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帕金森氏病认知恶化评定的 mini-mental Parkinson 和 SCOPA-COG 量表的度量属性。

Metric properties of the mini-mental Parkinson and SCOPA-COG scales for rating cognitive deterioration in Parkinson's disease.

机构信息

Movement Disorder and Biostatistic Units, Neurological Service, Carlos Andrade Marín Hospital, Quito, Ecuador.

出版信息

Mov Disord. 2010 Nov 15;25(15):2555-62. doi: 10.1002/mds.23322.

Abstract

UNLABELLED

Parkinson's disease (PD) is a chronic neurodegenerative disorder that causes cognitive impairment and dementia in ∼30% of patients.

OBJECTIVE

Compare metric qualities of Mini-Mental Parkinson (MMP) and scales for outcomes in Parkinson's disease-cognition (SCOPA-COG) with respect to their relative reliability, validity and ability to predict symptoms (mobility, quality of life, social repercussions, and mood) in PD patients. Outpatients (n=123, 78 males/45 females) diagnosed with PD were included in the study. A multilevel (hierarchical) modeling analysis was performed along with tests of reliability and validity to ascertain which of the two models better predicts symptoms related to PD.

RESULTS

The MMP differed significantly between patients with Hoehn and Yahr (H&Y) stages 1, 2 or versus 4/5 (grouped together). The SCOPA-COG showed differences only between patients in H&Y stages 2 versus 4/5. Both scales were dependent on educational background and age. The SCOPA-COG had a higher coefficient of variation (0.303) than the MMP (0.184), indicating that it was the more discriminative of the two.

CONCLUSIONS

The SCOPA-COG has some advantages over the MMP, the most important being a greater discriminative ability. Multilevel hierarchical analysis clarified the necessity of stratifying the PD population according to educational background, years of illness, and H&Y stage when using these scales.

摘要

非标记

帕金森病(PD)是一种慢性神经退行性疾病,约 30%的患者会出现认知障碍和痴呆。

目的

比较 Mini-Mental Parkinson(MMP)和帕金森病认知量表(SCOPA-COG)在相对可靠性、有效性以及预测 PD 患者运动症状(移动性、生活质量、社会影响和情绪)方面的能力,以评估这两种量表的优劣。该研究纳入了 123 名门诊 PD 患者(78 名男性/45 名女性)。采用多层次(分层)建模分析,同时进行可靠性和有效性测试,以确定哪种模型能更好地预测与 PD 相关的症状。

结果

Hoehn 和 Yahr(H&Y)分期 1、2 或 4/5 患者的 MMP 差异显著(将 4/5 与 H&Y 分期 2 归为一组)。SCOPA-COG 仅在 H&Y 分期 2 与 4/5 患者之间存在差异。两种量表均依赖于教育背景和年龄。SCOPA-COG 的变异系数(0.303)高于 MMP(0.184),表明 SCOPA-COG 的区分度更高。

结论

与 MMP 相比,SCOPA-COG 具有一些优势,最重要的是其具有更高的区分能力。多层次分层分析阐明了在使用这些量表时,根据教育背景、患病年限和 H&Y 分期对 PD 人群进行分层的必要性。

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