and quality of life but also, to the family and society, are of great economic burden. Early identification of high-risk T2DM patients with kidney disease is crucial for initiating targeted prevention and treatment measures in time to reduce or delay the occurrence and progression of diabetic kidney disease. Previous studies have identified a variety of clinical predictors for the progression of renal function in T2DM patients, including proteinuria, estimated glomerular filtration rate, blood glucose, blood pressure, serum uric acid, dyslipidemia, obesity, smoking, duration of DM, age, gender, race, family history of DM, and diabetic retinopathy. Clinical prediction models based on conventional clinical indicators are instrumental in evaluating the risk of kidney disease in T2DM patients, assisting in patient risk stratification. This article systematically reviews the clinical prediction factors and prediction models associated with the progression of renal function in T2DM patients, providing a comprehensive and current reference for improved clinical assessment of the risk of renal function progression.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.00
自引率
0.00%
发文量
0
期刊最新文献
Application of machine learning-based phenotyping in individualized fluid management in critically ill patients with heart failure An auxiliary diagnostic approach based on traditional Chinese medicine constitutions for older patients with frailty Use of short-term cervical collars is associated with emotional discomfort Challenges and advances of immune checkpoint therapy Drug repurposing: Bortezomib in the treatment of PTEN-deficient iCCA
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1