School of Health Sciences, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK.
Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK.
Br J Sports Med. 2019 Jul;53(13):825-834. doi: 10.1136/bjsports-2018-099450. Epub 2019 Jan 9.
To (i) identify predictors of outcome for the physiotherapy management of shoulder pain and (ii) enable clinicians to subgroup people into risk groups for persistent shoulder pain and disability.
1030 people aged ≥18 years, referred to physiotherapy for the management of musculoskeletal shoulder pain were recruited. 810 provided data at 6 months for 4 outcomes: Shoulder Pain and Disability Index (SPADI) (total score, pain subscale, disability subscale) and Quick Disability of the Arm, Shoulder and Hand (QuickDASH). 34 potential prognostic factors were used in this analysis.
Four classification trees (prognostic pathways or decision trees) were created, one for each outcome. The most important predictor was baseline pain and/or disability: higher or lower baseline levels were associated with higher or lower levels at follow-up for all outcomes. One additional baseline factor split participants into four subgroups. For the SPADI trees, high pain self-efficacy reduced the likelihood of continued pain and disability. Notably, participants with low baseline pain but concomitant low pain self-efficacy had similar outcomes to patients with high baseline pain and high pain self-efficacy. Cut-off points for defining high and low pain self-efficacy differed according to baseline pain and disability. In the QuickDASH tree, the association between moderate baseline pain and disability with outcome was influenced by patient expectation: participants who expected to recover because of physiotherapy did better than those who expected no benefit.
Patient expectation and pain self-efficacy are associated with clinical outcome. These clinical elements should be included at the first assessment and a low pain self-efficacy response considered as a target for treatment intervention.
（i）确定物理治疗管理肩痛的结果预测因素，（ii）使临床医生能够将人群分为持续性肩痛和残疾的风险组。
招募了 1030 名年龄≥18 岁、因肌肉骨骼肩痛接受物理治疗的患者。810 人在 6 个月时提供了 4 个结局的数据：肩痛和残疾指数（SPADI）（总分、疼痛分量表、残疾分量表）和快速上肢、肩部和手部残疾问卷（QuickDASH）。本分析使用了 34 个潜在的预后因素。
创建了 4 个分类树（预后途径或决策树），每个结局一个。最重要的预测因素是基线疼痛和/或残疾：所有结局的基线水平较高或较低，与随访时的水平较高或较低相关。一个额外的基线因素将参与者分为四组。对于 SPADI 树，较高的疼痛自我效能降低了持续疼痛和残疾的可能性。值得注意的是，基线疼痛较低但同时疼痛自我效能较低的参与者的结局与基线疼痛较高但疼痛自我效能较高的患者相似。定义高和低疼痛自我效能的截止值根据基线疼痛和残疾而有所不同。在 QuickDASH 树中，中度基线疼痛和残疾与结局之间的关联受患者预期的影响：由于物理治疗而预期恢复的患者比预期无益处的患者表现更好。
患者的预期和疼痛自我效能与临床结局相关。这些临床因素应在首次评估时纳入，并将低疼痛自我效能反应视为治疗干预的目标。
