Clustering in gestational diabetes mellitus: A systematic review

医学 妊娠期糖尿病 糖尿病 聚类分析 产科 怀孕 妊娠期 内分泌学 人工智能 计算机科学 遗传学 生物
作者
Wesley Hannah,Balaji Bhavadharini,Viswanathan Baskar,Ranjit Mohan Anjana,Suchitra Chandrasekaran,Ram Uma,Polina Popova,Mohan Deepa,Viswanathan Mohan
出处
期刊:International journal of gynaecology and obstetrics [Elsevier BV]
卷期号:171 (3): 1081-1091
标识
DOI:10.1002/ijgo.70267
摘要

BACKGROUND: Gestational diabetes mellitus (GDM) is a heterogenous disease with significant clinical variation. Studies of GDM clusters that are distinctive in terms of maternal characteristics could pave the way for more personalized treatments. AIM: We aimed to collate studies dealing with clusters of GDM published in the literature. METHODS: A search strategy was developed and databases such as PubMed, EMBASE, Scopus, and Ovid were searched until August 2024. Two reviewers (with a third if there was disagreement) screened the title/abstract and full text of articles and identified studies that performed clustering analysis or reported different clusters of GDM. The findings from the included studies were summarized. RESULTS: From the comprehensive literature search, 1579 studies were identified. After removal of duplicate studies, 990 studies were screened based on title/abstract, from which 24 full-text studies were selected, with 14 studies finally included in this systematic review. From these studies, it can be seen that clustering was performed mainly based on values of oral glucose tolerance tests. Other means of clustering in the literature also included metabolic, insulin, genetic and continuous glucose monitoring parameters. CONCLUSION: There are several studies reporting on clustering of GDM. However, future studies should identify the most appropriate way to stratify women diagnosed with GDM in order to improve pregnancy outcomes and beyond.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wang发布了新的文献求助10
刚刚
我是老大应助琦琦采纳,获得10
1秒前
1秒前
2秒前
3秒前
ju龙哥发布了新的文献求助10
3秒前
和谐乐萱完成签到,获得积分10
4秒前
左左柚柚完成签到,获得积分10
4秒前
半圆完成签到,获得积分10
4秒前
黄景滨完成签到 ,获得积分10
5秒前
SciGPT应助felix采纳,获得10
5秒前
5秒前
曾丽红完成签到,获得积分10
5秒前
Hilary完成签到,获得积分10
6秒前
呆呆发布了新的文献求助10
6秒前
852应助琦琦采纳,获得10
7秒前
ttttttttttg发布了新的文献求助10
7秒前
wanci应助wang采纳,获得10
7秒前
gulugulugulug发布了新的文献求助10
8秒前
公司账号2发布了新的文献求助10
8秒前
Deanna完成签到 ,获得积分10
9秒前
qianyu发布了新的文献求助10
10秒前
swallow完成签到,获得积分10
10秒前
天天快乐应助fauna采纳,获得10
10秒前
wangjialong完成签到,获得积分10
11秒前
phoebe完成签到,获得积分10
12秒前
香蕉觅云应助桃桃采纳,获得10
12秒前
13秒前
13秒前
11关注了科研通微信公众号
14秒前
14秒前
小羿羿呀发布了新的文献求助10
16秒前
16秒前
Eazin发布了新的文献求助10
16秒前
星辰大海应助小管采纳,获得10
17秒前
张张张发布了新的文献求助10
18秒前
铠甲勇士完成签到,获得积分10
18秒前
19秒前
20秒前
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Moody's Ratings Rising AI spending narrows the gap, but US hyperscalers retain edge over Chinese peers 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7695801
求助须知:如何正确求助?哪些是违规求助? 9256215
关于积分的说明 20001231
捐赠科研通 7270224
什么是DOI,文献DOI怎么找? 3292578
关于科研通互助平台的介绍 2448209
邀请新用户注册赠送积分活动 2298236