基于app的干预对骨关节炎人群的效果和安全性:随机对照试验的系统评价和荟萃分析。

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
He Zhang, Hongchi Wang, Cheng Zhang, Ruili Zhao, Qian Lv, Luyao Zhang, Haoran Zhang, Shiyan Yan
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引用次数: 0

摘要

背景:基于应用程序的干预措施在骨关节炎(OA)治疗中越来越受欢迎,但对治疗效果的潜在调节因子的研究尚缺乏。目的:本研究的目的是研究基于app的干预对OA患者的治疗效果、成本效益和安全性,并确定与更好的治疗结果相关的潜在因素。方法:检索PubMed、Web of Science、Embase和Cochrane图书馆从建立到2024年9月19日的随机对照试验,研究基于应用程序的OA患者干预措施的疗效或健康经济结果。采用修订后的Cochrane偏倚风险评估工具(ROB 2.0)对每项纳入研究的质量进行评估。主要结局指标是治疗前后疼痛强度的变化。次要结局包括功能、生活质量、不良事件和自我管理。如果I2为bb0 50%,则采用随机效应模型。除了基于OA类型、干预持续时间、偏倚风险、年龄和基于app的干预类型的预先计划亚组分析外,还对与人群、干预特征和研究设计特征相关的变量进行了探索性的事后亚组分析。结果:纳入14项研究,包括12项随机对照试验(RCTs)和2项卫生经济学研究。随机对照试验共涉及1410名参与者,平均年龄从54岁到67岁不等。与对照组相比,基于应用程序的干预导致疼痛减轻和身体功能改善(标准化平均差[SMD]=-0.36; 95% CI: -0.58至-0.14;结论:本研究表明,基于应用程序的干预对OA患者是安全有效的,特别是在资源有限的情况下,这可能是一种经济有效的选择。年龄是优化治疗效果的关键因素,特别是在考虑个人需求时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Effect and Safety of App-Based Interventions for Populations With Osteoarthritis: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

The Effect and Safety of App-Based Interventions for Populations With Osteoarthritis: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

The Effect and Safety of App-Based Interventions for Populations With Osteoarthritis: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

The Effect and Safety of App-Based Interventions for Populations With Osteoarthritis: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: Interventions based on apps are becoming increasingly popular for the treatment of osteoarthritis (OA), but research on the potential moderators of treatment efficacy is lacking.

Objective: The aim of this study was to examine the treatment efficacy, cost-effectiveness, and safety associated with app-based interventions for populations with OA and identify the potential factors associated with better treatment outcomes.

Methods: PubMed, Web of Science, Embase, and the Cochrane Library were searched from their inception to September 19, 2024, for randomized controlled trials on app-based interventions for patients with OA that report efficacy or health economic outcomes. The quality of each included study was assessed using the revised Cochrane Risk of Bias Assessment Tool (ROB 2.0). The primary outcome measure is the change in pain intensity before and after treatment. Secondary outcomes included function, quality of life, adverse events, and self-management. If I2 was >50%, a random-effects model was applied. In addition to preplanned subgroup analyses based on OA type, intervention duration, risk of bias, age, and type of app-based intervention, exploratory post hoc subgroup analyses were conducted on variables related to the population, intervention characteristics, and study design features.

Results: The review includes 14 studies, comprising 12 randomized controlled trials (RCTs) and 2 health economics studies. The RCTs involved a total of 1410 participants, whose mean age ranged from 54 to 67 years. Compared with controls, app-based interventions led to a reduction in pain and improvement in physical function (standardized mean difference [SMD]=-0.36; 95% CI: -0.58 to -0.14; P<.001; I2=72% and SMD 0.39; 95% CI 0.16 to 0.62; P<.001; I2=67%; respectively), but showed no significance for quality of life and adverse events (SMD 0.23; 95% CI -0.04 to 0.50; P=.10; I2=68% and odds ratio [OR]=1.33; 95% CI 0.84 to 2.12; P=.23; I2=7%; respectively). The cost of the intervention group was lower than that of the control group. Subgroup analysis revealed a significant difference between those aged 60 years and older and those younger than 60 years (SMD -0.29; 95% CI -0.51 to -0.06 and SMD -0.84; 95% CI -1.25 to -0.43). The study also reported a high level of satisfaction and compliance rate, with all scores of the System Usability Scale exceeding 70 points, and this score is considered acceptable.

Conclusions: This study showed that app-based interventions were safe and effective for patients with OA, which might provide a cost-effective option, especially in resource-limited settings. Age is a critical factor for optimizing treatment benefits, especially when considering individual needs.

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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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