Reply to: "Predictors of motor complications in early Parkinson's disease".
Reply to: "Predictors of motor complications in early Parkinson's disease".
复制标题
回复：“早期帕金森病运动并发症的预测因素”。
DOI：
10.1002/mds.27904
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Baig F
中科院分区：
文献类型：
--
作者：
Baig F
我们感谢Santos-Lobato及其同事对我们的研究的兴趣，并花时间制作了一个研究左旋多巴诱导的运动障碍预测因子的汇总表。1-4我们还要补充的是，还有一项前瞻性的以社区为基础的纵向研究，该研究将左旋多巴等效日剂量和女性性别确定为发生运动障碍的独立风险因素。5他们的信强调了报告结果的可变性，并指出这是迄今为止针对这一主题的最大规模的前瞻性研究。与我们的研究一致，左旋多巴等效剂量和非运动症状负担在多项研究中被确定为独立的预测因子。然而，有些不一致之处可能反映了方法上的差异。例如，在一些研究中，女性性别被确定为可能的预测因素。我们在单变量模型中也发现了这一点，但在多变量模型中有所减弱。这可能反映了我们能够调整更广泛的协变量，而不是真正的不一致性3，5以及PPMI队列中年轻，受损程度较低的样本在抽样方法上的可能差异。2我们同意，患者教育和更频繁的患者评估将提高数据收集的精度，但临床医生评估使高频数据收集昂贵且繁重。可穿戴技术的使用可能会有所帮助;然而，在家庭环境中能够可靠地区分帕金森氏运动障碍和震颤的技术困难还有待克服。我们计划使用该队列开发一个风险计算器，但正在等待进一步的纵向数据收集，以允许更多的参与者发展运动波动，从而提高模型的有效性。
We thank Santos-Lobato and colleagues for their interest in our study and taking the time to produce a summary table of studies investigating predictors of levodopa-induced dyskinesias. 1-4 We would also add that there is a further prospective communitybased longitudinal study which identified L-dopa equivalent daily dose and female sex as independent risk factors for developing dyskinesias. 5Their letter highlights the variability in reported results, noting that this is the largest prospective study to date to address this topic. In agreement with our study, L-dopa equivalent dose and nonmotor symptom burden were identified as independent predictors in more than one study. However, some inconsistencies may reflect methodological differences. For example, female sex has been identified as a possible predictor in some studies. We also found this in our univariable model, but this was attenuated in the multivariable model. This may reflect that we were able to adjust for a wider breadth covariates rather than a true inconsistency3, 5 and possibly differences in sampling methodology with a younger, less impaired sample in the PPMI cohort. 2 We agree that patient education and more frequent patient assessments would improve the precision of data collection, but clinician evaluation make high-frequency data collection expensive and burdensome. The use of wearable technologies may help; however, technological difficulties in being able to reliably distinguish Parkinson’s dyskinesia from tremor in the home environment have yet to be overcome. We plan to develop a risk calculator using this cohort, but are waiting for further longitudinal data collection to allow more participants to develop motor fluctuations and thus improve the validity of the model.