Thirty patients with dementia defined by DSM-III-R criteria (Alzheimer's disease (22), vascular dementia (3), Parkinson's disease, frontal lobe dementia, possible diffuse Lewy body dementia, normal pressure hydrocephalus and uncertain diagnosis), with scores below 24 points in the Mini-Mental Status Examination and more than 4 years of education were submitted to a neuropsychological evaluation. The scores in the neuropsychological tests were compared to those obtained by thirty normal volunteers paired for age, sex and education. Sensitivity, specificity and accuracy of the tests in the distinction of demented and normal volunteers were determined. The accuracies were calculated using ROC curves. Blessed's information-memory-concentration test showed greatest accuracy, followed by copy of simple figures, delayed memory of 10 figures (after 5 minutes), recognition of 10 figures and verbal fluency test (animals). A linear discriminant function, composed by 6 tests: visual perception, incidental memory, delayed memory (after 5 minutes), drawing of a clock, verbal fluency (animals) and calculation tests, was able to discriminate all controls from patients and only one patient was wrongly classified as normal control. These tests were chosen because they can be applied in less than 10 minutes and are very easy to interpret. This discriminant function must be applied in another group of patients and controls in order to demonstrate its value. When associated to the MMSE it may be useful to discriminate patients with dementia from normal people in epidemiological studies.
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http://dx.doi.org/10.1590/s0004-282x1994000400001 | DOI Listing |
Alzheimers Res Ther
January 2025
Department of Neurology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan.
Background: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatment. This study developed machine learning models to classify positron emission tomography (PET) Aβ-positivity in participants with preclinical and prodromal AD using data accessible to primary care physicians.
View Article and Find Full Text PDFBMC Nurs
January 2025
Department of Pain Medicine, the 1st affiliated hospital, Jiangxi Medical College, Nanchang University, 17 Yongwai Street, Nanchang, China.
Background: Mild cognitive impairment (MCI) is prevalent in older adults with chronic pain, making early detection crucial for dementia prevention and healthy aging. This study aimed to determine MCI risk factors in older patients with chronic pain and to develop 9 machine learning models to identify MCI risk.
Methods: A total of 612 older patients with chronic pain were recruited between October 2023 and July 2024.
Neurol Sci
January 2025
Research Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Rome, Italy.
Background: Fear of Falling (FOF) significantly affects Parkinson's Disease (PD) patients by limiting daily activities and reducing quality of life (QoL). Though common in PD, the relation between FOF, mobility, and QoL remains unclear. This study examines the connections between FOF, gait, daily motor activity, and QoL in PD patients.
View Article and Find Full Text PDFNeurol Sci
January 2025
School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder ranging from mild cognitive impairment (MCI) to AD dementia. Abnormal cerebral perfusion alterations, influenced by amyloid-beta (Aβ) accumulations, have been implicated in cognitive decline along this spectrum.
Objective: This study investigates the relationship between cerebrospinal fluid (CSF) Aβ1-42 levels and regional cerebral blood flow (CBF) changes across the AD continuum using the Arterial Spin Labeling (ASL) technique.
NPJ Parkinsons Dis
January 2025
Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.
Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for PD.
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