Bhatkar Viprali, Picard Rosalind, Staahl Camilla
Digital Health Independent Consultant, Arlington, MA, United States.
MIT Media Lab, Cambridge, MA, United States.
Front Pain Res (Lausanne). 2022 Mar 23;3:764128. doi: 10.3389/fpain.2022.764128. eCollection 2022.
BACKGROUND: Self-reported pain levels, while easily measured, are often not reliable for quantifying pain. More objective methods are needed that supplement self-report without adding undue burden or cost to a study. Methods that integrate multiple measures, such as combining self-report with physiology in a structured and specific-to-pain protocol may improve measures. METHOD: We propose and study a novel measure that combines the measured by an electronic visual-analog-scale (eVAS) with continuously-measured changes in electrodermal activity (EDA), a physiological measure quantifying sympathetic nervous system activity that is easily recorded with a skin-surface sensor. The new pain measure isolates and specifically quantifies three temporal regions of dynamic pain experience: I. Anticipation preceding the onset of a pain stimulus, II. Response rising to the level of peak pain, and III. Recovery from the peak pain level. We evaluate the measure across two pain models (cold pressor, capsaicin), and four types of treatments (none, A=pregabalin, B=oxycodone, C=placebo). Each of 24 patients made four visits within 8 weeks, for 96 visits total: A training visit (TV), followed by three visits double-blind presenting A, B, or C (randomized order). Within each visit, a participant experienced the cold pressor, followed by an hour of rest during which one of the four treatments was provided, followed by a repeat of the cold pressor, followed by capsaicin. RESULTS: The novel method successfully discriminates the pain reduction effects of the four treatments across both pain models, confirming maximal pain for no-treatment, mild pain reduction for placebo, and the most pain reduction with analgesics. The new measure maintains significant discrimination across the test conditions both within a single-day's visit (for relative pain relief within a visit) and across repeated visits spanning weeks, reducing different-day-physiology affects, and providing better discriminability than using self-reported eVAS. CONCLUSION: The new method combines the subjectively-identified time of peak pain with capturing continuous physiological data to quantify the sympathetic nervous system response during a dynamic pain experience. The method accurately discriminates, for both pain models, the reduction of pain with clinically effective analgesics.
背景:自我报告的疼痛程度虽然易于测量,但在量化疼痛时往往不可靠。需要更客观的方法来补充自我报告,同时又不给研究增加过多负担或成本。整合多种测量方法,比如将自我报告与生理学测量以一种结构化且针对疼痛的方案相结合,可能会改进测量效果。 方法:我们提出并研究了一种新的测量方法,该方法将电子视觉模拟量表(eVAS)测量的结果与持续测量的皮肤电活动(EDA)变化相结合,EDA是一种量化交感神经系统活动的生理学测量指标,可通过皮肤表面传感器轻松记录。这种新的疼痛测量方法分离并具体量化了动态疼痛体验的三个时间段:I. 疼痛刺激开始前的预期阶段;II. 上升至疼痛峰值水平的反应阶段;III. 从疼痛峰值水平恢复的阶段。我们在两种疼痛模型(冷加压、辣椒素)和四种治疗类型(无治疗、A = 普瑞巴林、B = 羟考酮、C = 安慰剂)中评估了该测量方法。24名患者每人在8周内进行了4次就诊,总共96次就诊:一次训练就诊(TV),随后是三次双盲就诊,分别呈现A、B或C(随机顺序)。在每次就诊期间,参与者先经历冷加压试验,然后休息一小时,在此期间提供四种治疗中的一种,接着重复冷加压试验,随后使用辣椒素。 结果:这种新方法成功区分了两种疼痛模型中四种治疗方法的疼痛减轻效果,证实无治疗时疼痛最大,安慰剂有轻度疼痛减轻,而镇痛药的疼痛减轻效果最显著。该新测量方法在单日就诊内(用于就诊期间的相对疼痛缓解)以及跨越数周的重复就诊中,在不同测试条件下都保持了显著的区分度,减少了不同日期生理学影响,并且比使用自我报告的eVAS具有更好的区分能力。 结论:这种新方法将主观确定的疼痛峰值时间与捕捉连续生理数据相结合,以量化动态疼痛体验期间的交感神经系统反应。该方法在两种疼痛模型中都能准确区分临床有效镇痛药对疼痛的减轻效果。
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