Personalized prediction of the probability of developing arterial hypertension and coronary heart disease in miners with anthracosilicosis using an automated system

Q4 Medicine
N. I. Panev, S. N. Filimonov, R. N. Panev, N. Evseeva, O. Korotenko
{"title":"Personalized prediction of the probability of developing arterial hypertension and coronary heart disease in miners with anthracosilicosis using an automated system","authors":"N. I. Panev, S. N. Filimonov, R. N. Panev, N. Evseeva, O. Korotenko","doi":"10.47470/0016-9900-2023-102-7-675-681","DOIUrl":null,"url":null,"abstract":"Introduction. The remaining high level of production-related cardiovascular morbidity necessitates timely preventive measures. The development of an automated forecasting technique will make it possible to implement personalized and differentiated approaches in the prevention of cardiovascular pathology in persons in contact with harmful production factors. \nMaterials and methods. The object of the study were workers employed in underground coal mining: One hundred sixty eight miners with previously diagnosed anthracosilicosis and 151 miners of the control group without lung pathology (a total of 319 people). Identification of diseases of the circulatory system and risk factors was carried out using clinical, laboratory, instrumental methods. The Bayes method was used to develop a forecasting system. The forecasting software as developed in the Lazarus environment using object-oriented programming methods. \nResults. The most informative markers associated with a high probability of developing arterial hypertension and coronary heart disease in workers with anthracosilicosis have been identified. A software “Automated system for personalized prediction of the probability of developing arterial hypertension and coronary heart disease in miners with anthracosilicosis” has been developed. An automated forecasting system determines the degree of risk of diseases based on the results of the sum of prognostic coefficients. \nLimitations. The limitation of the study was related to the sample of coal mine workers examined in the clinic of the Institute, namely: age from 40 to 54 years, long-term (more than 15 years) work experience in harmful working conditions. The study did not include miners who had other occupational diseases besides anthracosilicosis. \nConclusions. An automated system of personalized forecasting ensures the formation of high cardiovascular risk groups with minimal time costs, which allows starting primary prevention of cardiological pathology in a timely manner.","PeriodicalId":12550,"journal":{"name":"Gigiena i sanitariia","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gigiena i sanitariia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47470/0016-9900-2023-102-7-675-681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction. The remaining high level of production-related cardiovascular morbidity necessitates timely preventive measures. The development of an automated forecasting technique will make it possible to implement personalized and differentiated approaches in the prevention of cardiovascular pathology in persons in contact with harmful production factors. Materials and methods. The object of the study were workers employed in underground coal mining: One hundred sixty eight miners with previously diagnosed anthracosilicosis and 151 miners of the control group without lung pathology (a total of 319 people). Identification of diseases of the circulatory system and risk factors was carried out using clinical, laboratory, instrumental methods. The Bayes method was used to develop a forecasting system. The forecasting software as developed in the Lazarus environment using object-oriented programming methods. Results. The most informative markers associated with a high probability of developing arterial hypertension and coronary heart disease in workers with anthracosilicosis have been identified. A software “Automated system for personalized prediction of the probability of developing arterial hypertension and coronary heart disease in miners with anthracosilicosis” has been developed. An automated forecasting system determines the degree of risk of diseases based on the results of the sum of prognostic coefficients. Limitations. The limitation of the study was related to the sample of coal mine workers examined in the clinic of the Institute, namely: age from 40 to 54 years, long-term (more than 15 years) work experience in harmful working conditions. The study did not include miners who had other occupational diseases besides anthracosilicosis. Conclusions. An automated system of personalized forecasting ensures the formation of high cardiovascular risk groups with minimal time costs, which allows starting primary prevention of cardiological pathology in a timely manner.
使用自动化系统对炭黑矽肺矿工发生动脉高血压和冠心病的概率进行个性化预测
介绍与生产相关的心血管发病率居高不下,需要及时采取预防措施。自动化预测技术的发展将有可能在接触有害生产因素的人中实施个性化和差异化的方法来预防心血管病理。材料和方法。研究对象是受雇于地下煤矿的工人:168名先前诊断为炭疽病的矿工和151名没有肺部病理的对照组矿工(共319人)。循环系统疾病和危险因素的识别采用临床、实验室和仪器方法进行。使用贝叶斯方法开发了一个预测系统。在Lazarus环境中使用面向对象编程方法开发的预测软件。后果已经确定了与炭疽病工人患动脉高血压和冠心病的高概率相关的信息量最大的标志物。开发了一个软件“炭疽病矿工患动脉高压和冠心病概率的个性化预测自动化系统”。自动预测系统基于预后系数的总和的结果来确定疾病的风险程度。局限性该研究的局限性与该研究所诊所检查的煤矿工人样本有关,即:年龄在40至54岁之间,长期(超过15年)在有害工作条件下工作。该研究不包括除炭疽病外还患有其他职业病的矿工。结论。个性化预测的自动化系统确保以最小的时间成本形成心血管高危人群,从而能够及时开始心脏病病理学的初级预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Gigiena i sanitariia
Gigiena i sanitariia Environmental Science-Pollution
CiteScore
0.80
自引率
0.00%
发文量
192
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信