Department of Clinical Medicine, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka.
Department of Public Health, University of Kelaniya, Ragama, Sri Lanka.
Scand J Rheumatol. 2021 May;50(3):198-205. doi: 10.1080/03009742.2020.1829035. Epub 2021 Jan 20.
: This study examined whether risk factors for knee osteoarthritis (KOA) pain such as age, gender, body mass index (BMI), baseline pain, and other putative risk factors for knee osteoarthritis pain flares (KOAF) (e.g. knee buckling, injury, mood/stress/social support scores, and footwear) could predict KOAF.: People with KOA and previous history of KOAF were selected from a 3 month web-based longitudinal study. KOAF was defined as an increase of ≥ 2 points on a numeric rating scale (compared with background pain) which resolved within 20 days. Predictors assessed at baseline were gender, age, duration of KOA, BMI, pain, knee injury (7 days before), knee buckling (2 days before), Lubben Social Support, Knee Injury and Osteoarthritis Outcome Score, Intermittent and Constant Osteoarthritis Pain score (ICOAP), Positive/Negative Affect Score, and footwear stability/heel height. Outcome was occurrence of any KOAF during the ensuing 30 days. The combined ability of the above variables to predict occurrence of any KOAF was evaluated by multiple logistic regression with a 10-fold cross-validation method to build and internally validate the model. Variables that assessed similar domains were eliminated using receiver operating characteristics curve assessment for best fit.: Complete data were available for 313 people (66.6% female, mean ± sd age 62.3 ± 8.2 years, BMI 29.7 ± 6.5 kg/m). Increasing age, years of osteoarthritis, BMI, background/worst levels of pain, knee injury, knee buckling, ICOAP, and footwear category/heel height significantly predicted the occurrence of KOAF during the following 30 days, with an area under the curve of 0.73 (95% confidence interval 0.67-0.80).Conclusion: A combination of risk factors assessed at baseline, including exposures with potential to vary, successfully predicts the KOAF in the ensuing 30 days.
这项研究旨在探讨膝关节骨关节炎（KOA）疼痛的风险因素（如年龄、性别、体重指数（BMI）、基线疼痛以及膝关节骨关节炎疼痛发作（KOAF）的其他潜在风险因素（如膝关节屈曲、损伤、情绪/压力/社会支持评分和鞋类）是否可以预测 KOAF。从一项为期 3 个月的基于网络的纵向研究中选择了患有 KOA 且有 KOAF 病史的患者。KOAF 定义为数字评分量表（与背景疼痛相比）增加≥2 分，在 20 天内缓解。基线评估的预测因素包括性别、年龄、KOA 持续时间、BMI、疼痛、膝关节损伤（7 天前）、膝关节屈曲（2 天前）、Lubben 社会支持、膝关节损伤和骨关节炎结局评分、间歇性和持续性骨关节炎疼痛评分（ICOAP）、正负情绪评分和鞋类稳定性/鞋跟高度。结果是在接下来的 30 天内发生任何 KOAF。通过 10 倍交叉验证方法的多变量逻辑回归评估上述变量对任何 KOAF 发生的综合预测能力，以建立和内部验证模型。使用受试者工作特征曲线评估消除评估相似域的变量，以获得最佳拟合。
共有 313 人（66.6%为女性，平均年龄±标准差为 62.3±8.2 岁，BMI 为 29.7±6.5kg/m2）完成了所有数据。年龄增加、OA 持续时间、BMI、背景/最差疼痛水平、膝关节损伤、膝关节屈曲、ICOAP 和鞋类类别/鞋跟高度显著预测了接下来 30 天内 KOAF 的发生，曲线下面积为 0.73（95%置信区间 0.67-0.80）。结论：基线评估的风险因素组合，包括有潜在变化的暴露因素，可成功预测接下来 30 天内的 KOAF。
