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SCIENTIFIC LITERATURE · MED

Parkinson Hastalığı ile Komorbid Hafif Depresyon Hastalarında Yaş ve Alt Hastalık Özelliklerinin Belirlenmesi: Retrospektif Bir Vaka Kontrol Çalışması.

Identification of Age and Underlying Disease Characteristics in Patients with Mild to Moderate Depression Comorbid with Parkinson's Disease: A Retrospective Case-control Study.

Makine çevirisi · Editoryal inceleme bekliyor

Actas Esp Psiquiatr · 2025-03-01

DOI: 10.62641/aep.v53i2.1702PMID: 40071373

Open accessresearch-article; Journal ArticleKaynağa git ↗

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BackgroundDepression is a widely recognized neuropsychiatric condition that often occurs as a comorbidity with various medical illnesses, including neurodegenerative disorders like Parkinson's disease (PD). This study aimed to identify the age of onset and underlying disease characteristics associated with patients exhibiting mild to moderate depression comorbid with PD.MethodsThis retrospective case-control study included 114 elderly patients (age ≥65 years) diagnosed with Parkinson's disease. The patients were divided into two groups: the non-depressed group (n = 65) and the mild to moderate depression group (n = 49). Patients' emotional and affective symptoms, cognitive function, and clinical characteristics were assessed using standardized scales. Statistical analyses, including chi-square tests, Wilcoxon rank-sum tests, and logistic regression analysis, were performed to evaluate associations and correlations between the variables of interest.ResultsOur findings revealed that patients in the mild to moderate depression group exhibited a significantly lower onset age of PD (52.33 ± 3.87 years) compared to the non-depressed group (59.27 ± 3.62 years, p ConclusionThe study highlights the complex interaction of age and underlying disease characteristics in patients with mild to moderate depression comorbid with Parkinson's disease. Early recognition and tailored management of depressive symptoms, mood and affective disturbances, cognitive impairment, and disease-specific characteristics are crucial for optimizing patient care and improving outcomes in individuals with Parkinson's disease. These findings underscore the need for a comprehensive, patient-centered approach that considers the diverse interaction of demographic, clinical, and cognitive variables.

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