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慢性肾脏病患者风险因素监测及治疗依从性改善(Smit-CKD项目):初步观察性研究

Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study.

作者信息

Vilasi Antonio, Panuccio Vincenzo Antonio, Morante Salvatore, Villa Antonino, Versace Maria Carmela, Mezzatesta Sabrina, Mercuri Sergio, Inguanta Rosalinda, Aiello Giuseppe, Cutrupi Demetrio, Puglisi Rossella, Capria Salvatore, Li Vigni Maurizio, Tripepi Giovanni, Torino Claudia

机构信息

Institute of Clinical Physiology, National Research Council, Reggio Calabria, Italy.

Nephrology Unit, Grande Ospedale Metropolitano Bianchi Melacrino Morelli, Reggio Calabria, Italy.

出版信息

JMIR Bioinform Biotechnol. 2022 Nov 15;3(1):e36766. doi: 10.2196/36766.

Abstract

BACKGROUND

Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.

OBJECTIVE

With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.

METHODS

The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.

RESULTS

The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.

CONCLUSIONS

Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population.

摘要

背景

慢性肾脏病是一个重大的公共卫生问题,约13%的普通成年人口及30%的老年人受其影响。该疾病终末期患者的死亡风险和心血管事件风险几乎独一无二地高,治疗依从性降低是心血管发病和死亡的另一个风险因素。考虑到手机普及率的提高,一款移动应用程序可以教育患者自主监测心肾风险因素。

目的

鉴于此背景,我们开发了一个服务器与应用程序的集成系统,旨在改善对心血管和肾脏风险因素的自我监测以及治疗依从性。

方法

Smit-CKD服务器和Smit-CKD应用程序的软件基础设施采用标准的面向网络的开发方法进行开发,在有可用开源工具时优先选用。为使Smit-CKD应用程序适用于安卓和iOS系统,使用了允许从单一源代码开发多平台应用程序的平台。该集成系统在22名参与者的帮助下进行了实地测试。通过专门为本研究设计的问卷来测量用户满意度和治疗依从性;使用平台上的每日报告来测量应用程序的常规使用情况。

结果

Smit-CKD应用程序可监测心肾风险因素,如血压、体重和血糖。收集到的数据会实时传输给转诊的全科医生。此外,特殊提醒可提高药物治疗方案的依从性。通过Smit-CKD服务器,全科医生可以监测患者的临床状况及其治疗依从性。在测试阶段,73%(16/22)的受试者定期输入所有所需数据并发送关于药物摄入的反馈。使用6个月后,药物常规摄入量的百分比从64%(14/22)升至82%(18/22)。对评估问卷的分析表明,应用程序和服务器组件均得到用户的良好接受。

结论

我们的研究表明,一款用于自我监测可改变的心肾风险因素及治疗依从性的简单移动应用程序,慢性肾脏病患者对其耐受性良好。需要进一步研究以阐明使用该集成系统是否会对治疗依从性产生长期影响,以及风险因素的自我监测是否会改善该人群的临床结局。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fc/11135230/db678c10aa7b/bioinform_v3i1e36766_fig1.jpg

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