Park Sang Jun, Yoon Duck Mi, Yoon Kyung Bong, Moon Ji Ae, Kim Shin Hyung
Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
PLoS One. 2016 Sep 16;11(9):e0163132. doi: 10.1371/journal.pone.0163132. eCollection 2016.
Chronic musculoskeletal pain is highly prevalent, disabling, and costly, and has many negative effects on quality of life. The aim of this study was to investigate factors associated with higher reported pain levels in patients with chronic musculoskeletal pain among demographic, clinical, and psychological factors, and to evaluate whether insomnia is independently associated with pain intensity in this population.
A total of 357 patients with chronic musculoskeletal pain (pain duration ≥ six months) satisfied the study inclusion criteria and were included in the analyses. Patient demographics, clinical, and psychological factors were evaluated with hierarchical multivariate logistic analysis to identify factors associated with severe pain (NRS [numeric rating scale] ≥ 7). Hierarchical linear regression analysis also performed to identify factors associated with pain intensity (0 to 10 NRS).
Multivariate logistic analyses revealed older age (OR [odds ratio] = 1.017, 95% CI [confidence interval] 1.001-1.032, P = 0.034), high anxiety level (OR = 1.162, 95% CI 1.020-1.324, P = 0.024), high pain catastrophizing (OR = 1.043, 95% CI 1.007-1.081, P = 0.018), and severe insomnia (OR = 1.112, 95% CI 1.057-1.170, P<0.001) were significantly associated with severe pain. Hierarchical linear regression analysis showed age (β = 0.106, P = 0.041), pain catastrophizing (β = 0.249, P<0.001), and insomnia (β = 0.286, P<0.001) were significantly associated with pain intensity. The variance in pain intensity explained by the final model was 32.2%.
Older age, severe insomnia, and high pain catastrophizing were significantly associated with higher reported pain levels. Insomnia was independently associated with pain intensity, even after controlling for various demographic and clinical factors. These factors should be considered when devising pain management strategies for this population.
慢性肌肉骨骼疼痛非常普遍，会导致残疾，花费高昂，并且对生活质量有许多负面影响。本研究的目的是调查在人口统计学、临床和心理因素中，与慢性肌肉骨骼疼痛患者报告的较高疼痛水平相关的因素，并评估失眠是否与该人群的疼痛强度独立相关。
共有357例慢性肌肉骨骼疼痛患者（疼痛持续时间≥6个月）符合研究纳入标准并纳入分析。通过分层多变量逻辑分析评估患者的人口统计学、临床和心理因素，以确定与重度疼痛（数字评定量表[NRS]≥7）相关的因素。还进行了分层线性回归分析，以确定与疼痛强度（0至10分NRS）相关的因素。
多变量逻辑分析显示，年龄较大（比值比[OR]=1.017，95%置信区间[CI]1.001-1.032，P=0.034）、焦虑水平高（OR=1.162，95%CI 1.020-1.324，P=0.024）、疼痛灾难化程度高（OR=1.043，95%CI 1.007-1.081，P=0.018）和严重失眠（OR=1.112，95%CI 1.057-1.170，P<0.001）与重度疼痛显著相关。分层线性回归分析显示，年龄（β=0.106，P=0.041）、疼痛灾难化程度（β=0.249，P<0.001）和失眠（β=0.286，P<0.001）与疼痛强度显著相关。最终模型解释的疼痛强度方差为32.2%。
年龄较大、严重失眠和疼痛灾难化程度高与报告的较高疼痛水平显著相关。即使在控制了各种人口统计学和临床因素后，失眠仍与疼痛强度独立相关。在为该人群制定疼痛管理策略时，应考虑这些因素。
