Andrew J Perrin1, Ekaterina Nosova2, Kim Co2, Adam Book3, Oscar Iu2, Vanessa Silva3, Christina Thompson2, Martin J McKeown4, A Jon Stoessl4, Matthew J Farrer2, Silke Appel-Cresswell5. 1. Research Track Residency, Department of Psychiatry, University of British Columbia, Vancouver, BC V5Z 1M9, Canada; Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 2B5, Canada. Electronic address: perrinan@mail.ubc.ca. 2. Djavad Mowafaghian Centre for Brain Health, Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T 2B5, Canada. 3. Djavad Mowafaghian Centre for Brain Health, Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T 2B5, Canada; Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 2B5, Canada. 4. Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 2B5, Canada. 5. Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 2B5, Canada. Electronic address: silkec@mail.ubc.ca.
Abstract
INTRODUCTION: 30-40% of patients with Parkinson's disease (PD) experience depression during their illness; identifying subtypes of depression and groups at risk remains a challenge in routine clinical care. One avenue that remains underexplored is the gender-specific profiles manifested in PD depression. We sought to explore this in a large sample of clinical PD patients. METHODS: 307 patient records at a tertiary referral centre were reviewed for clinical and demographic factors. We used recursive partitioning to determine which items on the Beck Depression Inventory (BDI) were most useful in differentiating patients who scored in the depressed range (≥14) from those who scored in the non-depressed range (≤13). We also used recursive partitioning to identify those BDI items that were most effective in differentiating depressed from non-depressed patients in both genders. RESULTS: We were able to identify a subset of items on the BDI that were most useful in partitioning depressed from non-depressed in the entire cohort. Partitioning of men and women with PD depression relied on different key BDI items, melancholy featuring prominently in women, while the more classical factors associated with depression in PD (apathy and loss of libido) featured more prominently in men. CONCLUSION: Unique factors not previously identified as core features of depression in PD were found most useful in partitioning depressed women from non-depressed women. This raises the possibility that a female-specific depressive profile has been under-appreciated in past work. Additional studies are required to discern how this may impact future research, diagnosis and treatment.
INTRODUCTION: 30-40% of patients with Parkinson's disease (PD) experience depression during their illness; identifying subtypes of depression and groups at risk remains a challenge in routine clinical care. One avenue that remains underexplored is the gender-specific profiles manifested in PD depression. We sought to explore this in a large sample of clinical PDpatients. METHODS: 307 patient records at a tertiary referral centre were reviewed for clinical and demographic factors. We used recursive partitioning to determine which items on the Beck Depression Inventory (BDI) were most useful in differentiating patients who scored in the depressed range (≥14) from those who scored in the non-depressed range (≤13). We also used recursive partitioning to identify those BDI items that were most effective in differentiating depressed from non-depressed patients in both genders. RESULTS: We were able to identify a subset of items on the BDI that were most useful in partitioning depressed from non-depressed in the entire cohort. Partitioning of men and women with PD depression relied on different key BDI items, melancholy featuring prominently in women, while the more classical factors associated with depression in PD (apathy and loss of libido) featured more prominently in men. CONCLUSION: Unique factors not previously identified as core features of depression in PD were found most useful in partitioning depressed women from non-depressed women. This raises the possibility that a female-specific depressive profile has been under-appreciated in past work. Additional studies are required to discern how this may impact future research, diagnosis and treatment.
Authors: Cynthia M Funes; Helen Lavretsky; Linda Ercoli; Natalie St Cyr; Prabha Siddarth Journal: Am J Geriatr Psychiatry Date: 2017-06-16 Impact factor: 4.105
Authors: Luiz Philipe de Souza Ferreira; Rafael André da Silva; Matheus Marques Mesquita da Costa; Vinicius Moraes de Paiva Roda; Santiago Vizcaino; Nilma R L L Janisset; Renata Ramos Vieira; José Marcos Sanches; José Maria Soares Junior; Manuel de Jesus Simões Journal: Clinics (Sao Paulo) Date: 2022-10-01 Impact factor: 2.898