Demographic Influences on the Relationship Between Fatigue and Quality of Life in Parkinson's Disease

Mantri, Sneha; Chahine, Lana M.; Nabieva, Karina; Feldman, Robert; Althouse, Andrew D.; Torsney, Benjamin M.; Albert, Steven M.; Kopil, Catherine; Marras, Connie

doi:10.1002/mdc3.13360

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…The effect of fatigue on HRQoL can be interpreted in line with previous research. It is already known that fatigue is an early symptom of PD [ 37 , 38 ] that has a negative impact on quality of life [ 39 , 40 , 41 ]. Our study confirmed that fatigue is of central importance to the PDQ-39 summary index, and particularly for the MOB subscale.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Nonmotor Symptoms on Health-Related Quality of Life in Parkinson’s Disease: A Network Analysis Approach

Heimrich

Schönenberg

Santos‐García

et al. 2023

JCM

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Nonmotor symptoms negatively affect health-related quality of life (HRQoL) in patients with Parkinson’s disease (PD). However, it is unknown which nonmotor symptoms are most commonly associated with HRQoL. Considering the complex interacting network of various nonmotor symptoms and HRQoL, this study aimed to reveal the network structure, explained HRQoL variance, and identify the nonmotor symptoms that primarily affect HRQoL. We included 689 patients with PD from the Cohort of Patients with Parkinson’s Disease in Spain (COPPADIS) study who were rated on the Nonmotor Symptoms Scale in Parkinson’s disease (NMSS) and the Parkinson´s Disease Questionnaire 39 (PDQ-39) at baseline. Network analyses were performed for the 30 items of the NMSS and both the PDQ-39 summary index and eight subscales. The nodewise predictability, edge weights, strength centrality, and bridge strength were determined. In PD, nonmotor symptoms are closely associated with the mobility, emotional well-being, cognition, and bodily discomfort subscales of the PDQ-39. The most influential nonmotor symptoms were found to be fatigue, feeling sad, hyperhidrosis, impaired concentration, and daytime sleepiness. Further research is needed to confirm whether influencing these non-motor symptoms can improve HRQoL.

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Section: Discussionmentioning

confidence: 99%

The Impact of Nonmotor Symptoms on Health-Related Quality of Life in Parkinson’s Disease: A Network Analysis Approach

Heimrich

Schönenberg

Santos‐García

et al. 2023

JCM

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“…Therefore, we further investigated the effects of the two factors on fatigue and found that depression was the mediating variable of the impact of anxiety on fatigue in the established mediation. Several studies have shown a negative relationship between fatigue and the ability to perform daily activities ( 36 , 37 ). Consistent with previous research, the results of this study provided additional evidence.…”

Section: Discussionmentioning

confidence: 99%

Predicting the fatigue in Parkinson's disease using inertial sensor gait data and clinical characteristics

Wang

Huang

et al. 2023

Front. Neurol.

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ObjectivesThe study aimed to analyze the clinical features and gait characteristics of patients with Parkinson's disease (PD) who also suffer from fatigue and to develop a model that can help identify fatigue states in the early stages of PD.MethodologyA total of 81 PD patients have been enrolled for the Parkinson's Fatigue Scale (PFS-16) assessment and divided into two groups: patients with or without fatigue. Neuropsychological assessments of the two groups, including motor and non-motor symptoms, were collected. The patient's gait characteristics were collected using a wearable inertial sensor device.ResultsPD patients who experienced fatigue had a more significant impairment of motor symptoms than those who did not, and the experience of fatigue became more pronounced as the disease progressed. Patients with fatigue had more significant mood disorders and sleep disturbances, which can lead to a poorer quality of life. PD patients with fatigue had shorter step lengths, lower velocity, and stride length and increased stride length variability. As for kinematic parameters, PD patients with fatigue had lower shank-forward swing max, trunk-max sagittal angular velocity, and lumbar-max coronal angular velocity than PD patients without fatigue. The binary logistic analysis found that Movement Disorder Society-Unified Parkinson's Disease Rating Scale-I (MDS-UPDRS-I) scores, Hamilton Depression Scale (HAMD) scores, and stride length variability independently predicted fatigue in PD patients. The area under the curve (AUC) of these selected factors in the receiver operating characteristic (ROC) analysis was 0.900. Moreover, HAMD might completely mediate the association between Hamilton Anxiety Scale (HAMA) scores and fatigue (indirect effect: β = 0.032, 95% confidence interval: 0.001–0.062), with a percentage of mediation of 55.46%.ConclusionCombining clinical characteristics and gait cycle parameters, including MDS-UPDRS-I scores, HAMD scores, and stride length variability, can identify PD patients with a high fatigue risk.

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“…Consequently, the commonly and persistently experienced symptom of “fatigue” has been identified. Furthermore, studies have consistently revealed that fatigue is one of the most common nonmotor symptoms of PD, with the potential to diminish QoL ( 5 ). The prevalence of depression among PD patients is reported to be 38%.…”

Section: Introductionmentioning

confidence: 99%

The impact of fatigue severity and depression level on the quality of life in individuals with Parkinson’s disease in Taiwan

Lin,

Chiou

et al. 2024

Front. Psychiatry

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BackgroundPatients diagnosed with Parkinson’s disease undergo alterations in physical, psychological, and social functionality, with the psychological domain being particularly predisposed to inducing fatigue and depressive symptoms. Understanding the alterations occurring within a patient’s body and mind and how these influence their overall quality of life is crucial.PurposeThis study sought to explore the predictive capacity of fatigue severity, the presence of depressive symptoms, and diverse demographic factors on the quality of life among individuals with Parkinson’s disease.MethodsA cross-sectional correlational study was conducted at a teaching hospital in southern Taiwan. The research utilized a questionnaire survey to interview 133 study participants, focusing on the Quality of Life Scale, Depression Scale, Fatigue Severity Scale, Social Support Scale, and demographic attributes.ResultsA total of 130 valid questionnaires were obtained. The results showed that Hoehn and Yahr stage, fatigue severity, and depression status could predict quality of life, explaining 51.1% of the total variance. These findings suggest that patients at advanced Hoehn and Yahr stages, experiencing more severe fatigue, and exhibiting higher levels of depression, tended to report a lower overall quality of life. Our findings suggest that, in addition to Hoehn and Yahr stage, the severity of fatigue and levels of depression significantly impact the quality of life in individuals with Parkinson’s disease.ConclusionNurses need to understand the “stressful life events” and the changes in appearance and physical function that patients with Parkinson’s disease face due to chronic degenerative diseases. Hence, apart from addressing patients’ physiological needs, healthcare professionals should also offer appropriate care for psychological issues, such as depressive symptoms. Encouraging patients to participate in “counseling groups” can further bolster their social support networks, enhancing their overall well-being and addressing comorbidities associated with chronic degenerative diseases.

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Demographic Influences on the Relationship Between Fatigue and Quality of Life in Parkinson's Disease

Cited by 5 publications

References 32 publications

The Impact of Nonmotor Symptoms on Health-Related Quality of Life in Parkinson’s Disease: A Network Analysis Approach

The Impact of Nonmotor Symptoms on Health-Related Quality of Life in Parkinson’s Disease: A Network Analysis Approach

Predicting the fatigue in Parkinson's disease using inertial sensor gait data and clinical characteristics

The impact of fatigue severity and depression level on the quality of life in individuals with Parkinson’s disease in Taiwan

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