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利用上市后监测评估数字康复应用程序(Kaia应用程序)中与安全相关的事件:观察性研究。

Using Postmarket Surveillance to Assess Safety-Related Events in a Digital Rehabilitation App (Kaia App): Observational Study.

作者信息

Jain Deeptee, Norman Kevin, Werner Zachary, Makovoz Bar, Baker Turner, Huber Stephan

机构信息

Department of Orthopaedic Surgery, Washington University in St. Louis, St. Louis, MO, United States.

Neoteric Consulting, New York, NY, United States.

出版信息

JMIR Hum Factors. 2021 Nov 9;8(4):e25453. doi: 10.2196/25453.

Abstract

BACKGROUND

Low back pain (LBP) affects nearly 4 out of 5 individuals during their lifetime and is the leading cause of disability globally. Digital therapeutics are emerging as effective treatment options for individuals experiencing LBP. Despite the growth of evidence demonstrating the benefits of these therapeutics in reducing LBP and improving functional outcomes, little data has been systematically collected on their safety profiles.

OBJECTIVE

This study aims to evaluate the safety profile of a multidisciplinary digital therapeutic for LBP, the Kaia App, by performing a comprehensive assessment of reported adverse events (AEs) by users as captured by a standardized process for postmarket surveillance.

METHODS

All users of a multidisciplinary digital app that includes physiotherapy, mindfulness techniques, and education for LBP (Kaia App) from 2018 to 2019 were included. Relevant messages sent by users via the app were collected according to a standard operating procedure regulating postmarket surveillance of the device. These messages were then analyzed to determine if they described an adverse event (AE). Messages describing an AE were then categorized based on the type of AE, its seriousness, and its relatedness to the app, and they were described by numerical counts. User demographics, including age and gender, and data on app use were collected and evaluated to determine if they were risk factors for increased AE reporting.

RESULTS

Of the 138,337 active users of the Kaia App, 125 (0.09%) reported at least one AE. Users reported 0.00014 AEs per active day on the app. The most common nonserious AE reported was increased pain. Other nonserious AEs reported included muscle issues, unpleasant sensations, headache, dizziness, and sleep disturbances. One serious AE, a surgery, was reported. Details of the event and its connection to the intervention were not obtainable, as the user did not provide more information when asked to do so; therefore, it was considered to be possibly related to the intervention. There was no relationship between gender and AE reporting (P>.99). Users aged 25 to 34 years had reduced odds (odds ratio [OR] 0.31, 95% CI 0.08-0.95; P=.03) of reporting AEs, while users aged 55 to 65 years (OR 2.53, 95% CI 1.36-4.84, P=.002) and ≥75 years (OR 4.36, 95% CI 1.07-13.26; P=.02) had increased odds. AEs were most frequently reported by users who had 0 to 99 active days on the app, and less frequently reported by users with more active days on the app.

CONCLUSIONS

This study on the Kaia App provides the first comprehensive assessment of reported AEs associated with real-world use of digital therapeutics for lower back pain. The overall rate of reported AEs was very low, but significant reporting bias is likely to be present. The AEs reported were generally consistent with those described for in-person therapies for LBP.

摘要

背景

下腰痛(LBP)在近五分之四的人一生中都会出现,是全球致残的主要原因。数字疗法正成为LBP患者有效的治疗选择。尽管越来越多的证据表明这些疗法在减轻LBP和改善功能结局方面有益,但关于其安全性的数据很少被系统收集。

目的

本研究旨在通过对上市后监测的标准化流程所捕获的用户报告的不良事件(AE)进行全面评估,来评估一种用于LBP的多学科数字疗法——Kaia应用程序的安全性。

方法

纳入2018年至2019年使用包含物理治疗、正念技巧和LBP教育的多学科数字应用程序(Kaia应用程序)的所有用户。根据规范该设备上市后监测的标准操作程序,收集用户通过应用程序发送的相关信息。然后对这些信息进行分析,以确定它们是否描述了不良事件(AE)。描述AE的信息随后根据AE的类型、严重程度及其与应用程序的相关性进行分类,并通过数字计数进行描述。收集并评估用户人口统计学信息,包括年龄和性别,以及应用程序使用数据,以确定它们是否是AE报告增加的风险因素。

结果

在Kaia应用程序的138337名活跃用户中,125人(0.09%)报告了至少一项AE。用户在应用程序上每活跃一天报告0.00014起AE。报告的最常见非严重AE是疼痛加剧。报告的其他非严重AE包括肌肉问题、不适感、头痛、头晕和睡眠障碍。报告了一起严重AE,即一次手术。由于用户在被要求提供更多信息时未提供,因此无法获得该事件的详细信息及其与干预措施的关联;因此,认为其可能与干预措施有关。性别与AE报告之间无关联(P>0.99)。25至34岁的用户报告AE的几率降低(优势比[OR]0.31,95%CI 0.08 - 0.95;P = 0.03),而55至65岁的用户(OR 2.53,95%CI 1.36 - 4.84,P = 0.002)和≥75岁的用户(OR 4.36,95%CI 1.07 - 13.26;P = 0.02)报告AE的几率增加。在应用程序上活跃天数为0至99天的用户报告AE最为频繁,而活跃天数更多的用户报告频率较低。

结论

这项关于Kaia应用程序的研究首次对与数字疗法在现实世界中用于治疗下腰痛相关的报告AE进行了全面评估。报告的AE总体发生率非常低,但可能存在显著的报告偏倚。报告的AE通常与LBP的面对面治疗中描述的AE一致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01a4/8663617/0672d88fbc0d/humanfactors_v8i4e25453_fig1.jpg

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