数智赋能心脑血管病危险因素监测与防治：现状和展望

doi:10.3969/j.issn.1673-5765.2025.01.005

摘要/Abstract

摘要： 随着可穿戴设备、人工智能、大数据等技术的兴起，慢性病管理不断向数智化方向深入发展。在心脑血管病危险因素监测和防治领域，数智技术的作用尤为突出和重要。本文对数智技术在高血压、糖尿病、不良生活方式等心脑血管病危险因素监测和防治方面的应用现状进行综述，同时提出数智技术未来发展可能面临的问题和挑战，旨在为数智技术在心脑血管病防治中的相关应用和研究提供参考。

文章导读： 数智赋能心脑血管病防治正在为心脑血管病高危人群筛查、监测及疾病防治提供有效的科技支撑，同时数智技术本身在开发、应用、推广过程中也面临着巨大挑战，如患者隐私泄露、数据安全、适老化程度低、数字鸿沟现象等。

关键词: 数智技术; 心脑血管病; 危险因素; 监测; 防治

Abstract: With the rise of wearable devices, artificial intelligence, big data, and other techniques, the management of chronic diseases has been continuously evolving towards digital intelligence. In the field of monitoring and preventing of cardio-cerebrovascular diseases risk factors, the role of digital intelligent technology is particularly prominent and important. This paper reviews the application status of digital intelligent technology in monitoring and preventing the risk factors of cardio-cerebrovascular diseases, such as hypertension, diabetes, and unhealthy lifestyles. It also proposes the possible problems and challenges that digital intelligent technology may face in future development, aiming to provide references for the coming application and research of digital intelligent technology in the prevention and treatment of cardio-cerebrovascular diseases.

Key words: Digital intelligent technology; Cardio-cerebrovascular disease; Risk factor; Monitoring; Prevention

中图分类号:

R74
R318

刘利强, 李光耀, 吉训明. 数智赋能心脑血管病危险因素监测与防治：现状和展望[J]. 中国卒中杂志, 2025, 20(1): 41-47.

LIU Liqiang, LI Guangyao, JI Xunming. Digital Intelligence Empowering the Monitoring and Prevention of Cardio-Cerebrovascular Disease Risk Factors: Current Status and Prospect[J]. Chinese Journal of Stroke, 2025, 20(1): 41-47.

参考文献

[1] 刘明波，何新叶，杨晓红，等. 《中国心血管健康与疾病报告2023》要点解读[J]. 中国心血管杂志，2024，29（4）：305-324.
LIU M B，HE X Y，YANG X H，et al. Interpretation of Report on Cardiovascular Health and Diseases in China 2023[J]. Chin J Cardiovasc Med，2024，29（4）：305-324.
[2] 中华医学会神经病学分会，中华医学会神经病学分会脑血管病学组. 中国脑血管病一级预防指南2019[J]. 中华神经科杂志，2019，52（9）：684-709.
Chinese Society of Neurology，Chinese Stroke Society. Guidelines for the primary prevention of cerebrovascular diseases in China 2019[J]. Chin J Neurol，2019，52（9）：684-709.
[3] SIRSAT M S，FERMÉ E，CÂMARA J. Machine learning for brain stroke：a review[J/OL]. J Stroke Cerebrovasc Dis，2020，29（10）：105162[2024-11-22]. https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.105162.
[4] 中华医学会，中华医学会杂志社，高血压联盟（中国），等. 中国动态血压监测基层应用指南（2024年）[J]. 中华全科医师杂志，2024，23（12）：1242-1255.
Chinese Medical Association，Chinese Medical Association Publishing House，Chinese Hypertension League，et al. Chinese practice guideline for ambulatory blood pressure monitoring in primary care（2024）[J]. Chin J Gen Pract，2024，23（12）：1242-1255.
[5] KARIO K，NOMURA A，HARADA N，et al. Efficacy of a digital therapeutics system in the management of essential hypertension：the HERB-DH1 pivotal trial[J]. Eur Heart J，2021，42（40）：4111-4122.
[6] KARIO K，HARADA N，OKURA A. The first software as medical device of evidence-based hypertension digital therapeutics for clinical practice[J]. Hypertens Res，2022，45（12）：1899-1905.
[7] CASTELA F J，FOLKERTAMA P，GANNAMANI R，et al. Effect of a digitally-enabled，preventive health program on blood pressure in an adult，Dutch general population cohort：an observational pilot study[J/OL]. Int J Environ Res Public Health，2022，19（7）：4171[2024-11-22]. https://doi.org/10.3390/ijerph19074171.
[8] 赖晋媛，刘凯，徐英，等. 基于数字化远程血压监测平台的高血压健康管理方案在原发性高血压患者中的应用[J]. 中国医药导报，2024，21（8）：171-174，178.
LAI J Y，LIU K，XU Y，et al. Application of hypertension health management plan based on digital remote blood pressure monitoring platform in patients with essential hypertension[J]. China Medical Herald，2024，21（8）：171-174，178.
[9] 刘政，王锡榜，周艳红，等. 互联网+医生的社区高血压患者慢病管理模式效果[J]. 解放军医院管理杂志，2020，27（2）：156-161.
LIU Z，WANG X B，ZHOU Y H，et al. Application effect of chronic disease management mode of hypertension patients in community from internet + doctor[J]. Hosp Admin J Chin PLA，2020，27（2）：156-161.
[10] 王朋朋，应燕萍，高忠兰，等. App在H型高血压出院患者延续护理中的应用[J]. 护士进修杂志，2016，31（12）：1129-1132.
WANG P P，YING Y P，GAO Z L，et al. Application of App in continued nursing care for discharged patients with H-type hypertension[J]. Journal of Nurses Training，2016，31（12）：1129-1132.
[11] 徐琢，李江津，王婧，等. 移动互联网对在职高血压患者自我管理的影响研究[J]. 中国全科医学，2017，20（S2）：242-244.
XU Z，LI J J，WANG J，et al. Impact of mobile internet on self-management in in-service hypertensive patients[J]. Chinese General Practice，2017，20（S2）：242-244.
[12] CHANDLER J，SOX L，DIAZ V，et al. Impact of 12-month smartphone breathing meditation program upon systolic blood pressure among non-medicated stage 1 hypertensive adults[J/OL]. Int J Environ Res Public Health，2020，17（6）：1955[2024-11-22]. https://doi.org/10.3390/ijerph17061955.
[13] MCMANUS R J，MANT J，HAQUE M S，et al. Effect of self-monitoring and medication self-titration on systolic blood pressure in hypertensive patients at high risk of cardiovascular disease：the TASMIN-SR randomized clinical trial[J]. JAMA，2014，312（8）：799-808.
[14] MCMANUS R J，LITTLE P，STUART B，et al. Home and online management and evaluation of blood pressure（HOME BP）using a digital intervention in poorly controlled hypertension：randomised controlled trial[J/OL]. BMJ，2021，372：m4858[2024-11-22]. https://doi.org/10.1136/bmj.m4858.
[15] PERSELL S D，PEPRAH Y A，LIPISZKO D，et al. Effect of home blood pressure monitoring via a smartphone hypertension coaching application or tracking application on adults with uncontrolled hypertension：a randomized clinical trial[J/OL]. JAMA Netw Open，2020，3（3）：e200255[2024-11-22]. https://doi.org/10.1001/jamanetworkopen.2020.0255.
[16] ZHANG Y，TAO Y，ZHONG Y，et al. Feedback based on health advice via tracing bracelet and smartphone in the management of blood pressure among hypertensive patients：a community-based RCT trial in Chongqing，China[J/OL]. Medicine（Baltimore），2022，101（28）：e29346[2024-11-22]. https://doi.org/10.1097/MD.0000000000029346.
[17] 中华医学会糖尿病学分会，国家基层糖尿病防治管理办公室. 国家基层糖尿病防治管理手册（2022）[J]. 中华内科杂志，2022，61（7）：717-748.
Chinese Diabetes Society，National Office for Primary Diabetes Care. National handbook for the prevention and control of diabetes in primary care（2022）[J]. Chin J Intern Med，2022，61（7）：717-748.
[18] SUN H，SAEEDI P，KARURANGA S，et al. IDF diabetes atlas：global，regional and country-level diabetes prevalence estimates for 2021 and projections for 2045[J/OL]. Diabetes Res Clin Pract，2022，183：109119[2024-11-22]. https://doi.org/10.1016/j.diabres.2021.109119.
[19] XIAO J Y，LIU Y，SU L，et al. Microfluidic chip-based wearable colorimetric sensor for simple and facile detection of sweat glucose[J]. Anal Chem，2019，91（23）：14803-14807.
[20] ZHAO J Q，LIN Y J，WU J B，et al. A fully integrated and self-powered smartwatch for continuous sweat glucose monitoring[J]. ACS Sens，2019，4（7）：1925-1933.
[21] TOI P T，TRUNG T Q，DANG T M L，et al. Highly electrocatalytic，durable，and stretchable nanohybrid fiber for on-body sweat glucose detection[J]. ACS Appl Mater Interfaces，2019，11（11）：10707-10717.
[22] GAO W，BROOKS G A，KLONOFF D C. Wearable physiological systems and technologies for metabolic monitoring[J]. J Appl Physiol（1985），2018，124（3）：548-556.
[23] ARAKAWA T，TOMOTO K，NITTA H，et al. A wearable cellulose acetate-coated mouthguard biosensor for in vivo salivary glucose measurement[J]. Anal Chem，2020，92（18）：12201-12207.
[24] SEPAH S C，JIANG L H，ELLIS R J，et al. Engagement and outcomes in a digital diabetes prevention program：3-year update[J/OL]. BMJ Open Diabetes Res Care，2017，5（1）：e000422[2024-11-22]. https://doi.org/10.1136/bmjdrc-2017-000422.
[25] CHAWLA R，JAGGI S，GUPTA A，et al. Clinical utility of a digital therapeutic intervention in Indian patients with type 2 diabetes mellitus：12-week prospective single-arm intervention study[J/OL]. JMIR Diabetes，2022，7（4）：e41401[2024-11-22]. https://doi.org/10.2196/41401.
[26] AJJAN R A，ABOUGILA K，BELLARY S，et al. Sensor and software use for the glycaemic management of insulin-treated type 1 and type 2 diabetes patients[J]. Diab Vasc Dis Res，2016，13（3）：211-219.
[27] TIERNEY M J，TAMADA J A，POTTS R O，et al. Clinical evaluation of the GlucoWatch® biographer：a continual，non-invasive glucose monitor for patients with diabetes[J]. Biosens Bioelectron，2001，16（9/10/11/12）：621-629.
[28] RENARD E，FARRET A，KROPFF J，et al. Day-and-night closed-loop glucose control in patients with type 1 diabetes under free-living conditions：results of a single-arm 1-month experience compared with a previously reported feasibility study of evening and night at home[J]. Diabetes Care，2016，39（7）：1151-1160.
[29] 潘锋. 数字医学是县域慢病防控与健康管理发展新趋势[J]. 中国医药导报，2023，20（22）：1-3.
PAN F. Digital medicine is a new trend in the chronic disease prevention and management in the county areas[J]. China Medical Herald，2023，20（22）：1-3.
[30] SVERDLOV O，VAN D J，HANNESDOTTIR K，et al. Digital therapeutics：an integral component of digital innovation in drug development[J]. Clin Pharmacol Ther，2018，104（1）：72-80.
[31] KIM J，CAMPBELL A S，DE ÁVILA B E，et al. Wearable biosensors for healthcare monitoring[J]. Nat Biotechnol，2019，37（4）：389-406.
[32] SENYUREK V Y，IMTIAZ M H，BELAARE P，et al. Smoking detection based on regularity analysis of hand to mouth gestures[J/OL]. Biomed Signal Process Control，2019，51：106-112[2024-11-22]. https://doi.org/10.1016/j.bspc.2019.01.026.
[33] LOPEZ M P，TIFFANY S，PATIL Y，et al. Monitoring of cigarette smoking using wearable sensors and support vector machines[J]. IEEE Trans Biomed Eng，2013，60（7）：1867-1872.
[34] MASAKI K，TATENO H，KAMEYAMA N，et al. Impact of a novel smartphone App（CureApp Smoking Cessation）on nicotine dependence：prospective single-arm interventional pilot study[J/OL]. JMIR Mhealth Uhealth，2019，7（2）：e12694[2024-11-22]. https://doi.org/10.2196/12694.
[35] RAHEJA H，NAMANA V，CHOPRA K，et al. Electrocardiogram changes with acute alcohol intoxication：a systematic review[J/OL]. Open Cardiovasc Med J，2018，12：1-6[2024-11-22]. https://doi.org/10.2174/1874192401812010001.
[36] BENDER M S，COOPER B A，FLOWERS E，et al. Filipinos fit and trim—a feasible and efficacious DPP-based intervention trial[J/OL]. Contemp Clin Trials Commun，2018，12：76-84[2024-11-22]. https://doi.org/10.1016/j.conctc.2018.09.004.
[37] FINE J，BRANAN K L，RODRIGUEZ A J，et al. Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring[J/OL]. Biosensors（Basel），2021，11（4）：126[2024-11-22]. https://doi.org/10.3390/bios11040126.
[38] KUEHN B M. Telemedicine helps cardiologists extend their reach[J]. Circulation，2016，134（16）：1189-1191.
[39] 刘裕文，李庆印. 数字技术在心脏康复患者中的应用进展[J]. 中华护理杂志，2020，55（11）：1728-1732.
LIU Y W，LI Q Y. Application progress of digital technology in patients with cardiac rehabilitation[J]. Chin J Nurs，2020，55（11）：1728-1732.
[40] KENNEL P J，ROSENBLUM H，AXSOM K M，et al. Remote cardiac monitoring in patients with heart failure：a review[J]. JAMA Cardiol，2022，7（5）：556-564.
[41] REDLINE S，YENOKYAN G，GOTTLIEDB D J，et al. Obstructive sleep apnea-hypopnea and incident stroke：the sleep heart health study[J]. Am J Respir Crit Care Med，2010，182（2）：269-277.
[42] 赵智玲，郭兮恒. 智能动态血氧仪诊断睡眠呼吸暂停低通气综合征与多导睡眠图监测的一致性研究[J]. 国际呼吸杂志，2016，36（23）：1790-1795.
ZHAO Z L，GUO X H. Correlation of cloud platform wearable medical device and polysomnograghy in diagnozing sleep apnea hypopnea syndrome[J]. Int J Respir，2016，36（23）：1790-1795.
[43] SATEIA M J. International classification of sleep disorders-third edition：highlights and modifications[J]. Chest，2014，146（5）：1387-1394.
[44] MANONI A，LORETI F，RADICIONI V，et al. A new wearable system for home sleep apnea testing，screening，and classification[J/OL]. Sensors（Basel），2020，20（24）：7014[2024-11-22]. https://doi.org/10.3390/s20247014.