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在远程监测中应用预测 COPD 患者恶化的算法的临床实施:一项单盲随机对照试验的研究方案。

Clinical implementation of an algorithm for predicting exacerbations in patients with COPD in telemonitoring: a study protocol for a single-blinded randomized controlled trial.

机构信息

Department of Health Science and Technology, Aalborg University, Fredrik Bajers Vej 7C, 9220, Aalborg East, Denmark.

Department of Nursing, University College of Northern Denmark, Selma Lagerløfs Vej 2, 9220, Aalborg East, Denmark.

出版信息

Trials. 2022 Apr 26;23(1):356. doi: 10.1186/s13063-022-06292-y.

Abstract

BACKGROUND

Acute exacerbations have a significant impact on patients with COPD by accelerating the decline in lung function leading to decreased health-related quality of life and survival time. In telehealth, health care professionals exercise clinical judgment over a physical distance. Telehealth has been implemented as a way to monitor patients more closely in daily life with an intention to intervene earlier when physical measurements indicate that health deteriorates. Several studies call for research investigating the ability of telehealth to automatically flag risk of exacerbations by applying the physical measurements that are collected as part of the monitoring routines to support health care professionals. However, more research is needed to further develop, test, and validate prediction algorithms to ensure that these algorithms improve outcomes before they are widely implemented in practice.

METHOD

This trial tests a COPD prediction algorithm that is integrated into an existing telehealth system, which has been developed from the previous Danish large-scale trial, TeleCare North (NCT: 01984840). The COPD prediction algorithm aims to support clinical decisions by predicting the risk of exacerbations for patients with COPD based on selected physiological parameters. A prospective, parallel two-armed randomized controlled trial with approximately 200 participants with COPD will be conducted. The participants live in Aalborg municipality, which is located in the North Denmark Region. All participants are familiar with the telehealth system in advance. In addition to the participants' usual weekly monitored measurements, they are asked to measure their oxygen saturation two more times a week during the trial period. The primary outcome is the number of exacerbations defined as an acute hospitalization from baseline to follow-up. Secondary outcomes include changes in health-related quality of life measured by both the 12-Item Short Form Survey version 2 and EuroQol-5 Dimension Questionnaire as well as the incremental cost-effectiveness ratio.

DISCUSSION

This trial seeks to explore whether the COPD prediction algorithm has the potential to support early detection of exacerbations in a telehealth setting. The COPD prediction algorithm may initiate timely treatment, which may decrease the number of hospitalizations.

TRIAL REGISTRATION

NCT05218525 (pending at clinicaltrials.gov ) (date, month, year).

摘要

背景

急性加重对 COPD 患者有重大影响,会加速肺功能下降,导致健康相关生活质量和生存时间缩短。在远程医疗中,医疗保健专业人员在物理距离上进行临床判断。远程医疗已经被实施,作为一种更密切地监测患者日常生活的方式,以便在身体测量表明健康恶化时更早地进行干预。一些研究呼吁研究远程医疗通过应用作为监测常规一部分收集的身体测量值来自动标记加重风险的能力,以支持医疗保健专业人员。然而,需要更多的研究来进一步开发、测试和验证预测算法,以确保这些算法在广泛应用于实践之前提高结果。

方法

本试验测试了一种 COPD 预测算法,该算法集成到现有的远程医疗系统中,该系统是从以前的丹麦大规模试验 TeleCare North(NCT:01984840)中开发出来的。COPD 预测算法旨在通过基于选定的生理参数预测 COPD 患者的加重风险来支持临床决策。一项前瞻性、平行双臂随机对照试验,约有 200 名 COPD 患者参加。参与者居住在丹麦北部地区的奥尔堡市。所有参与者都提前熟悉远程医疗系统。除了参与者通常每周监测的测量值外,他们还被要求在试验期间每周额外测量两次氧饱和度。主要结局是从基线到随访的急性住院定义的加重次数。次要结局包括通过 12 项简短形式调查版本 2 和 EuroQol-5 维度问卷测量的健康相关生活质量变化,以及增量成本效益比。

讨论

本试验旨在探讨 COPD 预测算法是否有潜力在远程医疗环境中支持早期发现加重。COPD 预测算法可以启动及时治疗,从而减少住院次数。

试验注册

NCT05218525(在 clinicaltrials.gov 上待批)(日期、月份、年份)。

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