Department of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa, USA.
Department of Anesthesia, University of Iowa, Iowa City, Iowa, USA.
Pain Med. 2021 Mar 18;22(3):533-547. doi: 10.1093/pm/pnaa440.
Define and contrast acute pain trajectories vs. the aggregate pain measurements, summarize appropriate linear and nonlinear statistical analyses for pain trajectories at the patient level, and present methods to classify individual pain trajectories. Clinical applications of acute pain trajectories are also discussed.
In 2016, an expert panel involving the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION), American Pain Society (APS), and American Academy of Pain Medicine (AAPM) established an initiative to create a pain taxonomy, named the ACTTION-APS-AAPM Pain Taxonomy (AAAPT), for the multidimensional classification of acute pain. The AAAPT panel commissioned the present report to provide further details on analysis of the individual acute pain trajectory as an important component of comprehensive pain assessment.
Linear mixed models and nonlinear models (e.g., regression splines and polynomial models) can be applied to analyze the acute pain trajectory. Alternatively, methods for classifying individual pain trajectories (e.g., using the 50% confidence interval of the random slope approach or using latent class analyses) can be applied in the clinical context to identify different trajectories of resolving pain (e.g., rapid reduction or slow reduction) or persisting pain. Each approach has advantages and disadvantages that may guide selection. Assessment of the acute pain trajectory may guide treatment and tailoring to anticipated symptom recovery. The acute pain trajectory can also serve as a treatment outcome measure, informing further management.
Application of trajectory approaches to acute pain assessments enables more comprehensive measurement of acute pain, which forms the cornerstone of accurate classification and treatment of pain.
定义和对比急性疼痛轨迹与总体疼痛测量,总结适合患者水平疼痛轨迹的线性和非线性统计分析方法,并介绍个体疼痛轨迹分类方法。还讨论了急性疼痛轨迹的临床应用。
2016 年,一个涉及镇痛、麻醉和成瘾临床试验转化、创新、机遇和网络(ACTION)、美国疼痛协会(APS)和美国疼痛医学学院(AAPM)的专家小组启动了一项创建疼痛分类法的倡议,命名为 ACTION-APS-AAPM 疼痛分类法(AAAPT),用于急性疼痛的多维分类。AAAPT 小组委托本报告进一步详细说明分析个体急性疼痛轨迹作为全面疼痛评估的重要组成部分。
线性混合模型和非线性模型(例如,回归样条和多项式模型)可用于分析急性疼痛轨迹。或者,可以在临床环境中应用用于分类个体疼痛轨迹的方法(例如,使用随机斜率方法的 50%置信区间或使用潜在类别分析)来识别疼痛缓解(例如,快速减少或缓慢减少)或持续疼痛的不同轨迹。每种方法都有其优点和缺点,这可能有助于指导选择。评估急性疼痛轨迹可以指导治疗和针对预期症状恢复进行调整。急性疼痛轨迹也可以作为治疗结果的衡量标准,为进一步的管理提供信息。
将轨迹方法应用于急性疼痛评估可以更全面地测量急性疼痛,这是准确分类和治疗疼痛的基础。