Xu Zekun, Laber Eric, Staicu Ana-Maria, Lascelles B Duncan X
Department of Statistics, North Carolina State University, Raleigh, NC, USA.
Comparative Pain Research and Education Center, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA.
Sci Rep. 2021 Apr 8;11(1):7737. doi: 10.1038/s41598-021-87304-w.
Osteoarthritis (OA) is a chronic condition often associated with pain, affecting approximately fourteen percent of the population, and increasing in prevalence. A globally aging population have made treating OA-associated pain as well as maintaining mobility and activity a public health priority. OA affects all mammals, and the use of spontaneous animal models is one promising approach for improving translational pain research and the development of effective treatment strategies. Accelerometers are a common tool for collecting high-frequency activity data on animals to study the effects of treatment on pain related activity patterns. There has recently been increasing interest in their use to understand treatment effects in human pain conditions. However, activity patterns vary widely across subjects; furthermore, the effects of treatment may manifest in higher or lower activity counts or in subtler ways like changes in the frequency of certain types of activities. We use a zero inflated Poisson hidden semi-Markov model to characterize activity patterns and subsequently derive estimators of the treatment effect in terms of changes in activity levels or frequency of activity type. We demonstrate the application of our model, and its advance over traditional analysis methods, using data from a naturally occurring feline OA-associated pain model.
骨关节炎（OA）是一种常伴有疼痛的慢性疾病，影响着约14%的人口，且患病率呈上升趋势。全球人口老龄化使得治疗OA相关疼痛以及维持活动能力和行动力成为公共卫生的优先事项。OA影响所有哺乳动物，使用自发动物模型是改善转化性疼痛研究和制定有效治疗策略的一种有前景的方法。加速度计是收集动物高频活动数据以研究治疗对疼痛相关活动模式影响的常用工具。最近，人们越来越关注用其来了解人类疼痛状况下的治疗效果。然而，不同个体的活动模式差异很大；此外，治疗效果可能表现为活动计数增加或减少，或者以更微妙的方式呈现，比如某些类型活动频率的变化。我们使用零膨胀泊松隐藏半马尔可夫模型来表征活动模式，并随后根据活动水平或活动类型频率的变化推导出治疗效果的估计值。我们使用来自自然发生的猫科动物OA相关疼痛模型的数据，展示了我们模型的应用及其相对于传统分析方法的优势。
