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van der Vaart AD, Ma Y, Chiappelli J, Bruce H, Kvarta MD, Warner A, Du X, Adhikari BM, Sampath H, Kochunov P, Hong LE. Revisiting delusion subtypes in schizophrenia based on their underlying structures. J Psychiatr Res 2024; 171:75-83. [PMID: 38246028 PMCID: PMC10923062 DOI: 10.1016/j.jpsychires.2023.12.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/10/2023] [Accepted: 12/12/2023] [Indexed: 01/23/2024]
Abstract
A clear understanding of the pathophysiology of schizophrenia and related spectrum disorders has been limited by clinical heterogeneity. We investigated whether relative severity and predominance of one or more delusion subtypes might yield clinically differentiable patient profiles. Patients (N = 286) with schizophrenia spectrum disorders (SSD) completed the 21-item Peters et al. Delusions Inventory (PDI-21). We performed factor analysis followed by k-means clustering to identify delusion factors and patient subtypes. Patients were further assessed via the Brief Psychiatric Rating Scale, Brief Negative Symptom Scale, Digit Symbol and Digit Substitution tasks, use of cannabis and tobacco, and stressful life events. The overall patient sample clustered into subtypes corresponding to Low-Delusion, Grandiose-Predominant, Paranoid-Predominant, and Pan-Delusion patients. Paranoid-Predominant and Pan-Delusion patients showed significantly higher burden of positive symptoms, while Low-Delusion patients showed the highest burden of negative symptoms. The Paranoia delusion factor score showed a positive association with Digit Symbol and Digit Substitution tasks in the overall sample, and the Paranoid-Predominant subtype exhibited the best performance on both tasks. Grandiose-Predominant patients showed significantly higher tobacco smoking severity than other subtypes, while Paranoid-Predominant patients were significantly more likely to have a lifetime diagnosis of Cannabis Use Disorder. We suggest that delusion self-report inventories such as the PDI-21 may be of utility in identifying sub-syndromes in SSD. From the current study, a Paranoid-Predominant form may be most distinctive, with features including less cognitive impairment and a stronger association with cannabis use.
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Affiliation(s)
- Andrew D van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alia Warner
- Louis A Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiaoming Du
- Louis A Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Bhim M Adhikari
- Louis A Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Hemalatha Sampath
- Louis A Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Peter Kochunov
- Louis A Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - L Elliot Hong
- Louis A Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.
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Cubo E, Luo S, Martínez‐Martín P, Stebbins GT, Lin J, Choi D, García‐Bustillo A, Mir P, Santos‐Garcia D, Serrano‐Dueñas M, Rodriguez‐Violante M, Singer C. Expanded and Independent Spanish Validation of the MDS-Non Motor Rating Scale. Mov Disord Clin Pract 2023; 10:586-595. [PMID: 37071078 PMCID: PMC10105117 DOI: 10.1002/mdc3.13658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/08/2023] [Indexed: 01/16/2023] Open
Abstract
Background The Movement Disorder Society-sponsored Non-motor Rating Scale (MDS-NMS) assess the severity and disability caused by non-motor symptoms (NMS) in Parkinson's disease (PD). Objective This article encapsulates the formal process for completing this program and the data on the first officially approved non-English version of the MDS-NMS (Spanish). Methods The MDS-NMS translation program involves four steps: translation and back-translation; cognitive pre-testing to ensure that raters and patients understand the scale and are comfortable with its content; field testing of the finalized version; analysis of the factor structure of the tested version against the original English language version for the nine domains that could be analyzed in a confirmatory factor analysis. To be designated an "Official MDS translation," the confirmatory factor analysis Comparative Fit Index had to be ≥0.90. Results The Spanish MDS-NMS was tested in 364 native-Spanish-speaking patients with PD from seven countries. For all subjects with fully computable data with all domains of the MDS-NMS (n = 349), the Comparative Fit Index was ≥0.90 for the nine eligible domains. Missing data were negligible and moderate floor effect (42.90%) was found for the Non-Motor Fluctuations subscale. Item homogeneity coefficient was adequate, and the correlation of the MDS-NMS domains with other measures for related constructs was acceptable (r s ≥ 0.50). Conclusions The Spanish version of the MDS-NMS followed the IPMDS Translation Program protocol, reached the criterion to be designated as an Official Translation, and is now available on the MDS website.
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Affiliation(s)
- Esther Cubo
- Neurology DepartmentComplejo Asistencial Universitario de BurgosBurgosSpain
- Health Science DepartmentUniversity of BurgosBurgosSpain
| | - Sheng Luo
- Department of Biostatistics & BioinformaticsDuke UniversityDurhamNorth CarolinaUSA
| | - Pablo Martínez‐Martín
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas)MadridSpain
| | - Glenn T. Stebbins
- Professor EmeritusNeurological Sciences Rush University Medical CenterChicagoIllinoisUSA
| | - Jeffrey Lin
- Department of Biostatistics & BioinformaticsDuke UniversityDurhamNorth CarolinaUSA
| | - Dongrak Choi
- Department of Biostatistics & BioinformaticsDuke UniversityDurhamNorth CarolinaUSA
| | | | - Pablo Mir
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas)MadridSpain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de SevillaHospital Universitario Virgen del Rocío/CSIC/Universidad de SevillaSevillaSpain
- Departamento de Medicina, Facultad de MedicinaUniversidad de SevillaSevillaSpain
| | | | | | | | - Carlos Singer
- Leonard M. Miller School of MedicineUniversity of MiamiMiamiFloridaUSA
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Weintraub D, Aarsland D, Chaudhuri KR, Dobkin RD, Leentjens AF, Rodriguez-Violante M, Schrag A. The neuropsychiatry of Parkinson's disease: advances and challenges. Lancet Neurol 2022; 21:89-102. [PMID: 34942142 PMCID: PMC8800169 DOI: 10.1016/s1474-4422(21)00330-6] [Citation(s) in RCA: 134] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 08/21/2021] [Accepted: 09/20/2021] [Indexed: 01/03/2023]
Abstract
In people with Parkinson's disease, neuropsychiatric signs and symptoms are common throughout the disease course. These symptoms can be disabling and as clinically relevant as motor symptoms, and their presentation can be similar to, or distinct from, their counterparts in the general population. Correlates and risk factors for developing neuropsychiatric signs and symptoms include demographic, clinical, and psychosocial characteristics. The underlying neurobiology of these presentations is complex and not well understood, with the strongest evidence for neuropathological changes associated with Parkinson's disease, mechanisms linked to dopaminergic therapy, and effects not specific to Parkinson's disease. Assessment instruments and formal diagnostic criteria exist, but there is little routine screening of these signs and symptoms in clinical practice. Mounting evidence supports a range of pharmacological and non-pharmacological interventions, but relatively few efficacious treatment options exist. Optimising the management of neuropsychiatric presentations in people with Parkinson's disease will require additional research, raised awareness, specialised training, and development of innovative models of care.
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Affiliation(s)
- Daniel Weintraub
- Departments of Psychiatry and Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Parkinson's Disease Research, Education and Clinical Center, Corporal Michael J Crescenz Philadelphia Veterans Affairs Medical Center, Philadelphia, PA, USA.
| | - Dag Aarsland
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Centre for Age-Related Disease, Stavanger University Hospital, Stavanger, Norway
| | - Kallol Ray Chaudhuri
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Parkinson's Foundation Centre of Excellence, King's College Hospital, King's College London, London, UK
| | - Roseanne D Dobkin
- Department of Psychiatry, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, USA
| | - Albert Fg Leentjens
- Department of Psychiatry, and School for Mental Health and Neuroscience, Maastricht University Hospital, Maastricht, Netherlands
| | - Mayela Rodriguez-Violante
- Clinical Neurodegenerative Diseases Research Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Anette Schrag
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, UCL, London, UK
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Rodriguez-Sanchez F, Rodriguez-Blazquez C, Bielza C, Larrañaga P, Weintraub D, Martinez-Martin P, Rizos A, Schrag A, Chaudhuri KR. Identifying Parkinson's disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering. Sci Rep 2021; 11:23645. [PMID: 34880345 PMCID: PMC8654994 DOI: 10.1038/s41598-021-03118-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 11/29/2021] [Indexed: 12/27/2022] Open
Abstract
Identification of Parkinson's disease subtypes may help understand underlying disease mechanisms and provide personalized management. Although clustering methods have been previously used for subtyping, they have reported generic subtypes of limited relevance in real life practice because patients do not always fit into a single category. The aim of this study was to identify new subtypes assuming that patients could be grouped differently according to certain sets of related symptoms. To this purpose, a novel model-based multi-partition clustering method was applied on data from an international, multi-center, cross-sectional study of 402 Parkinson's disease patients. Both motor and non-motor symptoms were considered. As a result, eight sets of related symptoms were identified. Each of them provided a different way to group patients: impulse control issues, overall non-motor symptoms, presence of dyskinesias and pyschosis, fatigue, axial symptoms and motor fluctuations, autonomic dysfunction, depression, and excessive sweating. Each of these groups could be seen as a subtype of the disease. Significant differences between subtypes (P< 0.01) were found in sex, age, age of onset, disease duration, Hoehn & Yahr stage, and treatment. Independent confirmation of these results could have implications for the clinical management of Parkinson's disease patients.
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Affiliation(s)
| | - Carmen Rodriguez-Blazquez
- National Center of Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Carlos III Institute of Health, Madrid, Spain
| | - Concha Bielza
- Computational Intelligence Group, Universidad Politécnica de Madrid, Madrid, Spain
| | - Pedro Larrañaga
- Computational Intelligence Group, Universidad Politécnica de Madrid, Madrid, Spain
| | - Daniel Weintraub
- Departments of Psychiatry and Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Pablo Martinez-Martin
- Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Carlos III Institute of Health, Madrid, Spain
| | - Alexandra Rizos
- King's College London, Department of Neurosciences, Institute of Psychiatry, Psychology & Neuroscience and Parkinson's Foundation Centre of Excellence, King's College Hospital, London, UK
| | - Anette Schrag
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - K Ray Chaudhuri
- King's College London, Department of Neurosciences, Institute of Psychiatry, Psychology & Neuroscience and Parkinson's Foundation Centre of Excellence, King's College Hospital, London, UK
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Urso D, Leta V, Batzu L, Yousaf T, Farrell C, van Wamelen DJ, Ray Chaudhuri K. Disentangling the PIGD classification for the prediction of cognitive impairment in de novo Parkinson's disease. J Neurol 2021; 269:1566-1573. [PMID: 34338858 PMCID: PMC8857169 DOI: 10.1007/s00415-021-10730-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 07/19/2021] [Accepted: 07/26/2021] [Indexed: 11/29/2022]
Abstract
Background Postural Instability and Gait difficulties (PIGD) subtype has been associated with worse cognitive performance in Parkinson’s disease (PD). Objective To investigate whether PIGD subtype classification or PIGD-related clinical features predict the development of cognitive decline in de novo PD patients. Methods Data from 422 PD patients with de novo PD were obtained from the PPMI database. At follow-up (up to 6 years), patients were categorized as having cognitive impairment or not. Multivariate Cox survival analysis was carried out including motor subtype and individual MDS-UPDRS items defining PIGD phenotype as predictors. Previously validated clinical predictors of cognitive impairment were included in the model as covariates. Occurrence of cognitive impairment at follow-up was used as the time-to-event and Kaplan–Meier curve was generated. Results At baseline, 76 patients were classified as PIGD, 299 tremor-dominant and 47 as indeterminate. Development of cognitive impairment was not associated with PIGD subtype (p = 0.252). When individual MDS-UPDRS items were interrogated in the model, postural instability proved to be an independent predictor of cognitive impairment (HR = 2.045; 95%CI: 1.068–3.918; p = 0.031), while gait difficulties were not associated with cognitive decline (p = 0.870). Conclusions Our findings suggest that postural instability, as assessed by MDS-UPDRS III, may serve as a possible indicator of the risk of developing cognitive impairment in de novo PD patients rather than the PIGD phenotype.
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Affiliation(s)
- Daniele Urso
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. .,Parkinson's Foundation Centre of Excellence, King's College Hospital, Denmark Hill, London, UK. .,Department of Clinical Research in Neurology, Center for Neurodegenerative Diseases and the Aging Brain, University of Bari 'Aldo Moro', "Pia Fondazione Cardinale G. Panico", Tricase, Lecce, Italy.
| | - Valentina Leta
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Parkinson's Foundation Centre of Excellence, King's College Hospital, Denmark Hill, London, UK
| | - Lucia Batzu
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Parkinson's Foundation Centre of Excellence, King's College Hospital, Denmark Hill, London, UK
| | - Tayyabah Yousaf
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Chloe Farrell
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Daniel J van Wamelen
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Parkinson's Foundation Centre of Excellence, King's College Hospital, Denmark Hill, London, UK.,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - K Ray Chaudhuri
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Parkinson's Foundation Centre of Excellence, King's College Hospital, Denmark Hill, London, UK
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Rukavina K, Batzu L, Boogers A, Abundes-Corona A, Bruno V, Chaudhuri KR. Non-motor complications in late stage Parkinson's disease: recognition, management and unmet needs. Expert Rev Neurother 2021; 21:335-352. [PMID: 33522312 DOI: 10.1080/14737175.2021.1883428] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Introduction: The burden of non-motor symptoms (NMS) is a major determinant of health-related quality of life in Parkinson's disease (PD), particularly at its late stage.Areas covered: The late stage is usually defined as the period from unstable advanced to the palliative stage, characterized by a combination of emerging treatment-resistant axial motor symptoms (freezing of gait, postural instability, falls and dysphagia), as well as both non-dopaminergic and dopaminergic NMS: cognitive decline, neuropsychiatric symptoms, aspects of dysautonomia, pain and sleep disturbances (insomnia and excessive day-time sleepiness). Here, the authors summarize the current knowledge on NMS dominating the late stage of PD and propose a pragmatic and clinically focused approach for their recognition and treatment.Expert opinion: The NMS progression pattern is complex and remains under-researched. While dopamine-dependent NMS may improve with dopamine replacement therapy, non-dopamine dependent NMS worsen progressively and culminate at the late stages of PD. Furthermore, some PD specific features could interact negatively with other comorbidities, multiple medication use and frailty - the evaluation of these aspects is important in the creation of personalized management plans in the late stage of PD.
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Affiliation(s)
- Katarina Rukavina
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience at King's College and King's College Hospital NHS Foundation Trust, London, UK.,Parkinson Foundation Centre of Excellence, King's College Hospital, London, UK
| | - Lucia Batzu
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience at King's College and King's College Hospital NHS Foundation Trust, London, UK.,Parkinson Foundation Centre of Excellence, King's College Hospital, London, UK
| | - Alexandra Boogers
- Department of Neurology, University Hospital Leuven, Leuven, U.Z, Belgium
| | - Arturo Abundes-Corona
- Department of Neurology, Clinical Laboratory of Neurodegenerative Diseases, National Institute of Neurology and Neurosurgery, Mexico City, México.,Neurology Department, American British Cowdray Medical Center IAP, Mexico City, Mexico
| | - Veronica Bruno
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - K Ray Chaudhuri
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience at King's College and King's College Hospital NHS Foundation Trust, London, UK.,Parkinson Foundation Centre of Excellence, King's College Hospital, London, UK
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