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AlHarkan K, Sultana N, Al Mulhim N, AlAbdulKader AM, Alsafwani N, Barnawi M, Alasqah K, Bazuhair A, Alhalwah Z, Bokhamseen D, Aljameel SS, Alamri S, Alqurashi Y, Ghamdi KA. Artificial intelligence approaches for early detection of neurocognitive disorders among older adults. Front Comput Neurosci 2024; 18:1307305. [PMID: 38444404 PMCID: PMC10913197 DOI: 10.3389/fncom.2024.1307305] [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: 10/04/2023] [Accepted: 01/29/2024] [Indexed: 03/07/2024] Open
Abstract
Introduction Dementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately. Methods Quantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient's cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients' cognitive function based on gender and developed the predicting models for males and females separately. Results Fifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time. Conclusion The results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.
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Affiliation(s)
- Khalid AlHarkan
- Department of Family and Community Medicine, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Nahid Sultana
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Noura Al Mulhim
- Department of Physiology, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Assim M. AlAbdulKader
- Department of Family and Community Medicine, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Noor Alsafwani
- Department of Pathology, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Marwah Barnawi
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Khulud Alasqah
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Anhar Bazuhair
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Zainab Alhalwah
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Dina Bokhamseen
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Sumayh S. Aljameel
- Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Sultan Alamri
- Department of Family Medicine, College of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Yousef Alqurashi
- Respiratory Care Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Kholoud Al Ghamdi
- Department of Physiology, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
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Wang M, Wang Y, Wang Z, Ren Q. The Abnormal Alternations of Brain Imaging in Patients with Chronic Obstructive Pulmonary Disease: A Systematic Review. J Alzheimers Dis Rep 2023; 7:901-919. [PMID: 37662615 PMCID: PMC10473125 DOI: 10.3233/adr-220083] [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: 10/12/2022] [Accepted: 07/11/2023] [Indexed: 09/05/2023] Open
Abstract
Background Cognitive impairment (CI) is an important extrapulmonary complication in patients with chronic obstructive pulmonary disease (COPD). Multimodal Neuroimaging Examination can display changes in brain structure and functions in patients with COPD. Objective The purpose of this systematic review is to provide an overview of the variations in brain imaging in patients with COPD and their potential relationship with CI. Furthermore, we aim to provide new ideas and directions for future research. Methods Literature searches were performed using the electronic databases PubMed, Scopus, and ScienceDirect. All articles published between January 2000 and November 2021 that met the eligibility criteria were included. Results Twenty of the 23 studies focused on changes in brain structure and function. Alterations in the brain's macrostructure are manifested in the bilateral frontal lobe, hippocampus, right temporal lobe, motor cortex, and supplementary motor area. The white matter microstructural changes initially appear in the bilateral frontal subcortical region. Regarding brain function, patients with COPD exhibited reduced frontal cerebral perfusion and abnormal alterations in intrinsic brain activity in the bilateral posterior cingulate cortex, precuneus, right lingual gyrus, and left anterior central gyrus. Currently, there is limited research related to brain networks. Conclusion CI in patients with COPD may present as a type of dementia different from Alzheimer's disease, which tends to manifest as frontal cognitive decline early in the disease. Further studies are required to clarify the neurobiological pathways of CI in patients with COPD from the perspective of brain connectomics based on the whole-brain system in the future.
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Affiliation(s)
- Mengxue Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Yanjuan Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Qingguo Ren
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
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Ahmadi M, Kazemi-Arpanahi H, Nopour R, Shanbehzadeh M. Factors influencing quality of life among the elderly: An approach using logistic regression. JOURNAL OF EDUCATION AND HEALTH PROMOTION 2023; 12:215. [PMID: 37545996 PMCID: PMC10402806 DOI: 10.4103/jehp.jehp_13_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/20/2023] [Indexed: 08/08/2023]
Abstract
BACKGROUND Improving the physical, psychological, and social factors in the elderly significantly increases the QoL1 among them. This study aims to identify the crucial factors for predicting QoL among the elderly using statistical methods. MATERIALS AND METHODS In this study, 980 samples related to the elderly with favorable and unfavorable QoL were investigated. The elderly's QoL was investigated using a qualitative and self-assessment questionnaire that measured the QoL among them by five Likert spectrum and independent factors. The Chi-square test and eta coefficient were used to determine the relationship between each predicting factor of the elderly's QoL in SPSS V 25 software. Finally, we used the Enter and Forward LR methods to determine the correlation of influential factors in the presence of other variables. RESULTS The study showed that 20 variables gained a significant relationship with the quality of life of the elderly at P < 0.05. The study results showed that the degree of dependence (P = 0.03), diabetes mellitus (P = 0.03), formal and informal social relationships (P = 0.01 and P = 0.02), ability to play an emotional role (P = 0.03), physical performance (P = 0.01), heart diseases and arterial blood pressure (P = 0.02), and cancer (P = 0.01) have favorable predictive power in predicting the QoL among the elderly. CONCLUSION Attempts to identify and modify the important factors affecting the elderly's QoL have a significant role in improving the QoL and life satisfaction in this age group people. This study showed that the statistical methods have a pleasant capability to discover the factors associated with the elderly's QoL with high performance in this regard.
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Affiliation(s)
- Maryam Ahmadi
- Ph.D. of Health Information Management, Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Hadi Kazemi-Arpanahi
- Ph.D. of Health Information Management, Department of Health Information Technology, Abadan University of Medical Sciences, Abadan, Iran
| | - Raoof Nopour
- Ph.D. Student of Health Information Management, Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Mostafa Shanbehzadeh
- Ph.D. of Health Information Management, Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran
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Compagne C, Gabriel D, Ferrero L, Magnin E, Tannou T. Tools for the Assessment of Risk-Taking Behavior in Older Adults with Mild Dementia: A Cross-Sectional Clinical Study. Brain Sci 2023; 13:967. [PMID: 37371445 DOI: 10.3390/brainsci13060967] [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: 05/25/2023] [Revised: 06/08/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
Diseases such as Alzheimer's cause an alteration of cognitive functions, which can lead to increased daily risk-taking in older adults living at home. The assessment of decision-making abilities is primarily based on clinicians' global analysis. Usual neuropsychological tests such as the MoCA (Montreal Cognitive Assessment) cover most of the cognitive domains and include mental flexibility tasks. Specific behavioral tasks for risk-taking, such as the Balloon Analogue Risk Task (BART) or the Iowa Gambling Task (IGT), have been developed to assess risk-taking behavior, particularly in the field of addictology. Our cross-sectional study aims to determine whether the MoCA global cognitive assessment could be used as a substitute for behavioral tasks in the assessment of risky behavior. In the current study, 24 patients (age: 82.1 ± 5.9) diagnosed with mild dementia completed the cognitive assessment (MoCA and executive function assessment) and two behavioral risk-taking tasks (BART, simplified version of the IGT). Results revealed no relationship between scores obtained in the MoCA and behavioral decision-making tasks. However, the two tasks assessing risk-taking behavior resulted in concordant risk profiles. In addition, patients with a high risk-taking behavior profile on the BART had better Trail Making Test (TMT) scores and thus retained mental flexibility. These findings suggest that MoCA scores are not representative of risk-taking behavioral inclinations. Thus, additional clinical tests should be used to assess risk-taking behavior in geriatric settings. Executive function measures, such as the TMT, and behavioral laboratory measures, such as the BART, are recommended for this purpose.
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Affiliation(s)
- Charline Compagne
- UR LINC, Université de Franche-Comté, 25 000 Besançon, France
- CIC-1431 INSERM, Centre Hospitalier Universitaire, 25 000 Besançon, France
| | - Damien Gabriel
- UR LINC, Université de Franche-Comté, 25 000 Besançon, France
- CIC-1431 INSERM, Centre Hospitalier Universitaire, 25 000 Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle Neuraxess, 25 000 Besançon, France
| | - Lénaïc Ferrero
- CIC-1431 INSERM, Centre Hospitalier Universitaire, 25 000 Besançon, France
| | - Eloi Magnin
- UR LINC, Université de Franche-Comté, 25 000 Besançon, France
- CHU Département de Neurologie, Centre Hospitalier Universitaire, 25 000 Besançon, France
| | - Thomas Tannou
- UR LINC, Université de Franche-Comté, 25 000 Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle Neuraxess, 25 000 Besançon, France
- CIUSS Centre-Sud de l'Ile-de-Montréal, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, QC H3W 1W5, Canada
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Yang F, Fu M, Hu Q, Guo J. The associations between cognitive function and depressive symptoms among older Chinese population: A cohort study. Front Psychiatry 2023; 14:1081209. [PMID: 37091713 PMCID: PMC10117645 DOI: 10.3389/fpsyt.2023.1081209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 03/14/2023] [Indexed: 04/25/2023] Open
Abstract
With the rapid development of society, population aging has emerged as a significant global challenge. This study aimed to evaluate the impact of baseline cognitive performance, current cognitive function, and cognitive decline on subsequent depressive symptoms. Data were obtained from participants aged 65 years and older in the Chinese Longitudinal Healthy Longevity Survey (CLHLS), Wave 2014-2018. Of the 7,192 participants in Wave 2014, 1,627 were included in the analysis. Multivariate regressions were conducted to estimate the associations between cognitive measures and depressive symptoms. Our results indicated that baseline cognitive function was not associated with subsequent depressive symptoms, but current cognitive function was. Furthermore, participants who experienced significant cognitive decline were more likely to develop depressive symptoms. Covariates, including marital status, economic status, physical activity, and recreational activity, were also associated with subsequent depressive symptoms. These findings suggest that slowing cognitive decline is an effective strategy for preventing depressive symptoms in older adults, promoting their health and wellbeing.
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Affiliation(s)
- Fan Yang
- Department of Health Policy and Management, School of Public Health, Peking University Health Science Center, Beijing, China
- Center for Health Policy and Technology Evaluation, Peking University Health Science Center, Beijing, China
| | - Mingqi Fu
- Center for Social Security Studies, Wuhan University, Wuhan, China
| | - Qitu Hu
- College of Humanities Education, Inner Mongolia Medical University, Hohhot, China
- *Correspondence: Qitu Hu,
| | - Jing Guo
- Department of Health Policy and Management, School of Public Health, Peking University Health Science Center, Beijing, China
- Center for Health Policy and Technology Evaluation, Peking University Health Science Center, Beijing, China
- Jing Guo,
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Felício LFF, Leão LL, Souza EHEE, Machado FSM, Laks J, Deslandes AC, Paula AMBD, Monteiro-Junior RS. Cognitive abilities of institutionalized older persons with depressive symptoms. JORNAL BRASILEIRO DE PSIQUIATRIA 2022. [DOI: 10.1590/0047-2085000000383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
ABSTRACT Objective To determine the level of association between depressive symptoms and cognitive abilities of institutionalized older adults. Methods This is a cross-sectional study that enrolled 69 older adults, living in a long-term care facility. Investigation of depressive symptoms in all individuals was performed using the geriatric depression scale. Cognitive verbal fluency, digit span forward (DSF) and backward (DSB) tests, and two-minute stationary gait, sit-to-stand test, and six-minute walk test were performed to assess their association with depressive symptoms. Results Depressive symptoms were identified in 35 individuals. Worse cognition and physical performances were associated with the presence of depressive symptoms – Mini-Mental State Examination [t (61) = 2.36; p < 0.05] and Stationary gait test of two minutes [t (53) = 3.12; p < 0.05]. Short-term memory and working memory tests presented worse results in individuals with depressive symptoms (DSF: U = 402.00; p < 0.05 e DSB: U = 341,00; p < 0.05). Older adults with scores below normal in DSF were 5 times more likely to exhibit depressive symptoms. Conclusion The importance of physical, cognitive and social intervention strategies in long-term care facilities for the older adults is highlighted, in order to privilege autonomy. Notably, there is an association between deficits in short-term memory and the presence of depressive symptoms in older adults. Therefore, prospective studies are suggested to investigate the cause-effect relationship of this association with the institutionalization of older adults.
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Affiliation(s)
| | | | | | | | - Jerson Laks
- Federal University of Rio de Janeiro, Brazil
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