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Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative...
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Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Health Assessments".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 8766

Special Issue Editor

Dr. Seyed Mohammad Fereshtehnejad

E-Mail Website
Guest Editor
1. Division of Neurology, Department of Medicine, University of Ottawa, Ottawa, ON K1N 6N5, Canada
2. Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, 14186 Stockholm, Sweden
Interests: neuroepidemiology; clinical neuroscience; neurodegenerative disorders; neuroimaging; Parkinson's disease; neuro-prevention

Special Issue Information

Dear Colleagues,

Neurodegenerative disorders are a heterogenous group of neurologic entities with various pathogenesis consisting of proteinopathies (e.g., Parkinson’s disease, Alzheimer’s disease, other dementias), motor neuron diseases (e.g., amyotrophic lateral sclerosis (ALS)), autoimmune-related (e.g., multiple sclerosis), or genetic disorders (e.g., Huntington's disease, spinocerebellar ataxia (SCA)). Neurodegenerative diseases are progressive, with debilitating consequences affecting motor, cognitive, and behavioural performances. The burden of these diseases, particularly age-related proteinopathies (e.g., Parkinson’s disease and Alzheimer’s disease), is steadily increasing in most countries, mainly due to population ageing and longevity. Due to multi-domain involvement, chronicity and progressive course, caring for people with neurodegenerative diseases is highly complex. Even though many of the neurodegenerative diseases (i.e., Parkinson’s disease and Alzheimer’s disease) are preceded by a long prodromal stage of up to 1–2 decades prior to the presence of debilitating motor or cognitive symptoms, there is currently no neuroprotective agent that can reverse or halt their pathogenesis. Furthermore, disease modifying treatments only exist for certain conditions, such as multiple sclerosis.         

This Special Issue seeks manuscripts that address different aspects of neurodegenerative diseases, namely prevention, diagnosis, symptomatic and/or disease modifying treatments, as well as multidisciplinary management and care plans. Original articles and reviews will be considered. Papers tackling the themes of prevention, novel diagnostic biomarkers, treatments and the latest advances in the management of neurodegenerative diseases using a multidisciplinary approach are of particular interest.

This Special Issue aims to provide an updated panorama of the current state of the art and future healthcare trends to reduce the global burden of neurodegenerative diseases.

Dr. Seyed Mohammad Fereshtehnejad
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • healthcare
  • disease modifying treatment
  • prevention
  • neurorehabilitation
  • neuroimaging
  • neurodegenerative diseases
  • Alzheimer’s disease and other dementias
  • Parkinson’s disease
  • motor neuron disease
  • multiple system atrophy
  • progressive supranuclear palsy
  • multiple sclerosis
  • Huntington's disease

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Published Papers (7 papers)

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14 pages, 1510 KiB  
Article
Development and Validation of the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk)
by Jiangwei Chen, Qing Fang, Kehua Yang, Jiayu Pan, Lanlan Zhou, Qunli Xu and Yuedi Shen
Healthcare 2024, 12(20), 2015; https://doi.org/10.3390/healthcare12202015 - 10 Oct 2024
Viewed by 585
Abstract
Objectives: The aim was to develop and validate the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk), aiding community healthcare workers in the early identification of individuals at high risk of mild cognitive impairment (MCI). Methods: Based on nationally representative community [...] Read more.
Objectives: The aim was to develop and validate the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk), aiding community healthcare workers in the early identification of individuals at high risk of mild cognitive impairment (MCI). Methods: Based on nationally representative community survey data, backward stepwise regression was employed to screen the variables, and logistic regression was utilized to construct the CGMCI-Risk. Internal validation was conducted using bootstrap resampling, while external validation was performed using temporal validation. The area under the receiver operating characteristic curve (AUROC), calibration curve, and decision curve analysis (DCA) were employed to evaluate the CGMCI-Risk in terms of discrimination, calibration, and net benefit, respectively. Results: The CGMCI-Risk model included variables such as age, educational level, sex, exercise, garden work, TV watching or radio listening, Instrumental Activity of Daily Living (IADL), hearing, and masticatory function. The AUROC was 0.781 (95% CI = 0.766 to 0.796). The calibration curve showed strong agreement, and the DCA suggested substantial clinical utility. In external validation, the CGMCI-Risk model maintained a similar performance with an AUROC of 0.782 (95% CI = 0.763 to 0.801). Conclusions: CGMCI-Risk is an effective tool for assessing cognitive function risk within the community. It uses readily predictor variables, allowing community healthcare workers to identify the risk of MCI in older adults over a three-year span. Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
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18 pages, 3243 KiB  
Article
Prediction Model for Cognitive Impairment among Disabled Older Adults: A Development and Validation Study
by Xiangyu Cui, Xiaoyu Zheng and Yun Lu
Healthcare 2024, 12(10), 1028; https://doi.org/10.3390/healthcare12101028 - 15 May 2024
Cited by 1 | Viewed by 1325
Abstract
Disabled older adults exhibited a higher risk for cognitive impairment. Early identification is crucial in alleviating the disease burden. This study aims to develop and validate a prediction model for identifying cognitive impairment among disabled older adults. A total of 2138, 501, and [...] Read more.
Disabled older adults exhibited a higher risk for cognitive impairment. Early identification is crucial in alleviating the disease burden. This study aims to develop and validate a prediction model for identifying cognitive impairment among disabled older adults. A total of 2138, 501, and 746 participants were included in the development set and two external validation sets. Logistic regression, support vector machine, random forest, and XGBoost were introduced to develop the prediction model. A nomogram was further established to demonstrate the prediction model directly and vividly. Logistic regression exhibited better predictive performance on the test set with an area under the curve of 0.875. It maintained a high level of precision (0.808), specification (0.788), sensitivity (0.770), and F1-score (0.788) compared with the machine learning models. We further simplified and established a nomogram based on the logistic regression, comprising five variables: age, daily living activities, instrumental activity of daily living, hearing impairment, and visual impairment. The areas under the curve of the nomogram were 0.871, 0.825, and 0.863 in the internal and two external validation sets, respectively. This nomogram effectively identifies the risk of cognitive impairment in disabled older adults. Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
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12 pages, 303 KiB  
Article
Differences in Motor Imagery Ability between People with Parkinson’s Disease and Healthy Controls, and Its Relationship with Functionality, Independence and Quality of Life
by María del Rosario Ferreira-Sánchez, Marcos Moreno-Verdú, María de los Ángeles Atín-Arratibel and Patricia Martín-Casas
Healthcare 2023, 11(21), 2898; https://doi.org/10.3390/healthcare11212898 - 3 Nov 2023
Cited by 3 | Viewed by 1960 | Correction
Abstract
Motor imagery (MI) has been shown to be effective for the acquisition of motor skills; however, it is still unknown whether similar benefits can be achieved in neurological patients. Previous findings of differences in MI ability between people with Parkinson’s disease (PwPD) and [...] Read more.
Motor imagery (MI) has been shown to be effective for the acquisition of motor skills; however, it is still unknown whether similar benefits can be achieved in neurological patients. Previous findings of differences in MI ability between people with Parkinson’s disease (PwPD) and healthy controls (HCs) are mixed. This study examined differences in the ability to both create and maintain MI as well as investigating the relationship between the ability to create and maintain MI and motor function, independence and quality of life (QoL). A case–control study was conducted (31 PwPD and 31 HCs), collecting gender, age, dominance, socio-demographic data, duration and impact of the disease. MI intensity (MIQ-RS and KVIQ-34) and temporal accuracy of MI (imagined box and block test [iBBT], imagined timed stand and walk test [iTUG]) were assessed. Functional and clinical assessments included upper limb motor function, balance, gait, independence in activities of daily living and quality of life measures. Statistically significant differences in temporal accuracy were observed and partial and weak relationships were revealed between MI measures and functioning, independence and QoL. PwPD retain the ability to create MI, indicating the suitability of MI in this population. Temporal accuracy might be altered as a reflection of bradykinesia on the mentally simulated actions. Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
14 pages, 639 KiB  
Article
Falls and Sleep Disorders in Spanish Alzheimer’s Disease in Nursing Homes: An Observational Study
by Rubén Cámara-Calmaestra, Antonio Martínez-Amat, Agustín Aibar-Almazán, Fidel Hita-Contreras, Nerea De Miguel-Hernando, Daniel Rodríguez-Almagro, Raquel Fábrega-Cuadros and Alexander Achalandabaso-Ochoa
Healthcare 2023, 11(21), 2852; https://doi.org/10.3390/healthcare11212852 - 30 Oct 2023
Viewed by 1406
Abstract
Objective: The main objective of this study was to establish a relationship between the number of falls and sleep problems experienced by patients with Alzheimer’s disease. Materials and Methods: This was a cross-sectional study. A total of 114 Spanish aged people with Alzheimer’s [...] Read more.
Objective: The main objective of this study was to establish a relationship between the number of falls and sleep problems experienced by patients with Alzheimer’s disease. Materials and Methods: This was a cross-sectional study. A total of 114 Spanish aged people with Alzheimer’s disease institutionalized in nursing homes and 80 independent Spanish aged people without neurodegenerative diseases living at home were enrolled in this study and completed in-person interviews and digital questionnaires. Results: The mean age was 78.98 ± 8.59 years. Sleep disorders were related to continuous stress (p = 0.001; OR = 4.729) and a high frequency of falls (p = 0.001; OR = 2.145), while predictor variables associated with falls in patients with Alzheimer’s disease were continuous medical visits (β = 0.319, p < 0.001), family history of dementia (β = 0.212; p = 0.014), and sleep disorders (β = 0.235; p = 0.007). Second, the analysis showed that moderate physical activity (p = 0.001; OR = 0.147), continuous medical visits (p < 0.001; OR = 0.621), and high level of study (p = 0.011; OR = 0.334) were protective factors against Alzheimer’s, while older age (p = 0.035; OR = 1.087), type II Diabetes Mellitus (p = 0.042; OR = 3.973), number of falls (p = 0.021; OR = 1.409), and daily drug intake (p = 0.001; OR = 1.437) were risk factors for Alzheimer’s. Conclusions: Sleep disturbances are related to stress and falls in a sample of 114 Spanish AD aged people institutionalized in nursing homes, and the falls they experience are related to ongoing medical visits, a history of dementia, and sleep disturbances. Therefore, a bidirectional relationship was established between falls and sleep disorders in these patients. Moreover, this study showed that a greater frequency of falls and high daily drug intake could constitute novel risk factors for Alzheimer’s disease, in addition to already known factors, such as age and type II Diabetes Mellitus, while being physically active and a high level of studies are protective factors against Alzheimer’s disease. Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
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27 pages, 13455 KiB  
Article
A Pilot Fuzzy System with Virtual Reality for Mild Cognitive Impairment (MCI) Assessment
by Cheng-Li Liu, Che-Jen Chuang and Chin-Mei Chou
Healthcare 2023, 11(18), 2503; https://doi.org/10.3390/healthcare11182503 - 9 Sep 2023
Cited by 1 | Viewed by 1290
Abstract
Mild cognitive impairment (MCI) is when brain function declines. MCI is the gray area transitioning from normal aging to the AD stage. Currently, the majority of early MCI diagnoses are processed through comprehensive neuropsychological tests. These tests may take the form of interviews, [...] Read more.
Mild cognitive impairment (MCI) is when brain function declines. MCI is the gray area transitioning from normal aging to the AD stage. Currently, the majority of early MCI diagnoses are processed through comprehensive neuropsychological tests. These tests may take the form of interviews, paper-and-pencil tests, or computer-based tests. There may be resistance from the subject if he/she has to undergo many screening tests simultaneously for multiple evaluation information, resulting in execution difficulty. The objectives of this study are to use 3D virtual reality to create an entertaining test scenario integrating the Mini-Cog, SPMSQ, MMSE, SLUMS, CDR, and CASI for middle-aged to older adults, furthermore, to employ fuzzy logic control (FLC) technology to develop a “MCI assessment system” for obtaining some pilot information for MCI assessment. There were 24 middle-aged to older adults aged from 50 to 65 years who participated in the evaluation experiment. The results showed that the MCI assessment system developed in this study is highly correlated with the traditional screening tests, including the Mini-Cog, SPMSQ, MMSE, SLUMS, and CASI. The assessment system can provide an integrated reference score for clinic workers in making judgments. In addition, the distribution of the System Usability Scale (SUS) evaluation scores for the MCI assessment system revealed that 87.5% were grade C (good to use) or above and 29.2% were grade B (extremely good to use) or above. The assessment system received positive feedback from the subjects. Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
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19 pages, 4718 KiB  
Article
Multi-Criterial Model for Weighting Biological Risk Factors in Multiple Sclerosis: Clinical and Health Insurance Implications
by Roberto De Masi, Stefania Orlando, Chiara Leo, Matteo Pasca, Luca Anzilli and Maria Carmela Costa
Healthcare 2023, 11(17), 2420; https://doi.org/10.3390/healthcare11172420 - 29 Aug 2023
Viewed by 1096
Abstract
The etiology of Multiple Sclerosis (MS) remains undetermined. Its pathogenic risk factors are thought to play a negligible role individually in the development of the disease, instead assuming a pathogenic role when they interact with each other. Unfortunately, the statistical weighting of this [...] Read more.
The etiology of Multiple Sclerosis (MS) remains undetermined. Its pathogenic risk factors are thought to play a negligible role individually in the development of the disease, instead assuming a pathogenic role when they interact with each other. Unfortunately, the statistical weighting of this pathogenic role in predicting MS risk is currently elusive, preventing clinical and health insurance applications. Here, we aim to develop a population-based multi-criterial model for weighting biological risk factors in MS; also, to calculate the individual MS risk value useful for health insurance application. Accordingly, among 596 MS patients retrospectively assessed at the time of diagnosis, the value of vitamin D < 10 nm/L, BMI (Body Mass Index) < 15 Kg/m2 and >30 Kg/m2, female sex, degree of family kinship, and the range of age at onset of 20–45 years were considered as biological risk factors for MS. As a result, in a 30-year-old representative patient having a BMI of 15 and second degree of family kinship for MS, the major developmental contributor for disease is the low vitamin D serum level of 10 nm/L, resulting in an MS risk of 0.110 and 0.106 for female and male, respectively. Furthermore, the Choquet integral applied to uncertain variables, such as biological risk factors, evidenced the family kinship as the main contributor, especially if coincident with the others, to the MS risk. This model allows, for the first time, for the risk stratification of getting sick and the application of the health insurance in people at risk for MS. Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
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1 pages, 168 KiB  
Correction
Correction: Ferreira-Sánchez et al. Differences in Motor Imagery Ability between People with Parkinson’s Disease and Healthy Controls, and Its Relationship with Functionality, Independence and Quality of Life. Healthcare 2023, 11, 2898
by María del Rosario Ferreira-Sánchez, Marcos Moreno-Verdú, María de los Ángeles Atín-Arratibel and Patricia Martín-Casas
Healthcare 2024, 12(21), 2129; https://doi.org/10.3390/healthcare12212129 - 25 Oct 2024
Viewed by 325
Abstract
In the original publication [...] Full article
(This article belongs to the Special Issue Prevention, Diagnosis, Treatment and Healthcare for the People with Neurodegenerative Diseases)
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