Tavares Daniela Regina Brandão, Moça Trevisani Virginia Fernandes, Frazao Okazaki Jane Erika, Valéria de Andrade Santana Marcia, Pereira Nunes Pinto Ana Carolina, Tutiya Karina Kuraoka, Gazoni Fernanda Martins, Pinto Camila Bonin, Cristina Dos Santos Fania, Fregni Felipe
Department of Geriatrics and Gerontology, Federal University of São Paulo, São Paulo, SP, Brazil.
Department of Evidence-Based Medicine, Brazilian Cochrane Centre, Federal University of São Paulo, São Paulo, SP, Brazil.
Heliyon. 2020 Dec 19;6(12):e05723. doi: 10.1016/j.heliyon.2020.e05723. eCollection 2020 Dec.
Data on the precise mechanisms of the complex interactions of factors related to clinical impact of knee osteoarthritis (KOA) in the elderly population remain limited. To find predictors that explain pain intensity, physical function, and quality of life in elderly KOA subjects, we performed a cross-sectional analysis of the baseline data from a randomized trial. The trial included 104 subjects (aged ≥60) with KOA pain and dysfunctional endogenous pain-inhibitory system activity assessed by conditioned pain modulation (CPM). Three multiple linear regression models were performed to understand the independent predictors of Brief Pain Inventory (BPI), WOMAC function subscale (WOMACFunc), and SF-12 physical subscale (SF12-PCS). Model 1 showed that BPI pain score was predicted by low CPM response, high von-Frey light touch threshold, worse radiological severity as indexed by Kellgren-Lawrence grade (KL), high von-Frey punctate pain intensity and high levels of anxiety (adjusted R2 = 27.1%, F (6,95) = 7.27, P < 0.0001). In model 2, von-Frey light touch threshold, KL, depressive symptoms indexed by Beck Depression Inventory (BDI), level of sleepiness and pain pressure threshold were risk factors for SF12-PCS (adjusted R2 = 31.9%, F (5,96) = 10.5, P < 0.0001). Finally, model 3 showed that WOMACFunc was predicted by BDI, KL and BPI (adjusted R2 = 41%, F (3,98) = 24.42, P < 0.0001). Our data provides an interesting framework to understand the predictors of KOA pain in the elderly and highlights how its related outcomes are affected by disease-specific factors, somatosensory dysfunction and emotional factors.
关于老年人群中与膝关节骨关节炎(KOA)临床影响相关因素复杂相互作用的确切机制的数据仍然有限。为了找到能够解释老年KOA患者疼痛强度、身体功能和生活质量的预测因素,我们对一项随机试验的基线数据进行了横断面分析。该试验纳入了104名年龄≥60岁、患有KOA疼痛且内源性疼痛抑制系统功能通过条件性疼痛调制(CPM)评估为功能失调的受试者。进行了三个多元线性回归模型,以了解简明疼痛量表(BPI)、WOMAC功能子量表(WOMACFunc)和SF-12身体子量表(SF12-PCS)的独立预测因素。模型1显示,BPI疼痛评分由低CPM反应、高von-Frey轻触阈值、以Kellgren-Lawrence分级(KL)表示的更严重放射学严重程度、高von-Frey点状疼痛强度和高焦虑水平预测(调整后R2 = 27.1%,F(6,95)= 7.27,P < 0.0001)。在模型2中,von-Frey轻触阈值、KL、以贝克抑郁量表(BDI)表示的抑郁症状、嗜睡水平和疼痛压力阈值是SF12-PCS的危险因素(调整后R2 = 31.9%,F(5,96)= 10.5,P < 0.0001)。最后,模型3显示,WOMACFunc由BDI、KL和BPI预测(调整后R2 = 41%,F(3,98)= 24.42,P < 0.0001)。我们的数据为理解老年KOA疼痛的预测因素提供了一个有趣的框架,并突出了其相关结果如何受到疾病特异性因素、体感功能障碍和情绪因素的影响。