Examination of Factors Associated With Fatigue in Individuals Diagnosed With Parkinson's Disease
NCT ID: NCT06230939
Last Updated: 2026-01-27
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
129 participants
OBSERVATIONAL
2023-11-05
2025-11-05
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Fatigue, Sleep and Quality of Life in Parkinson's Patients
NCT05687799
Central and Peripheral Fatigue in Individuals With Parkinson's Disease - Evaluation and Training
NCT01971528
Effect of Motor Function, Depression and Sleep Quality on Attention in Parkinson's Disease
NCT06283043
Establishing the Central and Peripheral Fatigue Indexes and VR Based Anti-fatigue Training Paradigm for Individuals With Parkinson Disease
NCT02017938
Managing Fatigue in People With Parkinson's Disease
NCT04267107
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
CASE_ONLY
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Parkinson's Disease Group
The study will be conducted in collaboration with Gazi University Faculty of Health Sciences and Nigde Omer Halisdemir University. The study data will be obtained from individuals diagnosed with PD admitted to the Neurology Outpatient Clinic of Nigde Omer Halisdemir University Training and Research Hospital. Necessary permissions were obtained from all institutions. All evaluations will be collected in a single meeting using the face-to-face interview method. It is calculated that 80% power will be reached with a margin of error of 0.05 when 84 individuals diagnosed with PD are included in the study.
Examination
Individual characteristics of the patients (gender, age, height, body weight, marital status, education level, dominant extremity, smoking and alcohol consumption habits, use and type of assistive device, how many years the assistive device has been used) and disease-related (year of diagnosis, disease duration Information (such as CV, family history, medications used, surgeries) will be questioned. HYE and UPDRS will be used for disease staging and grading. PFS-16 will be used to evaluate fatigue and MMSE will be used to evaluate sleep. In addition, "Timed Up and Go (TUG)" will be applied for lower extremity performance evaluation. All evaluations will be collected in a single meeting using the face-to-face interview method.
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Examination
Individual characteristics of the patients (gender, age, height, body weight, marital status, education level, dominant extremity, smoking and alcohol consumption habits, use and type of assistive device, how many years the assistive device has been used) and disease-related (year of diagnosis, disease duration Information (such as CV, family history, medications used, surgeries) will be questioned. HYE and UPDRS will be used for disease staging and grading. PFS-16 will be used to evaluate fatigue and MMSE will be used to evaluate sleep. In addition, "Timed Up and Go (TUG)" will be applied for lower extremity performance evaluation. All evaluations will be collected in a single meeting using the face-to-face interview method.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Being diagnosed with PD by a neurologist,
* Having stable medical treatment,
* Being able to stand independently for at least 60 seconds without any assistive device,
* Having received 18 points or more according to the MMSD evaluation.
Exclusion Criteria
* Having undergone a surgery that may affect lower extremity functions,
* Diabetes mellitus is a diagnosis of another neurological and rheumatic disease.
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Gazi University
OTHER
Nigde Omer Halisdemir University
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Asli Demirtaş
Lecturer
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
İlke KESER, Prof. Dr.
Role: STUDY_DIRECTOR
Gazi University
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Gazi University
Ankara, , Turkey (Türkiye)
Nigde Omer Halisdemir University
Niğde, , Turkey (Türkiye)
Countries
Review the countries where the study has at least one active or historical site.
References
Explore related publications, articles, or registry entries linked to this study.
Opara J, Malecki A, Malecka E, Socha T. Motor assessment in Parkinson;s disease. Ann Agric Environ Med. 2017 Sep 21;24(3):411-415. doi: 10.5604/12321966.1232774. Epub 2017 May 11.
Ascherio A, Schwarzschild MA. The epidemiology of Parkinson's disease: risk factors and prevention. Lancet Neurol. 2016 Nov;15(12):1257-1272. doi: 10.1016/S1474-4422(16)30230-7. Epub 2016 Oct 11.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
Gazi University-05.09.2023.3
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.