Mental Fatigue in Parkinson's Disease: Systematic Review and Evaluation of Self-Reported Fatigue Scales.

IF 2.1 4区 医学 Q3 CLINICAL NEUROLOGY Parkinson's Disease Pub Date : 2024-06-06 eCollection Date: 2024-01-01 DOI:10.1155/2024/9614163
Junle Chen, Yanjun Zhou, Hengyi Rao, Jianghong Liu
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Abstract

Fatigue is a common and debilitating symptom affecting a significant proportion of individuals with Parkinson's disease (PD), often overshadowing even motor symptoms in its impact on quality of life. The accurate definition and assessment of mental fatigue in PD is crucial for both clinical management and research, yet it remains a challenge due to the subjective nature of the symptom and the heterogeneity of assessment scales. This systematic review examined the existing measures of self-reported mental fatigue in PD by searching through PubMed, Embase, and Scopus databases using specific keywords from 2001 to 2024. Out of the 4182 articles found, 40 met the inclusion criteria, and 14 different scales were identified to measure self-reported fatigue in PD patients. However, most of these scales lack a consistent definition of fatigue, indicating a need for validated combinations of unidimensional and multidimensional scales to accurately assess mental fatigue in PD. The review found that it is best to use Fatigue Severity Inventory (FSI) and Multidimensional Fatigue Inventory (MdFI) to screen for severity of PD mental fatigue and Neuro-QoL Item Bank v1.0 (Neuro-QoL) to evaluate its impact on patients' lives. Furthermore, multidimensional scales Parkinson's Disease Questionnaire (PDQ) and Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F) are frequently coupled with Fatigue Severity Scale (FSS), Parkinson's Fatigue Scale (PFS), and/or Modified Fatigue Impact Scale (MFIS) due to their short length and holistic coverage of variables in patients' quality of life. Combining fatigue scales can be used for screening and scoring methods. The review also recommends validating fatigue scales translation and combining them with biomarkers to improve the accuracy and effectiveness of fatigue assessment in clinical practice. Future research should analyze correlations between fatigue scales, expand language types, and explore the link between fatigue scales and the pathophysiological basis of PD. Our findings underscore the need for a standardized approach to the measurement of fatigue in PD and set the stage for future research to consolidate assessment tools that can reliably guide treatment strategies and improve patient outcomes.

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帕金森病患者的精神疲劳:疲劳自评量表的系统回顾与评估》。
疲劳是一种常见的使人衰弱的症状,影响着相当一部分帕金森病(PD)患者,对生活质量的影响甚至常常超过运动症状。准确定义和评估帕金森病患者的精神疲劳对临床管理和研究都至关重要,但由于该症状的主观性和评估量表的异质性,这仍然是一项挑战。本系统性综述通过使用特定关键词在PubMed、Embase和Scopus数据库中检索2001年至2024年间的文献,研究了现有的帕金森病患者自我报告精神疲劳的测量方法。在找到的 4182 篇文章中,有 40 篇符合纳入标准,并确定了 14 种不同的量表来测量帕金森病患者的自我报告疲劳。然而,这些量表大多缺乏一致的疲劳定义,这表明需要将单维和多维量表进行有效组合,以准确评估帕金森病患者的精神疲劳。综述发现,最好使用疲劳严重程度量表(FSI)和多维疲劳量表(MdFI)来筛查帕金森病精神疲劳的严重程度,并使用神经量表项目库 v1.0(Neuro-QoL)来评估其对患者生活的影响。此外,多维量表帕金森病问卷(PDQ)和慢性疾病治疗功能评估-疲劳量表(FACIT-F)因其长度较短且全面覆盖患者生活质量的变量,经常与疲劳严重程度量表(FSS)、帕金森病疲劳量表(PFS)和/或改良疲劳影响量表(MFIS)结合使用。疲劳量表的组合可用于筛查和评分方法。综述还建议对疲劳量表进行翻译验证,并将其与生物标志物相结合,以提高疲劳评估在临床实践中的准确性和有效性。未来的研究应分析疲劳量表之间的相关性,扩大语言类型,并探索疲劳量表与帕金森病病理生理基础之间的联系。我们的研究结果表明,需要一种标准化的方法来测量帕金森病患者的疲劳程度,并为未来的研究奠定了基础,以便整合出能够可靠地指导治疗策略并改善患者预后的评估工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Parkinson's Disease
Parkinson's Disease CLINICAL NEUROLOGY-
CiteScore
5.80
自引率
3.10%
发文量
0
审稿时长
18 weeks
期刊介绍: Parkinson’s Disease is a peer-reviewed, Open Access journal that publishes original research articles, review articles, and clinical studies related to the epidemiology, etiology, pathogenesis, genetics, cellular, molecular and neurophysiology, as well as the diagnosis and treatment of Parkinson’s disease.
期刊最新文献
Effectiveness and Feasibility of Nonpharmacological Interventions for People With Parkinson's Disease and Cognitive Impairment on Patient-Centred Outcomes: Systematic Review and Meta-Analysis. Validation and Psychometric Properties of the Spanish Version of King's Parkinson's Disease Pain Scale. A Cognitive-Behavioral Model of Apathy in Parkinson's Disease. Possible Implications of Managing Alexithymia on Quality of Life in Parkinson's Disease: A Systematic Review. Implications of Convolutional Neural Network for Brain MRI Image Classification to Identify Alzheimer's Disease.
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