利用结构方程模型建立巴基斯坦儿童先天性心脏病的预测模型。

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS BMC Medical Informatics and Decision Making Pub Date : 2024-11-21 DOI:10.1186/s12911-024-02774-y
Sana Shahid, Haris Khurram, Muhammad Ahmed Shehzad, Muhammad Aslam
{"title":"利用结构方程模型建立巴基斯坦儿童先天性心脏病的预测模型。","authors":"Sana Shahid, Haris Khurram, Muhammad Ahmed Shehzad, Muhammad Aslam","doi":"10.1186/s12911-024-02774-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The structural abnormality of the heart and its blood vessels at the time of birth is known as congenital heart disease. Every year in Pakistan, sixty thousand children are born with CHD, and 44 in 1000 die before they are a month old. Various studies used different techniques to estimate the risk factors of congenital heart disease, but these techniques suffer from a deficiency of capacity to present human understanding and a deficiency of adequate data. The current study provided an innovative approach by defining the latent variables to handle this issue and building a reasonable model.</p><p><strong>Method: </strong>Data used in this study has been collected from mothers and hospital records of the children. The dataset contains information on 3900 children who visited the OPD of the Chaudry Pervaiz Elahi Institute of Cardiology (CPEIC) Multan, Pakistan from October 2021 to September 2022. The latent variables were defined from the data and structural equation modeling was used to model them.</p><p><strong>Result: </strong>The results show that there are 53.6% of males have acyanotic CHD and 54.5% have cyanotic CHD. There are 46.4% of females have acyanotic CHD and 45.5% have cyanotic CHD. The children who have no diabetes in the family are 64.0% and children who have diabetes in the family are 36.0% in acyanotic CHD, the children who have no diabetes in the family are 59.7% and children have diabetes in the family are 40.3% in cyanotic CHD. The value of standardized root mean residual is 0.087 is less than 0.089 which shows that the model is a good fit. The value of root mean square error of approximation is 0.113 is less than 0.20 which also shows the good fit of the model.</p><p><strong>Conclusion: </strong>It was concluded that the model is a good fit. Also, the latent variables, socioeconomic factors, and environmental factors of mothers during pregnancy have a significant effect in causing cyanotic while poor general health factor increases the risk of Acyanotic congenital heart disease.</p>","PeriodicalId":9340,"journal":{"name":"BMC Medical Informatics and Decision Making","volume":"24 1","pages":"351"},"PeriodicalIF":3.3000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11580548/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictive model for congenital heart disease in children of Pakistan by using structural equation modeling.\",\"authors\":\"Sana Shahid, Haris Khurram, Muhammad Ahmed Shehzad, Muhammad Aslam\",\"doi\":\"10.1186/s12911-024-02774-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The structural abnormality of the heart and its blood vessels at the time of birth is known as congenital heart disease. Every year in Pakistan, sixty thousand children are born with CHD, and 44 in 1000 die before they are a month old. Various studies used different techniques to estimate the risk factors of congenital heart disease, but these techniques suffer from a deficiency of capacity to present human understanding and a deficiency of adequate data. The current study provided an innovative approach by defining the latent variables to handle this issue and building a reasonable model.</p><p><strong>Method: </strong>Data used in this study has been collected from mothers and hospital records of the children. The dataset contains information on 3900 children who visited the OPD of the Chaudry Pervaiz Elahi Institute of Cardiology (CPEIC) Multan, Pakistan from October 2021 to September 2022. The latent variables were defined from the data and structural equation modeling was used to model them.</p><p><strong>Result: </strong>The results show that there are 53.6% of males have acyanotic CHD and 54.5% have cyanotic CHD. There are 46.4% of females have acyanotic CHD and 45.5% have cyanotic CHD. The children who have no diabetes in the family are 64.0% and children who have diabetes in the family are 36.0% in acyanotic CHD, the children who have no diabetes in the family are 59.7% and children have diabetes in the family are 40.3% in cyanotic CHD. The value of standardized root mean residual is 0.087 is less than 0.089 which shows that the model is a good fit. The value of root mean square error of approximation is 0.113 is less than 0.20 which also shows the good fit of the model.</p><p><strong>Conclusion: </strong>It was concluded that the model is a good fit. Also, the latent variables, socioeconomic factors, and environmental factors of mothers during pregnancy have a significant effect in causing cyanotic while poor general health factor increases the risk of Acyanotic congenital heart disease.</p>\",\"PeriodicalId\":9340,\"journal\":{\"name\":\"BMC Medical Informatics and Decision Making\",\"volume\":\"24 1\",\"pages\":\"351\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11580548/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Informatics and Decision Making\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12911-024-02774-y\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL INFORMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Informatics and Decision Making","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12911-024-02774-y","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
引用次数: 0

摘要

背景:出生时心脏及其血管结构异常被称为先天性心脏病。在巴基斯坦,每年有 6 万名儿童出生时患有先天性心脏病,而每 1000 名儿童中就有 44 名在出生一个月前死亡。各种研究使用不同的技术来估算先天性心脏病的风险因素,但这些技术都存在缺乏对人类认识的能力和缺乏足够数据的问题。本研究提供了一种创新方法,通过定义潜在变量来处理这一问题,并建立一个合理的模型:本研究使用的数据来自母亲和医院的儿童记录。数据集包含从 2021 年 10 月至 2022 年 9 月在巴基斯坦木尔坦 Chaudry Pervaiz Elahi心脏病研究所(CPEIC)门诊部就诊的 3900 名儿童的信息。根据数据定义了潜在变量,并使用结构方程模型对其进行建模:结果显示,53.6% 的男性患有无青紫型先天性心脏病,54.5% 的男性患有青紫型先天性心脏病。46.4%的女性患有青紫型先天性心脏病,45.5%患有青紫型先天性心脏病。家族中无糖尿病的儿童患青紫型先天性心脏病的比例为 64.0%,家族中有糖尿病的儿童患青紫型先天性心脏病的比例为 36.0%;家族中无糖尿病的儿童患青紫型先天性心脏病的比例为 59.7%,家族中有糖尿病的儿童患青紫型先天性心脏病的比例为 40.3%。标准化均方根残差值为 0.087,小于 0.089,表明模型拟合良好。近似均方根误差值为 0.113,小于 0.20,也表明模型拟合良好:结论:模型拟合良好。此外,潜在变量、社会经济因素和母亲怀孕期间的环境因素对导致紫绀有显著影响,而不良的一般健康因素会增加患紫绀型先天性心脏病的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Predictive model for congenital heart disease in children of Pakistan by using structural equation modeling.

Background: The structural abnormality of the heart and its blood vessels at the time of birth is known as congenital heart disease. Every year in Pakistan, sixty thousand children are born with CHD, and 44 in 1000 die before they are a month old. Various studies used different techniques to estimate the risk factors of congenital heart disease, but these techniques suffer from a deficiency of capacity to present human understanding and a deficiency of adequate data. The current study provided an innovative approach by defining the latent variables to handle this issue and building a reasonable model.

Method: Data used in this study has been collected from mothers and hospital records of the children. The dataset contains information on 3900 children who visited the OPD of the Chaudry Pervaiz Elahi Institute of Cardiology (CPEIC) Multan, Pakistan from October 2021 to September 2022. The latent variables were defined from the data and structural equation modeling was used to model them.

Result: The results show that there are 53.6% of males have acyanotic CHD and 54.5% have cyanotic CHD. There are 46.4% of females have acyanotic CHD and 45.5% have cyanotic CHD. The children who have no diabetes in the family are 64.0% and children who have diabetes in the family are 36.0% in acyanotic CHD, the children who have no diabetes in the family are 59.7% and children have diabetes in the family are 40.3% in cyanotic CHD. The value of standardized root mean residual is 0.087 is less than 0.089 which shows that the model is a good fit. The value of root mean square error of approximation is 0.113 is less than 0.20 which also shows the good fit of the model.

Conclusion: It was concluded that the model is a good fit. Also, the latent variables, socioeconomic factors, and environmental factors of mothers during pregnancy have a significant effect in causing cyanotic while poor general health factor increases the risk of Acyanotic congenital heart disease.

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
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
期刊最新文献
Creating a data warehouse to support monitoring of NSQHS blood management standard from EMR data. Multimodal machine learning for language and speech markers identification in mental health. Screening for severe coronary stenosis in patients with apparently normal electrocardiograms based on deep learning. Healthcare dashboard technologies and data visualization for lipid management: A scoping review. Predictive model for congenital heart disease in children of Pakistan by using structural equation modeling.
×
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