Traits associated with central pain augmentation in the Knee Pain In the Community (KPIC) cohort
Traits associated with central pain augmentation in the Knee Pain In the Community (KPIC) cohort
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DOI：
10.1097/j.pain.0000000000001183
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发表时间：
2018-06-01
期刊：
影响因子：
7.4
通讯作者：
Walsh, David A.
中科院分区：
文献类型：
--
作者：
Akin-Akinyosoye, Kehinde;Frowd, Nadia;Walsh, David A.
本研究的目的是确定自我报告的相关性与膝关节疼痛的个人中央疼痛的增加。社区膝关节疼痛和相关健康（KPIC）基线调查中的一部分参与者（n = 420）进行了压痛检测阈值（PPT）评估。测量与中枢性疼痛机制相关的特定特征的项目是根据专家共识、表面效度、与原始主机问卷测量的基础结构的项目关联、充分的针对性和PPT相关性从调查中选择的。报告了人体模型上的疼痛分布。通过因子分析寻找“中枢性疼痛机制”因子。项目的关联，派生因素，并与PPT原始问卷进行了比较。测量焦虑、抑郁、灾难性、神经病样疼痛、疲劳、睡眠障碍、疼痛分布和认知影响特征的八个自我报告项目被确定为中枢疼痛机制的可能指标。压迫性疼痛检测阈值与代表每个特征的项目及其原始量表相关。疼痛分布分类为“腰部以下疼痛加上膝关节疼痛”与低PPT的相关性比疼痛分布的其他分类更强。一个单一的因素，解释为“中枢性疼痛机制”，确定了8个选定的项目，并解释PPT的变化（R-2 = 0.17）比任何原始规模（R-2 = 0.10-0.13）。总之，在复合自我报告工具中包括代表性项目可能有助于识别中央增强膝关节疼痛的人。
This study aimed to identify self-report correlates of central pain augmentation in individuals with knee pain. A subset of participants (n = 420) in the Knee Pain and related health In the Community (KPIC) baseline survey undertook pressure pain detection threshold (PPT) assessments. Items measuring specific traits related to central pain mechanisms were selected from the survey based on expert consensus, face validity, item association with underlying constructs measured by originating host questionnaires, adequate targeting, and PPT correlations. Pain distribution was reported on a body manikin. A "central pain mechanisms" factor was sought by factor analysis. Associations of items, the derived factor, and originating questionnaires with PPTs were compared. Eight self-report items measuring traits of anxiety, depression, catastrophizing, neuropathic-like pain, fatigue, sleep disturbance, pain distribution, and cognitive impact were identified as likely indices of central pain mechanisms. Pressure pain detection thresholds were associated with items representing each trait and with their originating scales. Pain distribution classified as "pain below the waist additional to knee pain" was more strongly associated with low PPT than were alternative classifications of pain distribution. A single factor, interpreted as "central pain mechanisms," was identified across the 8 selected items and explained variation in PPT (R-2 = 0.17) better than did any originating scale (R-2 = 0.10-0.13). In conclusion, including representative items within a composite self-report tool might help identify people with centrally augmented knee pain.