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Longitudinal Monitoring of Pain Associated Distress with the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) Tool: Predicting Reduction Pain Intensity and Disability
Archives of Physical Medicine and Rehabilitation ( IF 3.6 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.apmr.2020.05.025
Steven Z George 1 , Cai Li 2 , Sheng Luo 3 , Maggie E Horn 4 , Trevor A Lentz 1
Affiliation  

OBJECTIVE To investigate the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) tool for longitudinal monitoring of pain associated distress with the goal of improving prediction of 50% reduction in pain intensity and disability outcomes. DESIGN Cohort study with 12-month follow-up after initial care episode SETTING: Ambulatory care, participants seeking care from out-patient physical therapy clinics PARTICIPANTS: Participants were seeking care for primary complaint of neck, low back, knee or shoulder pain. This secondary analysis included 440 subjects (62.5% female; mean age 45.1± 17) at baseline with n=279 (63.4%) providing follow-up data at 12 months. INTERVENTIONS Not applicable MAIN OUTCOME MEASURES: 50% reduction (baseline to 12-month follow-up) in pain intensity and self-reported disability RESULTS: Trends for prediction accuracy were similar for all versions of the OSPRO-YF. For predicting 50% reduction in pain intensity, model fit met the statistical criterion for improvement (i.e., p < 0.05) with each additional time point added from baseline. Model discrimination improved statistically when the 6-month to 12-month change was added to the model (Area Under the Curve = 0.849, p = 0.003). For predicting 50% reduction in disability, there was no evidence of improvement in model fit or discrimination from baseline with the addition of 4-week, 6-month, or 12-month changes (p's > 0.05). CONCLUSIONS These results suggested that longitudinal monitoring improved prediction accuracy for reduction in pain intensity, but not for disability reduction. Differences in OSPRO-YF item sets (10 vs. 17 items) or scoring methods (simple summary score vs. yellow flag count) did not impact predictive accuracy for pain intensity, providing flexibility for implementing this tool in practice settings.

中文翻译:

使用最佳筛选预测转诊和结果黄旗 (OSPRO-YF) 工具对疼痛相关痛苦进行纵向监测:预测减轻疼痛强度和残疾

目的 研究用于纵向监测疼痛相关痛苦的预测转诊和结果黄旗 (OSPRO-YF) 工具的最佳筛选,目的是提高对疼痛强度和残疾结果降低 50% 的预测。设计 初始护理事件后 12 个月随访的队列研究 设置:门诊护理,从物理治疗门诊寻求护理的参与者 参与者:参与者正在寻求治疗颈部、腰部、膝盖或肩部疼痛的主诉。该次要分析包括基线时的 440 名受试者(62.5% 女性;平均年龄 45.1±17),n=279(63.4%)提供 12 个月的随访数据。干预 不适用 主要结局指标:疼痛强度和自我报告的残疾减少 50%(基线至 12 个月随访) 结果:所有版本的 OSPRO-YF 的预测准确性趋势都相似。为了预测疼痛强度降低 50%,模型拟合满足改善的统计标准(即 p < 0.05),每个额外的时间点从基线增加。当将 6 个月到 12 个月的变化添加到模型中时,模型区分在统计上有所改善(曲线下面积 = 0.849,p = 0.003)。为了预测残疾减少 50%,没有证据表明模型拟合或歧视与基线相比增加了 4 周、6 个月或 12 个月的变化(p > 0.05)。结论 这些结果表明,纵向监测提高了疼痛强度降低的预测准确性,但不能提高残疾程度的降低。OSPRO-YF 项目集的差异(10 对
更新日期:2020-06-01
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