Clinical approach to nonmotor sensory fluctuations in Parkinson's disease

Bayülkem, Kemal; Lopez, Grisel

doi:10.1016/j.jns.2011.07.056

Cited by 30 publications

(25 citation statements)

References 37 publications

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“…In contrast to motor fluctuations, these non-motor fluctuations (NMF) are poorly researched. NMF have been described to be present in up to 100 % of patients with motor fluctuations and can be more troublesome and disabling than motor disturbances (Witjas et al 2002;Bayulkem and Lopez 2011). This study follows on from previously published results of the NonMotor Fluctuations in PD (NoMoFlu-PD) study which was designed as a multicenter cross-sectional study to assess NMF and correlate them to motor fluctuations and hr-QoL (Storch et al 2013).…”

Section: Introductionmentioning

confidence: 89%

Quantitative assessment of non-motor fluctuations in Parkinson’s disease using the Non-Motor Symptoms Scale (NMSS)

et al. 2015

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Data on frequency, severity and correlations of NMS with motor complications are only available for a limited number of NMS. The NMS Scale (NMSS) is a validated tool to assess a broad range of NMS, which has not been used in NMS fluctuations. We assessed fluctuations of a broad range of non-motor symptom (NMS) for a 1-month time period in fluctuating Parkinson's disease (PD) in a multicenter cross-sectional study using the NMSS assessing NMS in motor On (NMSSOn) and Off state (NMSSOff) combined with clinical NMS and motor function scoring in 100 fluctuating PD patients. ΔNMSSOn/Off was defined as the differences of NMSS scores between On and Off. Complete NMSS datasets were available from 73 patients (53 % men; age: 68.2 ± 9.7 years) with mean total NMSS score in On state of 41.5 ± 37.6 and in Off state of 75.6 ± 42.3 (P < 0.001). Scores were higher in Off compared to On state for all domains except for domain "perceptual problems/hallucinations" (P = 0.608). Clinimetric properties of the NMSS were similar to those reported previously for NMS assessments independent of motor oscillations. NMSSOn, NMSSOff and ΔNMSSOn/Off showed weak to moderate correlations with demographics, indicators of motor symptom severity as well as with other measures of NMS, depression and quality of life. Correlations of NMSS items/domains with independent measures of related constructs were weak to moderate. In conclusion, when assessed with the NMSS, a broad range of NMS fluctuate with motor oscillations, but these fluctuations do neither correlate with motor function nor with measures of disease progression.

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Section: Introductionmentioning

confidence: 89%

Quantitative assessment of non-motor fluctuations in Parkinson’s disease using the Non-Motor Symptoms Scale (NMSS)

et al. 2015

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“…However, balance impairment in PD is a late phenomenon and in fact, prominent balance impairment in the first few years suggests that PD is not the correct diagnosis. Non-motor symptoms can be categorized as autonomic, cognitive/psychiatric and sensory [18] and may include depression, dementia, hallucinations, rapid eye movement (REM), sleep behavior disorder (RMD), orthostatic hypotension, and constipation. Non-motor symptoms can also fluctuate, especially depression, pain, numbness, paresthesia, akathisia, and restless-legs syndrome.…”

Section: )mentioning

confidence: 99%

“…Non-motor symptoms can also fluctuate, especially depression, pain, numbness, paresthesia, akathisia, and restless-legs syndrome. Recognition of non-motor symptoms of Parkinson's disease is essential for appropriate management [18].…”

Section: )mentioning

confidence: 99%

Towards an Expert System for Accurate Diagnosis and Progress Monitoring of Parkinson’s Disease

Alexiou

Psiha

Vlamos

2014

Advances in Experimental Medicine and Biology

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While Parkinson's disease is a chronic and progressive movement disorder, no one can predict which symptoms will affect an individual patient. At the present time there is no cure for Parkinson's disease but instead a variety of alternative treatments provide relief from the symptoms. Due to these unpromising factors, we propose a new multi-scale ontology-based modeling technology for the accurate diagnosis of Parkinson's disease and its progress monitoring. The proposed model will be used to assess the status of the patient with PD corresponding treatments using a multilayer neural network. The proposed tool also aims to identify new associated physical and biological biomarkers from heterogeneous patients' data. The architecture of this expert system and its implementation in Protégé is presented in this paper.

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“…However, balance impairment in PD is a late phenomenon and in fact, prominent balance impairment in the first few years suggests that PD is not the correct diagnosis. Nonmotor symptoms can be categorized as autonomic, cognitive/psychiatric and sensory [14] and may include depression, dementia, hallucinations, rapid eye movement (REM), sleep behaviour disorder (RMD), orthostatic hypotension, and constipation. Nonmotor symptoms can also fluctuate, especially depression, pain, numbness, paresthesia/dysesthesia, akathisia and restless-legs syndrome.…”

Section: The General Structure Of the Proposed Modelmentioning

confidence: 99%

“…Nonmotor symptoms can also fluctuate, especially depression, pain, numbness, paresthesia/dysesthesia, akathisia and restless-legs syndrome. Recognition of nonmotor symptoms of Parkinson disease is essential for appropriate management [14]. 3.…”

Section: The General Structure Of the Proposed Modelmentioning

confidence: 99%

An Integrated Ontology-Based Model for the Early Diagnosis of Parkinson’s Disease

Alexiou

Psiha

Vlamos

2012

IFIP Advances in Information and Communication Technology

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Abstract. In our days there is no single test or biomarker that can predict whether a particular person will develop Parkinson Disease and a definitive diagnosis is only possible after death, with postmortem analysis. Recent discoveries have highlighted that defects in mitochondrial dynamics are associated with neurodegenerative disease. In this paper the general architecture of an integrated multi-scale ontology-based modeling technology for early diagnosis of PD and for progress monitoring is proposed. The proposed model will be used to identify physics and biology-based biomarkers of processes occurring at radically different scales, from cell to whole body.

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Clinical approach to nonmotor sensory fluctuations in Parkinson's disease

Cited by 30 publications

References 37 publications

Quantitative assessment of non-motor fluctuations in Parkinson’s disease using the Non-Motor Symptoms Scale (NMSS)

Quantitative assessment of non-motor fluctuations in Parkinson’s disease using the Non-Motor Symptoms Scale (NMSS)

Towards an Expert System for Accurate Diagnosis and Progress Monitoring of Parkinson’s Disease

An Integrated Ontology-Based Model for the Early Diagnosis of Parkinson’s Disease

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