PDF(Pubmed)
Abstract：
OBJECTIVE: We tested a previously developed clinical prediction tool-a nomogram consisting of four patient measures (lower patient-expected benefit, lower patient-reported knee function, greater knee varus angle and severe medial knee radiological degeneration) that were related to poor response to non-surgical management of knee osteoarthritis. This study sought to prospectively evaluate the predictive validity of this nomogram to identify patients most likely to respond poorly to non-surgical management of knee osteoarthritis.
METHODS: Multisite prospective longitudinal study.
METHODS: Advanced practice physiotherapist-led multidisciplinary service across six tertiary hospitals.
METHODS: Participants with knee osteoarthritis deemed appropriate for trial of non-surgical management following an initial assessment from an advanced practice physiotherapist were eligible for inclusion.
METHODS: Baseline clinical nomogram scores were collected before a trial of individualised non-surgical management commenced.
METHODS: Clinical outcome (Global Rating of Change) was collected 6 months following commencement of non-surgical management and dichotomised to responder (a little better to a very great deal better) or poor responder (almost the same to a very great deal worse). Clinical nomogram accuracy was evaluated from receiver operating characteristics curve analysis and area under the curve, and sensitivity/specificity and positive/negative likelihood ratios were calculated.
RESULTS: A total of 242 participants enrolled. Follow-up scores were obtained from 210 participants (87% response rate). The clinical nomogram demonstrated an area under the curve of 0.70 (p<0.001), with greatest combined sensitivity 0.65 and specificity 0.64. The positive likelihood ratio was 1.81 (95% CI 1.32 to 2.36) and negative likelihood ratio 0.55 (95% CI 0.41 to 0.75).
CONCLUSIONS: The knee osteoarthritis clinical nomogram prediction tool may have capacity to identify patients at risk of poor response to non-surgical management. Further work is required to determine the implications for service delivery, feasibility and impact of implementing the nomogram in clinical practice.
METHODS: Multisite prospective longitudinal study.
METHODS: Advanced practice physiotherapist-led multidisciplinary service across six tertiary hospitals.
METHODS: Participants with knee osteoarthritis deemed appropriate for trial of non-surgical management following an initial assessment from an advanced practice physiotherapist were eligible for inclusion.
METHODS: Baseline clinical nomogram scores were collected before a trial of individualised non-surgical management commenced.
METHODS: Clinical outcome (Global Rating of Change) was collected 6 months following commencement of non-surgical management and dichotomised to responder (a little better to a very great deal better) or poor responder (almost the same to a very great deal worse). Clinical nomogram accuracy was evaluated from receiver operating characteristics curve analysis and area under the curve, and sensitivity/specificity and positive/negative likelihood ratios were calculated.
RESULTS: A total of 242 participants enrolled. Follow-up scores were obtained from 210 participants (87% response rate). The clinical nomogram demonstrated an area under the curve of 0.70 (p<0.001), with greatest combined sensitivity 0.65 and specificity 0.64. The positive likelihood ratio was 1.81 (95% CI 1.32 to 2.36) and negative likelihood ratio 0.55 (95% CI 0.41 to 0.75).
CONCLUSIONS: The knee osteoarthritis clinical nomogram prediction tool may have capacity to identify patients at risk of poor response to non-surgical management. Further work is required to determine the implications for service delivery, feasibility and impact of implementing the nomogram in clinical practice.
摘要：
目的：我们测试了先前开发的临床预测工具-由四个患者测量值组成的列线图（较低的患者预期获益，患者报告的膝关节功能较低，较大的膝关节内翻角度和严重的膝关节内侧放射学变性）与对膝关节骨关节炎的非手术治疗反应不佳有关。这项研究旨在前瞻性评估该列线图的预测有效性，以确定最有可能对膝关节骨关节炎的非手术治疗反应不佳的患者。
方法：多站点前瞻性纵向研究。
方法：高级实践物理治疗师主导的跨六家三级医院的多学科服务。
方法：经高级实践物理治疗师初步评估后认为适合非手术治疗试验的膝骨关节炎参与者有资格入选。
方法：在个体化非手术治疗试验开始前收集基线临床列线图评分。
方法：在非手术治疗开始后6个月收集临床结果（总体变化评级），并将其分为应答者（稍好到非常好）或应答不良（几乎相同到非常差）。通过受试者工作特征曲线分析和曲线下面积评估临床列线图的准确性，计算敏感性/特异性和阳性/阴性似然比。
结果：共有242名参与者登记。从210名参与者获得随访评分（87％的反应率）。临床列线图显示曲线下面积为0.70（p<0.001），最大的联合灵敏度为0.65，特异性为0.64。阳性似然比为1.81（95％CI1.32至2.36），阴性似然比为0.55（95％CI0.41至0.75）。
结论：膝骨性关节炎临床列线图预测工具可能有能力识别对非手术治疗反应不良的患者。需要进一步的工作来确定对服务交付的影响，在临床实践中实施列线图的可行性和影响。
方法：多站点前瞻性纵向研究。
方法：高级实践物理治疗师主导的跨六家三级医院的多学科服务。
方法：经高级实践物理治疗师初步评估后认为适合非手术治疗试验的膝骨关节炎参与者有资格入选。
方法：在个体化非手术治疗试验开始前收集基线临床列线图评分。
方法：在非手术治疗开始后6个月收集临床结果（总体变化评级），并将其分为应答者（稍好到非常好）或应答不良（几乎相同到非常差）。通过受试者工作特征曲线分析和曲线下面积评估临床列线图的准确性，计算敏感性/特异性和阳性/阴性似然比。
结果：共有242名参与者登记。从210名参与者获得随访评分（87％的反应率）。临床列线图显示曲线下面积为0.70（p<0.001），最大的联合灵敏度为0.65，特异性为0.64。阳性似然比为1.81（95％CI1.32至2.36），阴性似然比为0.55（95％CI0.41至0.75）。
结论：膝骨性关节炎临床列线图预测工具可能有能力识别对非手术治疗反应不良的患者。需要进一步的工作来确定对服务交付的影响，在临床实践中实施列线图的可行性和影响。
