American journal of Alzheimer's disease and other dementias最新文献

Objective: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment.

Methods: 371 elderly individuals were ultimately included in the ML analysis. Demographic information (including gender, age, parity, visual acuity, auditory function, mobility, and medication history) and 35 features from 10 assessment scales were used for modeling. Five machine learning classifiers were used for evaluation, employing a procedure involving feature extraction, selection, model training, and performance assessment to identify key indicative factors.

Results: The Random Forest model, after data preprocessing, Information Gain, and Meta-analysis, utilized three training features and four meta-features, achieving an area under the curve of 0.961 and a accuracy of 0.894, showcasing exceptional accuracy for the identification of dementia and mild cognitive impairment.

Conclusions: ML serves as a identification tool for dementia and mild cognitive impairment. Using Information Gain and Meta-feature analysis, Clinical Dementia Rating (CDR) and Neuropsychiatric Inventory (NPI) scale information emerged as crucial for training the Random Forest model.

Objectives: Neuropsychological test batteries, which accurately and comprehensively assess cognitive functions, are a crucial approach in the early detection of and interventions for cognitive impairments. However, these tests have yet to gain wide clinical application in China owing to their complexity and time-consuming nature. This study aimed to develop the Computerized Neurocognitive Battery for Chinese-Speaking participants (CNBC), an autorun and autoscoring cognitive assessment tool to provide efficient and accurate cognitive evaluations for Chinese-Speaking individuals.

Methods: The CNBC was developed through collaboration between clinical neurologists and software engineers. Qualified volunteers were recruited to complete CNBC and traditional neurocognitive batteries. The reliability and validity of the CNBC were evaluated by analyzing the correlations between the measurements obtained from the computerized and the paper-based assessment and those between software-based scoring and manual scoring.

Results: The CNBC included 4 subtests and an autorun version. Eighty-six volunteers aged 51-82 years with 7-22 years of education were included. Significant correlations (0.256-0.666) were observed between paired measures associated with attention, executive function, and episodic memory from the CNBC and the traditional paper-based neurocognitive batteries. This suggests a strong construct validity of the CNBC in assessing these cognitive domains. Furthermore, the correlation coefficients between manual scoring and system scoring ranged from 0.904-1.0, indicating excellent inter-rater reliability for the CNBC.

Interpretation: A novel CNBC equipped with automated testing and scoring features was developed in this study. The preliminary results confirm its strong reliability and validity, indicating its promising potential for clinical utilization.

Introduction: To evaluate whether both acute and chronic low-intensity pulsed ultrasound (LIPUS) affect brain functions of healthy male and female mice. Methods: Ultrasound (frequency: 1.5 MHz; pulse: 1.0 kHz; spatial average temporal average (SATA) intensity: 25 mW/cm²; and pulse duty cycle: 20%) was applied at mouse head in acute test for 20 minutes, and in chronic experiment for consecutive 10 days, respectively. Behaviors were then evaluated. Results: Both acute and chronic LIPUS at 25 mW/cm² exposure did not affect the abilities of movements, mating, social interaction, and anxiety-like behaviors in the male and female mice. However, physical restraint caused struggle-like behaviors and short-time memory deficits in chronic LIPUS groups in the male mice. Conclusion: LIPUS at 25 mW/cm² itself does not affect brain functions, while physical restraint for LIPUS therapy elicits struggle-like behaviors in the male mice. An unbound helmet targeted with ultrasound intensity at 25-50 mW/cm² is proposed for clinical brain disease therapy.

Objectives: This study examined the acceptability and usefulness of Positive Behaviour Support (PBS) training in enhancing the capabilities of support staff and family members providing behaviour support to residents with dementia in residential aged care (RAC).

Methods: A mixed-methods pilot study was conducted across 3 RAC organisations, involving pre- and post-training questionnaire assessments for clinical leaders (n = 8), support staff (n = 37) and family members (n = 18).

Results: Findings indicated increased confidence among support staff and family members in providing behaviour support, with 96% indicating it would support their practices across settings. Key training benefits included identifying and addressing underlying causes of challenging behaviours. A majority (89%) expressed the need for further behaviour support training.

Conclusion: Recommendations focus on developing systems to enable effective and collaborative behaviour support practices. Further research is needed to examine application of PBS principles and planning for residents living with dementia.

Several research studies have demonstrated the potential use of cerebrospinal fluid biomarkers such as amyloid beta 1-42, T-tau, and P-tau, in early diagnosis of Alzheimer's disease stages. The levels of these biomarkers in conjunction with the dementia rating scores are used to empirically differentiate the dementia patients from normal controls. In this work, we evaluated the performance of standard machine learning classifiers using cerebrospinal fluid biomarker levels as the features to differentiate dementia patients from normal controls. We employed various types of machine learning models, that includes Discriminant, Logistic Regression, Tree, K-Nearest Neighbor, Support Vector Machine, and Naïve Bayes classifiers. The results demonstrate that these models can distinguish cognitively impaired subjects from normal controls with an accuracy ranging from 64% to 69% and an area under the curve of the receiver operating characteristics between 0.64 and 0.73. In addition, we found that the levels of 2 biomarkers, amyloid beta 1-42 and T-tau, provide a modest improvement in accuracy when distinguishing dementia patients from healthy controls.

Timely diagnosis of young-onset dementia (YOD) is critical. This study aimed to identify factors that increased time to diagnosis at each stage of the diagnostic pathway. Participants were patients diagnosed with YOD (n = 40) and their care partners (n = 39). Information was obtained from questionnaires, and review of medical records. Mean time from symptom onset to YOD diagnosis was 3.6 ± 2 years. Suspicion of depression/anxiety at presentation was associated with significantly increased time from presentation to specialist referral. Neurologist-diagnosed YOD was the fastest route to a diagnosis, whereas diagnoses made by other specialists significantly increased the time from first specialist visit to diagnosis. By investigating multiple stages of the diagnostic pathway, we identified two factors that increased time to diagnosis: suspicion of depression/anxiety at presentation delayed specialist referral from primary care, and diagnosis by a specialist other than a neurologist delayed diagnosis of YOD.

This study investigated a dose-response relationship between Leisure-Time Physical Activity participation (LTPA) and the risk of diabetes and a comparison of the risk across different cognitive function groups among older adults. The Health and Retirement Study data were used from 2012 to 2020 (n = 18 746). This study conducted a Cox Proportional Hazard Regression to investigate the Dose-Response Curve between the prevalence of diabetes and the covariates following a level of LTPA participation. The result presented that the Odds Ratio continuously decreased as the level of LTPA participation increased. Among the three cognitive function groups, the high group (OR = .43, P < .05) and the mid group (OR = .71, P < .05) had a larger negative slope coefficient than the low group. This study found that LTPA participation reduces the risk of diabetes and gives evidence for the importance of cognitive function in reducing the prevalence of diabetes.

Background: Alterations in Heart Rate (HR) and Heart Rate Variability (HRV) reflect autonomic dysfunction associated with neurodegeneration making them biomarkers suitable for detecting Mild Cognitive Impairment (MCI). Methods: The study involves 297 urban Indian participants [48.48% (144) were male and 51.51% (153) were female]. MCI was detected in 19.19% (57) of participants and the rest, 80.8% (240) of them were healthy. ECG recordings spanning 10 s were collected and R-peaks were detected. Machine learning algorithms like were employed to further validate the features. Results: The mean of R-to-R (NN) intervals (P = .0021), the RMS of NN intervals (P = .0014), the SDNN (P = .0192) and the RMSSD (P = .0206) values differ significantly between MCI and non-MCI. Machine learning classifiers, SVM, DA, and NB show a high accuracy of 80.801% on RMS feature input. Conclusion: HR and its variability can be considered potential biomarkers for detecting MCI.

Several risk factors contribute to the development of Alzheimer's disease (AD), including genetics, metabolic health, cardiovascular history, and diet. It has been observed that women appear to face a higher risk of developing AD. Among the various hypotheses surrounding the gender disparity in AD, one pertains to the potential neuroprotective properties of estrogen. Compared to men, women are believed to be more susceptible to neuropathology due to the significant decline in circulating estrogen levels following menopause. Studies have shown, however, that estrogen replacement therapies in post-menopausal women do not consistently reduce the risk of AD. While menopause and estrogen levels are potential factors in the elevated incidence rates of AD among women, this review highlights the possible roles estrogen has in other pathways that may also contribute to the sex disparity observed in AD such as olfaction, sleep, and glymphatic functionality.

Introduction: Multimodal non-pharmacological interventions (MNPI) have been determined as effective in delaying cognitive deterioration. The effectiveness of timing of such interventions in elderly is less discussed. We compared the different effectiveness of MNPI in cognitive preservation in elderly subjects with and without dementia.

Methods: We enrolled volunteer the elderly subjects. Subjects were classified as dementia group and non-dementia group by instrument of ascertainment of dementia 8. All were assigned to attend 3 hours of MNPI (physical fitness training, Chinese capillary, and Chinese drawings and paintings) twice a week over a 16-week period. Neuropsychiatric tests, including Mini-Mental State Examination (MMSE), Cognitive Assessment Screening Instrument (CASI), clinical dementia rating (CDR), and neuropsychiatric inventory (NPI), were administered before and 1 year after MNPI. We demonstrated the changes of cognition and behavioral and psychological symptoms of dementia (BPSD) before and after MNPI. We compared the different effectiveness of cognition preservation between two groups.

Results: In total, there were 43 participants in our study, including 18 with non-dementia and 25 with dementia. The non-dementia group had a significantly higher proportion of cognitive preservation in remote memory (100.0% vs 68.0%, P = .007), orientation (94.4% vs 48.0%, P = .001), drawing (94.4% vs 64.0%, P = .021) and language (77.8% vs 48.0%, P = .049) than the dementia group. The highest proportion of preserved cognition after MNPI was remote memory (100%), followed by orientation (94.4%) and drawing (94.4%) in the non-dementia group. The highest proportion of preserved cognition after MNPI was attention (72%) followed by remote memory (68%), recent memory (64%) and drawing (64%) in the dementia group. Overall, their improved rate in behavioral and psychological symptoms was 55.6%.

Conclusion: Our study concluded the benefits of early MNPI in cognition preservation in the elderly, especially in the field of remote memory, orientation, drawing and language.