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Chen H, Wang X, Zhang J, Xie D. Effect of high-frequency repetitive transcranial magnetic stimulation on cognitive impairment in WD patients based on inverse probability weighting of propensity scores. Front Neurosci 2024; 18:1375234. [PMID: 38660222 PMCID: PMC11039870 DOI: 10.3389/fnins.2024.1375234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 03/26/2024] [Indexed: 04/26/2024] Open
Abstract
Background Hepatolenticular degeneration [Wilson disease (WD)] is an autosomal recessive metabolic disease characterized by copper metabolism disorder. Cognitive impairment is a key neuropsychiatric symptom of WD. At present, there is no effective treatment for WD-related cognitive impairment. Methods In this study, high-frequency repetitive transcranial magnetic stimulation (rTMS) was used to treat WD-related cognitive impairment, and inverse probability weighting of propensity scores was used to correct for confounding factors. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Auditory Verbal Learning Test (AVLT), Boston Naming Test (BNT), Clock Drawing Test (CDT) and Trail Making Test (TMT) were used to evaluate overall cognition and specific cognitive domains. Results The MMSE, MoCA and CDT scores after treatment were significantly different from those before treatment (MMSE: before adjustment: OR = 1.404, 95% CI: 1.271-1.537; after adjustment: OR = 1.381, 95% CI: 1.265-1.497, p < 0.001; MoCA: before adjustment: OR = 1.306, 95% CI: 1.122-1.490; after adjustment: OR = 1.286, 95% CI: 1.104; AVLT: OR = 1.161, 95% CI: 1.074-1.248; after adjustment: OR = 1.145, 95% CI: 1.068-1.222, p < 0.05; CDT: OR = 1.524, 95% CI: 1.303-1.745; after adjustment: OR = 1.518, 95% CI: 1.294-1.742, p < 0.001). The BNT and TMT scores after adjustment were not significantly different from those before adjustment (BNT: before adjustment: OR = 1.048, 95% CI: 0.877-1.219; after adjustment: OR = 1.026, 95% CI: 0.863-1.189, p > 0.05; TMT: before adjustment: OR = 0.816, 95% CI: 1.122-1.490; after adjustment: OR = 0.791, 95% CI: 0.406-1.176, p > 0.05). Conclusion High-frequency rTMS can effectively improve cognitive impairment, especially memory and visuospatial ability, in WD patients. The incidence of side effects is low, and the safety is good.
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Affiliation(s)
- Hong Chen
- The First Clinical Mdical College of Anhui University of Chinese Medicine, Hefei, China
| | - Xie Wang
- The First Clinical Mdical College of Anhui University of Chinese Medicine, Hefei, China
| | - Juan Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China
| | - Daojun Xie
- Department of Neurology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, China
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Öksüz N, Ghouri R, Taşdelen B, Uludüz D, Özge A. Mild Cognitive Impairment Progression and Alzheimer's Disease Risk: A Comprehensive Analysis of 3553 Cases over 203 Months. J Clin Med 2024; 13:518. [PMID: 38256652 PMCID: PMC10817043 DOI: 10.3390/jcm13020518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/04/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024] Open
Abstract
This study aimed to elucidate the long-term progression of mild cognitive impairment (MCI) within a comprehensive longitudinal dataset, distinguish it from healthy aging, explore the influence of a dementia subtype on this progression, and identify potential contributing factors. Patients with prodromal and preclinical cases underwent regular neuropsychological assessments utilizing various tools. The study included a total of 140 participants with MCI, categorized into Alzheimer's disease (AD) and non-AD subtypes. Our dataset revealed an overall progression rate of 92.8% from MCI to the clinical stage of dementia during the follow-up period, with an annual rate of 15.7%. Notably, all prodromal cases of Lewy body dementia/Parkinson's disease (LBD/PDD) and frontotemporal dementia (FTD) advanced to clinical stages, whereas 7% of vascular dementia (VaD) cases and 8.4% of AD cases remained in the prodromal stage throughout follow-up. Furthermore, we observed a faster progression rate in MCI-AD cases compared to non-AD sufferers (53.9% vs. 35.5%, Entropy: 0.850). This study revealed significant cognitive changes in individuals with MCI over time. The mini-mental state examination (MMSE), global deterioration scale (GDS), and calculation tests were the most effective tests for evaluation of MCI. These findings may offer valuable insights for the development of personalized interventions and management strategies for individuals with MCI.
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Affiliation(s)
- Nevra Öksüz
- Department of Neurology, School of Medicine, Mersin University, Mersin 33110, Turkey; (N.Ö.); (R.G.)
| | - Reza Ghouri
- Department of Neurology, School of Medicine, Mersin University, Mersin 33110, Turkey; (N.Ö.); (R.G.)
| | - Bahar Taşdelen
- Department of Biostatistics, School of Medicine, Mersin University, Mersin 33110, Turkey;
| | - Derya Uludüz
- Department of Neurology, Brain 360 Holistic Approach Center, İstanbul 34353, Turkey;
| | - Aynur Özge
- Department of Neurology, School of Medicine, Mersin University, Mersin 33110, Turkey; (N.Ö.); (R.G.)
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Georgiou E(EZ, Prapiadou S, Thomopoulos V, Skondra M, Charalampopoulou M, Pachi A, Anagnostopoulou Α, Vorvolakos T, Perneczky R, Politis A, Alexopoulos P. Naming ability assessment in neurocognitive disorders: a clinician's perspective. BMC Psychiatry 2022; 22:837. [PMID: 36585667 PMCID: PMC9801565 DOI: 10.1186/s12888-022-04486-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 12/15/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Detecting impaired naming capacity is valuable in diagnosing neurocognitive disorders (ND). A. clinical practice- oriented overview of naming tests validated in ND is not available yet. Here, features of naming tests with validated utility in ND which are open access or available for purchase are succinctly presented and compared. METHODS Searches were carried out across Pubmed, Medline and Google Scholar. Additional studies were identified by searching reference lists. Only peer-reviewed journal articles were eligible. A narrative- and tabullar synthesis was used to summarize different aspects of the naming assessment instruments used in patients with ND such as stimuli type, administration time, assessment parameters and accessibility. Based on computational word frequency calculations, the tests were compared in terms of the average frequency of their linguistic content. RESULTS Twelve naming tests, relying either on visual or auditory stimuli have been validated in ND. Their content and administration time vary between three and 60 items and one and 20 minutes, respectively. The average frequency of the words of each considered test was two or lower, pointing to low frequency of most items. In all but one test, scoring systems are exclusively based on correctly named items. Seven instruments are open access and four are available in more than one language. CONCLUSIONS Gaining insights into naming tests' characteristics may catalyze the wide incorporation of those with short administration time but high diagnostic accuracy into the diagnostic workup of ND at primary healthcare and of extensive, visual or auditory ones into the diagnostic endeavors of memory clinics, as well as of secondary and tertiary brain healthcare settings.
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Affiliation(s)
- Eliza ( Eleni-Zacharoula) Georgiou
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
| | - Savvina Prapiadou
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
| | - Vasileios Thomopoulos
- Large-Scale Machine Learning & Cloud Data Engineering Laboratory (ML@Cloud-Lab), Faculty of Computer Engineering & Informatics, School of Engineering, University of Patras, Patras, Greece
| | - Maria Skondra
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
| | - Marina Charalampopoulou
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
| | - Asimina Pachi
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
| | - Αlexandra Anagnostopoulou
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
- General Hospital of Zakynthos “Saint Dionysios”, Zakynthos, Greece
| | - Theofanis Vorvolakos
- Department of Psychiatry, Faculty of Medicine, School of Health Sciences, University Hospital of Alexandroupolis, Democritus University of Thrace, Alexandroupolis, Greece
| | - Robert Perneczky
- Division of Mental Health in Older Adults and Alzheimer Therapy and Research Center, Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-Universität Munich, Munich, Germany
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology and Medicine, London, UK
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Sheffield Institute for Translational Neurosciences (SITraN), University of Sheffield, Sheffield, UK
| | - Antonios Politis
- First Department of Psychiatry, Eginition Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
- Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins Medical School, Baltimore, USA
| | - Panagiotis Alexopoulos
- Department of Psychiatry, Patras University General Hospital, Faculty of Medicine, School of Health Sciences, University of Patras, Patras, Greece
- Global Brain Health Institute, Medical School, Trinity College Dublin, The University of Dublin, Dublin, Republic of Ireland
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Faculty of Medicine, Technical University of Munich, Munich, Germany
- Patras Dementia Day Care Center, Corporation for Succor and Care of Elderly and Disabled – FRODIZO, Patras, Greece
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Paplikar A, Varghese F, Alladi S, Vandana VP, Darshini KJ, Iyer GK, Kandukuri R, Divyaraj G, Sharma M, Dhaliwal RS, Kaul S, Saroja AO, Ghosh A, Sunitha J, Khan AB, Mathew R, Mekala S, Menon R, Nandi R, Narayanan J, Nehra A, Padma MV, Pauranik A, Ramakrishnan S, Sarath L, Shah U, Tripathi M, Sylaja PN, Varma RP, Verma M, Vishwanath Y. Picture-naming test for a linguistically diverse population with cognitive impairment and dementia. INTERNATIONAL JOURNAL OF LANGUAGE & COMMUNICATION DISORDERS 2022; 57:881-894. [PMID: 35522006 DOI: 10.1111/1460-6984.12728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Picture-naming tests (PNTs) evaluate linguistic impairment in dementia due to semantic memory impairment, impaired lexical retrieval or perceptual deficits. They also assess the decline in naming impairment at various stages of dementia and mild cognitive impairment (MCI) that occurs due to progressive cognitive impairment. With the increasing numbers of people with dementia globally, it is necessary to have validated naming tests and norms that are culturally and linguistically appropriate. AIMS In this cross-sectional study we harmonized a set of 30 images applicable to the Indian context across five languages and investigated the picture-naming performance in patients with MCI and dementia. METHODS & PROCEDURES A multidisciplinary expert group formed by the Indian Council of Medical Research (ICMR) collaborated towards developing and adapting a picture naming test (PNT) known as the ICMR-PNT in five Indian languages: Hindi, Bengali, Telugu, Kannada and Malayalam. Based on cross-cultural adaptation guidelines and item-wise factor analysis and correlations established separately across five languages, the final version of the ICMR-PNT test was developed. A total of 368 controls, 123 dementia and 128 MCI patients were recruited for the study. Psychometric properties of the adapted version of the ICMR-PNT were examined, and sensitivity and specificity were examined. OUTCOMES & RESULTS The ICMR-PNT scores in all languages combined were higher in controls compared with patients with dementia and MCI (F2, 615 = 139.85; p < 0.001). Furthermore, PNT scores for MCI was higher in comparison with patients with dementia in all languages combined (p < 0.001). The area under the curve across the five languages ranged from 0.81 to 1.00 for detecting dementia. There was a negative correlation between Clinical Dementia Rating (CDR) and ICMR-PNT scores and a positive correlation between Addenbrooke's Cognitive Examination-III (ACE-III) and ICMR-PNT scores in control and patient groups. CONCLUSIONS & IMPLICATIONS The ICMR-PNT was developed by following cross-cultural adaptation guidelines and establishing correlations using item-wise factor analysis across five languages. This adapted PNT was found to be a reliable tool when assessing naming abilities effectively in mild to moderate dementia in a linguistically diverse context. WHAT THIS PAPER ADDS What is already known on this subject Picture-naming evaluates language impairment linked to naming difficulties due to semantic memory, lexical retrieval or perceptual disturbances. As a result, picture naming tests (PNTs) play an important role in the diagnosis of dementia. In a heterogeneous population such as India, there is a need for a common PNT that can be used across the wide range of languages. What this study adds to existing knowledge PNTs such as the Boston Naming Test (BNT) were developed for the educated, mostly English-speaking, Western populations and are not appropriate for use in an Indian context. To overcome this challenge, a PNT was harmonized in five Indian languages (Hindi, Bengali, Telugu, Kannada and Malayalam) and we report the patterns of naming difficulty in patients with MCI and dementia. The ICMR-PNT demonstrated good diagnostic accuracy when distinguishing patients with mild to moderate dementia from cognitively normal individuals. What are the potential or actual clinical implications of this work? With the growing number of persons suffering from Alzheimer's disease and other forms of dementia around the world, its critical to have culturally and linguistically relevant naming tests and diagnosis. This validated ICMR-PNT can be used widely as a clinical tool to diagnose dementia and harmonize research efforts across diverse populations.
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Affiliation(s)
- Avanthi Paplikar
- Department of Speech and Language Studies, Dr. S. R. Chandrasekhar Institute of Speech and Hearing, Bengaluru, India
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Feba Varghese
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Suvarna Alladi
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India
- Department of Neurology, Nizam's Institute of Medical Sciences, Hyderabad, India
| | - V P Vandana
- Department of Speech-Language-Pathology and Audiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - K J Darshini
- Department of Speech-Language-Pathology and Audiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Gowri K Iyer
- Department of Neurology, Nizam's Institute of Medical Sciences, Hyderabad, India
- Indian Institute of Public Health, Hyderabad, India
| | - Rajmohan Kandukuri
- Department of Neurology, Nizam's Institute of Medical Sciences, Hyderabad, India
| | - Gollahalli Divyaraj
- Department of Neurology, Nizam's Institute of Medical Sciences, Hyderabad, India
- Pause for Perspective Uma Nagar, Hyderabad, India
| | | | - R S Dhaliwal
- Indian Council of Medical Research (ICMR), Delhi, India
| | - Subhash Kaul
- Department of Neurology, Nizam's Institute of Medical Sciences, Hyderabad, India
- Krishna Institute of Medical Sciences, Hyderabad, India
| | - Aralikatte Onkarappa Saroja
- Jawaharlal Nehru Medical College, KLE Academy of Higher Education and Research Center Belagavi, Karnataka, India
| | - Amitabha Ghosh
- Apollo Gleneagles Hospital, Cognitive Neurology Unit, Kolkata, India
| | - J Sunitha
- Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Arfa Banu Khan
- Department of Psychiatry, KAHER's Jawaharlal Nehru Medical College and Research Center Belagavi, Karnataka, India
| | | | - Shailaja Mekala
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Ramshekhar Menon
- Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Ranita Nandi
- Jawaharlal Nehru Medical College, KLE Academy of Higher Education and Research Center Belagavi, Karnataka, India
| | | | - Ashima Nehra
- Clinical Neuropsychology, Neurosciences Centre, All India Institute of Medical Sciences, Delhi, India
| | - M V Padma
- Department of Neurology, All India Institute of Medical Sciences, Delhi, India
| | | | - Subasree Ramakrishnan
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Lekha Sarath
- Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | | | - Manjari Tripathi
- Department of Neurology, All India Institute of Medical Sciences, Delhi, India
| | - P N Sylaja
- Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Ravi Prasad Varma
- Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
| | - Mansi Verma
- Department of Neurology, All India Institute of Medical Sciences, Delhi, India
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