Collins Jemima T, Walsh David A, Gladman John R F, Patrascu Monica, Husebo Bettina S, Adam Esmee, Cowley Alison, Gordon Adam L, Ogliari Giulia, Smaling Hanneke, Achterberg Wilco
University of Nottingham, Nottingham, UK.
NIHR Nottingham Biomedical Research Centre, Nottingham, UK.
Drugs Aging. 2024 Mar;41(3):199-208. doi: 10.1007/s40266-024-01101-4. Epub 2024 Feb 24.
Pain and frailty are closely linked. Chronic pain is a risk factor for frailty, and frailty is a risk factor for pain. People living with frailty also commonly have cognitive impairment, which can make assessment of pain and monitoring of pain management even more difficult. Pain may be sub-optimally treated in people living with frailty, people living with cognitive impairment and those with both these factors. Reasons for sub-optimal treatment in these groups are pharmacological (increased drug side effects, drug-drug interactions, polypharmacy), non-pharmacological (erroneous beliefs about pain, ageism, bidirectional communication challenges), logistical (difficulty in accessing primary care practitioners and unaffordable cost of drugs), and, particularly in cognitive impairment, related to communication difficulties. Thorough assessment and characterisation of pain, related sensations, and their functional, emotional, and behavioural consequences ("phenotyping") may help to enhance the assessment of pain, particularly in people with frailty and cognitive impairment, as this may help to identify who is most likely to respond to certain types of treatment. This paper discusses the potential role of "digital phenotyping" in the assessment and management of pain in people with frailty. Digital phenotyping is concerned with observable characteristics in digital form, such as those obtained from sensing-capable devices, and may provide novel and more informative data than existing clinical approaches regarding how pain manifests and how treatment strategies affect it. The processing of extensive digital and usual data may require powerful algorithms, but processing these data could lead to a better understanding of who is most likely to benefit from specific and targeted treatments.
疼痛与身体虚弱密切相关。慢性疼痛是身体虚弱的一个风险因素，而身体虚弱也是疼痛的一个风险因素。身体虚弱的人通常还伴有认知障碍，这会使疼痛评估和疼痛管理监测变得更加困难。在身体虚弱的人、有认知障碍的人以及兼具这两种因素的人群中，疼痛可能未得到最佳治疗。这些人群治疗效果欠佳的原因包括药理学方面（药物副作用增加、药物相互作用、多种药物并用）、非药理学方面（对疼痛的错误认知、年龄歧视、双向沟通障碍）、后勤方面（难以接触到初级保健医生以及药物费用高昂），尤其是在认知障碍患者中，还与沟通困难有关。对疼痛、相关感觉及其功能、情感和行为后果进行全面评估和特征描述（“表型分析”）可能有助于加强疼痛评估，特别是在身体虚弱和有认知障碍的人群中，因为这可能有助于确定谁最有可能对某些类型的治疗产生反应。本文讨论了“数字表型分析”在身体虚弱人群疼痛评估和管理中的潜在作用。数字表型分析关注以数字形式呈现的可观察特征，例如从具备传感功能的设备获取的特征，并且与现有临床方法相比，可能会提供有关疼痛如何表现以及治疗策略如何影响疼痛的新颖且更具信息量的数据。处理大量数字数据和常规数据可能需要强大的算法，但处理这些数据可能会让人更好地理解谁最有可能从特定的靶向治疗中获益。
