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基于脑电的脑机接口的正念冥想应用在心房颤动射频导管消融中的有效性: 初步随机对照试验。

Effectiveness of a Mindfulness Meditation App Based on an Electroencephalography-Based Brain-Computer Interface in Radiofrequency Catheter Ablation for Patients With Atrial Fibrillation: Pilot Randomized Controlled Trial.

机构信息

Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

School of Nursing, Nanjing Medical University, Nanjing, China.

出版信息

JMIR Mhealth Uhealth. 2023 May 3;11:e44855. doi: 10.2196/44855.

Abstract

BACKGROUND

Radiofrequency catheter ablation (RFCA) for patients with atrial fibrillation (AF) can generate considerable physical and psychological discomfort under conscious sedation. App-based mindfulness meditation combined with an electroencephalography (EEG)-based brain-computer interface (BCI) shows promise as effective and accessible adjuncts in medical practice.

OBJECTIVE

This study aimed to investigate the effectiveness of a BCI-based mindfulness meditation app in improving the experience of patients with AF during RFCA.

METHODS

This single-center pilot randomized controlled trial involved 84 eligible patients with AF scheduled for RFCA, who were randomized 1:1 to the intervention and control groups. Both groups received a standardized RFCA procedure and a conscious sedative regimen. Patients in the control group were administered conventional care, while those in the intervention group received BCI-based app-delivered mindfulness meditation from a research nurse. The primary outcomes were the changes in the numeric rating scale, State Anxiety Inventory, and Brief Fatigue Inventory scores. Secondary outcomes were the differences in hemodynamic parameters (heart rate, blood pressure, and peripheral oxygen saturation), adverse events, patient-reported pain, and the doses of sedative drugs used in ablation.

RESULTS

BCI-based app-delivered mindfulness meditation, compared to conventional care, resulted in a significantly lower mean numeric rating scale (mean 4.6, SD 1.7 [app-based mindfulness meditation] vs mean 5.7, SD 2.1 [conventional care]; P=.008), State Anxiety Inventory (mean 36.7, SD 5.5 vs mean 42.3, SD 7.2; P<.001), and Brief Fatigue Inventory (mean 3.4, SD 2.3 vs mean 4.7, SD 2.2; P=.01) scores. No significant differences were observed in hemodynamic parameters or the amounts of parecoxib and dexmedetomidine used in RFCA between the 2 groups. The intervention group exhibited a significant decrease in fentanyl use compared to the control group, with a mean dose of 3.96 (SD 1.37) mcg/kg versus 4.85 (SD 1.25) mcg/kg in the control group (P=.003).The incidence of adverse events was lower in the intervention group (5/40) than in the control group (10/40), though this difference was not significant (P=.15).

CONCLUSIONS

BCI-based app-delivered mindfulness meditation effectively relieved physical and psychological discomfort and may reduce the doses of sedative medication used in RFCA for patients with AF.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05306015; https://clinicaltrials.gov/ct2/show/NCT05306015.

摘要

背景

房颤(AF)患者接受射频导管消融(RFCA)治疗时,在镇静状态下可能会产生相当大的身体和心理不适。基于应用程序的正念冥想结合基于脑电图(EEG)的脑机接口(BCI)作为有效的辅助手段,在医学实践中具有应用前景。

目的

本研究旨在探讨基于 BCI 的正念冥想应用程序在改善 AF 患者 RFCA 期间体验的有效性。

方法

这是一项单中心前瞻性随机对照试验,共纳入 84 名符合条件的拟行 RFCA 的 AF 患者,按照 1:1 的比例随机分为干预组和对照组。两组均接受标准 RFCA 程序和镇静药物治疗。对照组患者接受常规护理,而干预组患者则由研究护士提供基于 BCI 的应用程序正念冥想。主要结局指标为数字评分量表、状态焦虑量表和简要疲劳量表评分的变化。次要结局指标为血流动力学参数(心率、血压和外周血氧饱和度)、不良事件、患者报告的疼痛和消融过程中镇静药物剂量的差异。

结果

与常规护理相比,基于 BCI 的应用程序正念冥想可显著降低平均数字评分量表(均值 4.6,标准差 1.7[基于 BCI 的正念冥想] vs 均值 5.7,标准差 2.1[常规护理];P=0.008)、状态焦虑量表(均值 36.7,标准差 5.5 vs 均值 42.3,标准差 7.2;P<0.001)和简要疲劳量表(均值 3.4,标准差 2.3 vs 均值 4.7,标准差 2.2;P=0.01)评分。两组间血流动力学参数或 RFCA 中帕瑞昔布和右美托咪定的使用量无显著差异。与对照组相比,干预组芬太尼的使用量显著减少,平均剂量为 3.96(1.37)mcg/kg,而对照组为 4.85(1.25)mcg/kg(P=0.003)。干预组不良事件发生率(5/40)低于对照组(10/40),但差异无统计学意义(P=0.15)。

结论

基于 BCI 的应用程序正念冥想可有效缓解身体和心理不适,并可能减少 AF 患者 RFCA 中镇静药物的剂量。

试验注册

ClinicalTrials.gov NCT05306015;https://clinicaltrials.gov/ct2/show/NCT05306015.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75a5/10193217/b9f6d049a1f1/mhealth_v11i1e44855_fig1.jpg

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