Treatment Of Mild Cognitive Impairment Research Articles

IPECAD Modeling Workshop 2023 Cross Comparison Challenge on Cost-Effectiveness Models in Alzheimer’s Disease

Decision-analytic models assessing the value of emerging Alzheimer's disease (AD) treatments are challenged by limited evidence on short-term trial outcomes and uncertainty in extrapolating long-term patient-relevant outcomes. To improve understanding and foster transparency and credibility in modeling methods, we cross-compared AD decision models in a hypothetical context of disease-modifying treatment for mild cognitive impairment (MCI) due to AD. A benchmark scenario (US setting) was used with target population MCI due to AD and a set of synthetically generated hypothetical trial efficacy estimates. Treatment costs were excluded. Model predictions (10-year horizon) were assessed and discussed during a 2-day workshop. Nine modeling groups provided model predictions. Implementation of treatment effectiveness varied across models based on trial efficacy outcome selection (CDR-SB, CDR-global, MMSE, FAQ) and analysis method (observed severity transitions, change from baseline, progression hazard ratio, or calibration to these). Predicted mean time in MCI ranged from 2.6-5.2 years for control strategy, and from 0.1-1.0 years for difference between intervention and control strategies. Predicted quality-adjusted life-year gains ranged from 0.0-0.6 and incremental costs (excluding treatment costs) from -US$66,897 to US$11,896. Trial data can be implemented in different ways across health-economic models leading to large variation in model predictions. We recommend 1) addressing the choice of outcome measure and treatment effectiveness assumptions in sensitivity analysis, 2) a standardized reporting table for model predictions, and 3) exploring the use of registries for future AD treatments measuring long-term disease progression to reduce uncertainty of extrapolating short-term trial results by health economic models.

Global trends and hotspots of exercise interventions for mild cognitive impairment: A global bibliometric analysis.

Exercise interventions for mild cognitive impairment (MCI) have been extensively studied. However, there is no bibliometric study on exercise interventions for MCI. This study aimed to identify the collaborative networks, research hotspots, evolution trends, and future directions. Relevant documents were retrieved from the Web of Science Core Collection database. VOSviewer was used to analyze the co-authorship of the author, countries and institutions, and the keywords co-occurrence. CiteSpace was used to detect burst keywords' research trends. A total of 569 articles were included and showed an overall increasing trend in annual publications. The most influential subject categories, authors, journals, country, and institutions were "geriatrics gerontology," "Doi, Takehiko and Shimada, Hiroyuki," "Journal of Alzheimer's Disease," USA, and "Veterans Health Administration," respectively. The research hotspots are "effectiveness," "neural mechanism" and "correlation" of exercise interventions, and the emerging trend is "intervention quality." This area is in a rapid development phase, whereby research hotpots are focused and the research trend is clear. The highly productive authors and institutions have made outstanding contributions and the subject categories present an interdisciplinary trend. However, there is weak cooperation between countries and institutions, and a substantial research gap exists between developed and developing countries. Future research may highlight the intervention quality, emphasizing the combination with virtual reality technology.

A - 10 Selective Serotonin Reuptake Inhibitors Do Not Alter HD-tDCS Effects on Episodic Memory in Cognitively Impaired Older Adults

Abstract Objective High-Definition Transcranial Direct Current Stimulation (HD-tDCS) is a potential new intervention for mild cognitive impairment (MCI) and Alzheimer’s Dementia (ad) involving small doses of electrical stimulation. Prior studies suggest potential interactions with Selective Serotonin Reuptake Inhibitors (SSRIs) that could alter HD-tDCS’s effectiveness on cognitive outcomes. This study evaluated if SSRIs altered HD-tDCS response to episodic memory functioning in individuals with MCI and ad. Method Eighteen individuals (M age = 70.5; 27.8% female; 8 stable on SSRIs), 9 with MCI and 9 with ad, underwent ten 20-minute HD-tDCS sessions of 1 milliampere over the medial frontal cortex. Neuropsychological testing assessed learning and delayed recall for visual (Brief Visuospatial Memory Test-Revised) and verbal (Rey Auditory Verbal Learning Test or Hopkins Verbal Learning Test-Revised) episodic memory at baseline and immediately post-treatment. Linear regressions evaluated SSRI use as a predictor of post-treatment episodic memory performance controlling for baseline scores. Results Ten participants demonstrated improvement on at least one measure by 0.5 standard deviation (SD; 5 T-score points), with 5 showing 1 SD improvement. Eleven showed a decline by 0.5 SD on at least one measure, with 7 showing 1 SD decline. SSRI use did not significantly predict better or worse verbal learning (β = −4.285, p = 0.194), verbal delayed recall (β-0.408, p = 0.883), visual learning (β = −2.788, p = 0.405), and visual delayed recall (β = −6.673, p = 0.150) performance post-HD-tDCS. Conclusion Preliminary findings suggest SSRIs may not impact HD-tDCS outcomes in cognitively impaired older adults, specifically for episodic memory. These results may not translate to other neuropsychological domains; however, larger samples are needed for further investigation.

2248 Clinical relevance of Donanemab treatment

Abstract Objective To assess in Alzheimer’s disease (ad), the treatment impact of donanemab, an amyloid plaque-reducing monoclonal antibody, on readily interpretable item-measures and constructs that matter to patients, care-partners, and clinicians. Background Positive outcomes were reported from TRAILBLAZER-ALZ2, a randomised, double-blind, placebo-controlled, 18-month, phase 3 study evaluating donanemab as an investigational treatment for mild cognitive impairment (MCI) or mild dementia due to ad. In 1736 participants, donanemab significantly slowed the rate of clinical decline (by 22–36%) as measured by the integrated ad Rating Scale (iADRS) and the Clinical Dementia Rating Scale—Sum-of-Boxes (CDR-SB); both measures of cognition and function as indications of global clinical severity. In these subsequent post-hoc exploratory analyses, the impact of donanemab treatment on individual iADRS cognition and function items, CDR domains, and risks of advancing to greater disease severity were assessed. Methods Mixed model repeated measures and Cox proportional hazard modelling methodology assessed treatment effects on iADRS items and CDR domains. Results Donanemab treatment was associated with significant beneficial effects on: 1) iADRS cognitive items related to episodic memory and executive function, and instrumental activities of daily living items related to communication and others (e.g. being left alone, making a meal, using household appliances); 2) all CDR-SB cognitive and functional domains (i.e. memory, orientation, judgement/problem solving, community affairs, home/hobbies, and personal care); and 3) lowering risk of progression to a more advanced clinical stage of disease. Conclusions These analyses explored the impact of donanemab treatment on constructs that matter to and are considered more readily interpretable by patients, care-partners, and clinicians. These results provide further support that treating those with MCI or mild dementia due to ad with donanemab can meaningfully reduce risk of progression to more severe clinical stages (e.g. moderate stage dementia), and potentially allow greater independence for a longer period of time.

Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning

Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable devices collecting physiological and behavioral data can help in remote, passive, and continuous monitoring of moods and NPS, overcoming limitations and inconveniences of current assessment methods. In this longitudinal study, we examined the predictive ability of digital biomarkers based on sensor data from a wrist-worn wearable to determine the severity of NPS and mood disorders on a daily basis in older adults with predominant MCI. In addition to conventional physiological biomarkers, such as heart rate variability and skin conductance levels, we leveraged deep-learning features derived from physiological data using a self-supervised convolutional autoencoder. Models combining common digital biomarkers and deep features predicted depression severity scores with a correlation of r = 0.73 on average, total severity of mood disorder symptoms with r = 0.67, and mild behavioral impairment scores with r = 0.69 in the study population. Our findings demonstrated the potential of physiological biomarkers collected from wearables and deep learning methods to be used for the continuous and unobtrusive assessments of mental health symptoms in older adults, including those with MCI. Trial registrationThis trial was registered with ClinicalTrials.gov (NCT05059353) on September 28, 2021, titled “Effectiveness and Safety of a Digitally Based Multidomain Intervention for Mild Cognitive Impairment”.

VR rehabilitation system evaluator: A fNIRS-based and LLM-enabled evaluation paradigm for Mild Cognitive Impairment

Virtual Reality (VR) has significant potential for Mild Cognitive Impairment (MCI) rehabilitation by offering dynamic and engaging tasks designed to stimulate various cognitive domains. However, how efficiently evaluating the VR tasks is always challenging. The current effectiveness evaluation methods for task evaluation and optimisation typically rely on post-training metrics like game performance or subjective questionnaires, which cannot directly reflect the comprehensiveness and intensity of cognitive stimulation. To bridge these gaps, we propose a novel approach integrating functional near-infrared spectroscopy (fNIRS) data and a Large Language Model (LLM) for VR rehabilitation task evaluation and optimisation. Firstly, we leverage fundamental cognitive theories to propose a systematic evaluation paradigm for assessing the scope of the cognitive domains stimulated by VR tasks. Secondly, we propose fNIRS-derived graph parameters to objectively evaluate the cognitive stimulation with high-time resolution. Finally, we develop a prompt-generating strategy to facilitate Large Language Model (LLM)-based analysis, which transforms fNIRS-derived metrics combined with the scope of stimulated cognitive domains into easy-to-understand evaluation reports and actionable recommendations for task optimisation. We demonstrate this approach with two VR rehabilitation tasks. Several experts evaluated the LLM-based task evaluation results and task optimisation recommendation and agreed that the LLM-generated results are meaningful and applicable. This approach offers a rapid, objective method to evaluate VR task effectiveness and improves their design, marking a significant step in developing more effective MCI interventions.

Efficacy of Nonpharmacological Interventions in Cognitive Impairment: Systematic Review And Network Meta-Analysis

There is currently no known cure for cognitive impairment, which highlights the need to explore other ways of managing this condition. This topic has recently become an area of active research. However, the availability of nonpharmacological options poses a challenge when trying to determine the best treatment for improving cognitive function. We conducted a systematic review and a Bayesian network meta-analysis to compare the effects of nonpharmacological interventions on global cognition in patients with mild cognitive impairment and dementia. The nonpharmacological interventions were classified as aerobic exercise, strength exercise, multicomponent physical exercise, other physical exercises, tai chi, mind-body exercises, traditional cognitive rehabilitation, computer-based cognitive rehabilitation, occupational therapy, music therapy, physical-cognitive rehabilitation, and reminiscence therapy. Physical-cognitive rehabilitation emerged as the most effective nonpharmacological intervention for enhancing global cognition in patients with unspecified cognitive impairment and dementia, whereas occupational therapy focused on dual-task interventions was found to be the most effective nonpharmacological intervention for mild cognitive impairment. These results underscore the importance of adopting a dual approach to managing cognitive impairment, integrating both cognitive and physical rehabilitation within the same intervention.

Performance of Plasma Biomarkers Combined with Structural MRI to Identify Candidate Participants for Alzheimer’s Disease-Modifying Therapy

BackgroundRecently, two monoclonal antibodies that lower amyloid plaques have shown promising results for the treatment of Mild Cognitive Impairment (MCI) and mild dementia due to Alzheimer’s disease (AD). These treatments require the identification of cognitively impaired older adults with biomarker evidence of AD pathology using CSF biomarkers or amyloid-PET. Previous studies showed plasma biomarkers (plasma Aβ42/Aβ40 and p-tau181) and hippocampal volume from structural MRI correlated with brain amyloid pathology. We hypothesized plasma biomarkers with hippocampal volume would identify patients who are suitable candidates for disease-modifying therapy.ObjectivesTo evaluate the performance of plasma AD biomarkers and hippocampal atrophy to detect MCI or AD with amyloid pathology confirmed by amyloid-PET or CSF biomarkers in ADNI.DesignA cross-sectional and longitudinal study.Setting and ParticipantsData were from the Alzheimer’s Disease Neuroimaging Initiative. Participants were aged 55–90 years old with plasma biomarker and structural MRI brain data.MeasurementsThe optimum cut-off point for plasma Aβ42/Aβ40, p-tau181, and NFL and the performance of combined biomarkers and hippocampal atrophy for detecting cognitive impairment with brain amyloid pathology were evaluated. The association between baseline plasma biomarkers and clinical progression, defined by CDR-Sum of Boxes (CDR-SB) and diagnostic conversion over two years, was evaluated using a Weibull time-to-event analysis.ResultsA total of 428 participants were included; 167 had normal cognition, 245 had MCI, and 16 had mild AD. Among MCI and AD, 140 participants had elevated amyloid levels by PET or CSF. Plasma Aβ42/Aβ40 provided the best accuracy (sensitivity 79%, specificity 66%, AUC 0.73, 95% CI 0.68–0.77) to detect drug candidate participants at baseline. Combined plasma Aβ42/40, p-tau181, and hippocampal atrophy increased the specificity for diagnosis (96%), but had lower sensitivity (34%), and AUC (0.65). Hippocampal atrophy combined with the abnormal plasma p-tau181 or hippocampal atrophy alone showed high sensitivity to detect clinical progression (by CDR-SB worsening) of the drug-candidate participants within the next 2 years (sensitivity 93% and 89%, respectively).ConclusionPlasma biomarkers and structural MRI can help identify patients who are currently eligible for anti-amyloid treatment and are likely to progress clinically, in cases where amyloid-PET or CSF biomarkers are not available.

Summary of the effect of an exercise intervention on elderly with mild cognitive impairment: A systematic review and meta-analysis.

Many randomized controlled trials have demonstrated that exercise benefits cognitive function in patients with mild cognitive impairment (MCI), but less attention has been paid to the development of exercise programs in this population. This study aimed to assess the effect of exercise intervention for elderly with MCI and provide the most effective exercise intervention plan. We searched 4 international databases (PubMed, EMBASE, Web of Science, Cochrane Library) and 4 Chinese databases (Chinese National Knowledge Infrastructure, VIP database and Wanfang database) for studies on exercises associated with MCI up to September 25, 2022. The resulting standardized mean differences (SMD) and 95% confidence intervals were statistically analyzed using Review Manager 5.3 software. A total of 20 RCTs were comprised in this meta-analysis, including 1393 participants. The results of the meta-analysis revealed that exercise had positive effects on cognitive function in elderly with MCI and was statistically significant (SMD = 1.25, 95%CI: [0.88,1.62], P < .00001). Subgroup analysis showed that the most significant factor was the Peterson 2004 criteria, multi-exercise, 35 to 50 minutes/times, <3 times/3 to 5 times per week, >16 weeks and medium intensity. Exercise intervention can significantly alleviate cognition in elderly with MCI. The best exercise program for exercise intervention for MCI is: multi-exercise, 35 to 50 minutes/times, 3 to 5 times/week, and exercise cycle for more than 16 weeks with medium intensity, has the best effect. Plus, more RCTs with larger sample sizes will be required in the future to demonstrate the link between exercise duration, intensity, and cognitive function.

ChatGPT and BCI-VR: a new integrated diagnostic and therapeutic perspective for the accurate diagnosis and personalized treatment of mild cognitive impairment.

ChatGPT and BCI-VR: a new integrated diagnostic and therapeutic perspective for the accurate diagnosis and personalized treatment of mild cognitive impairment.

Go4cognition: Evaluation of a Newly Developed Multicomponent Intervention in Mild Cognitive Impairment.

Cognitive training and physical exercise show positive effects on cognitive decline in subjects with mild cognitive impairment (MCI). Multimodal interventions for MCI patients, combining physical and cognitive training in a social context seem to slow down cognitive decline. Based on a previous study, a new mobile gamification tool (go4cognition; https://www.ontaris.de/go4cognition) has been developed to train cognitive and physical functions simultaneously in a group setting. It involves tasks targeting various cognitive functions (short-term memory, working memory, executive functions). The computer-based setup allows for individual performance analysis. This study evaluated the effects of this tool. 30 participants with MCI, as defined by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) cut-off-score, aged between 66 and 89 years, trained for one hour two days a week for twelve weeks. Additionally, standard neuropsychological assessment of memory and attention was carried out before and after the intervention. The go4cognition device is highly effective in improving various cognitive functions. A significant improvement in the CERAD total score resulting in re-classification of 70% of former MCI patients into non-MCI patients was found. Additionally, an improvement of verbal fluency, verbal memory, spatial memory, and attention was observed. Furthermore, the CERAD total score was significantly correlated with performance in the go4cognition tool. The results of the intervention support the idea of the effectiveness of a combined cognitive and motor intervention by incorporating neuropsychological paradigms in a group setting and suggest a close relation between combined cognitive and physical exercise and cognitive performance.

A study of cognitive impairment quantitative assessment method based on gait characteristics

Alzheimer's disease (AD) is a common and serious form of elderly dementia, but early detection and treatment of mild cognitive impairment can help slow down the progression of dementia. Recent studies have shown that there is a relationship between overall cognitive function and motor function and gait abnormalities. We recruited 302 cases from the Rehabilitation Hospital Affiliated to National Rehabilitation Aids Research Center and included 193 of them according to the screening criteria, including 137 patients with MCI and 56 healthy controls (HC). The gait parameters of the participants were collected during performing single-task (free walking) and dual-task (counting backwards from 100) using a wearable device. By taking gait parameters such as gait cycle, kinematics parameters, time-space parameters as the focus of the study, using recursive feature elimination (RFE) to select important features, and taking the subject's MoCA score as the response variable, a machine learning model based on quantitative evaluation of cognitive level of gait features was established. The results showed that temporal and spatial parameters of toe-off and heel strike had important clinical significance as markers to evaluate cognitive level, indicating important clinical application value in preventing or delaying the occurrence of AD in the future.

Effectiveness of Tai Chi as a non-invasive intervention for mild cognitive impairment in the elderly: A comprehensive review and meta-analysis.

The aging population warrants the increase of mild cognitive impairment (MCI) prevalence, a condition that could progress to dementia. Efforts have been made to improve the MCI and prevent its progression, including the introduction of Tai Chi, a Chinese traditional exercise. The aim of this systematic review and meta-analysis was to evaluate the efficacy of Tai Chi in attenuating MCI among the elderly population. Records investigating the effect of Tai Chi exercise intervention on cognitive function among elderly patients were searched systematically from PubMed, ScienceDirect, Google Scholar, and Europe PMC as of April 13, 2023. The risk of bias (RoB 2.0) quality assessment was employed in the quality appraisal of the studies included. Review Manager 5.4.1 was used for data extraction and meta-analysis, where the standard mean difference (SMD) and 95% confidence interval (95%CI) were computed. Eight randomized control trials with a total of 1379 participants were included in this meta-analysis. Six trials assessed Montreal Cognitive Assessment scores, where its pooled analysis suggested that Tai Chi was as effective as conventional exercise (SMD=0.15, 95%CI: -0.11 to 0.40, p=0.26). However, pooled analysis of the Mini-Mental Status Examination suggested that Tai Chi intervention more effectively improved cognitive function and reduced the rate of cognitive impairment in elderly patients (SMD=0.36, 95%CI: 0.18 to 0.54, p<0.01) as compared to the control group. This systematic review and meta-analysis suggest that, in some extent, Tai Chi is efficacious in improving cognitive function and slowing down the rate of cognitive impairment among elderly patients.

Cost-Effectiveness of Lecanemab for Individuals With Early-Stage Alzheimer Disease.

Little is known regarding the cost-effectiveness of lecanemab (Leqembi), a monoclonal antibody approved by the US Food and Drug Administration in January 2023 for the treatment of mild cognitive impairment (MCI) or mild dementia due to Alzheimer disease (AD). This study aims to quantify the cost-effectiveness of lecanemab and how it varies based on the accuracy of AD testing and individuals' APOE ε4 status. Seven alternative test-treat-target strategies defined by combinations of testing approaches (PET, CSF, or plasma assay), treatment choices (standard of care [SoC] alone or lecanemab in addition to SoC), and targeting strategies (targeting APOE ε4 noncarriers or heterozygous patients or not) were compared. A hybrid decision tree-Markov cohort model was constructed with 5 states: (1) MCI (Clinical Dementia Rating-Sum of Boxes [CDR-SB] 0-4.5); (2) mild dementia (CDR-SB 4.6-9.5); (3) moderate dementia (CDR-SB 9.6-16); (4) severe dementia (CDR-SB >16); and (5) death. Effectiveness was measured by quality-adjusted life years and costs from third-party and societal perspectives were estimated in 2022 US dollars over a lifetime horizon. Among the 7 test-treat-target strategies, SoC alone was the optimal strategy from a cost-effectiveness perspective. Neither targeted lecanemab treatment nor treatment unrestricted by APOE ε4 genotype was cost-effective vs SoC alone, regardless of the test used to diagnose patients with early-stage AD. However, CSF assay followed by targeted treatment would become cost-effective if lecanemab is priced below $5,100 per year. These results were robust to the accuracy of diagnostic testing and rates of lecanemab discontinuation and adverse events. Neither targeted lecanemab treatment nor treatment unrestricted by APOE ε4 genotype is cost-effective vs SoC alone for patients with MCI or mild dementia due to AD. Lecanemab would be cost-effective in some settings if priced below $5,100 per year.

Improvements in performance based measures of functional capacity and cognition after computerized functional skills training in older people with mild cognitive impairment and healthy comparators

With no pharmacological treatments for Mild Cognitive impairment (MCI), computerized training strategies have been attempted. A computerized skills training intervention, FUNSAT, previously produced training-related gains in cognition in MCI and in comparators with normal cognition (NC). A new remotely delivered version of FUNSAT was administered to a new sample of participants with NC and MCI. Outcomes measures included cognition (BAC) and functional capacity (VRFCAT) to examine training transfer. Participants with MCI (n = 92) and NC (n = 72) trained for up to 12 weeks on FUNSAT. Half the MCI participants started with 3 weeks of computerized cognitive training (CCT). Baseline, post-training, and 30-day follow-up scores on cognition and functional capacity were compared. Participants improved on both cognition (d = 0.80) and functional capacity (d = 0.64), with no differences in training gains across MCI and NC, although treatment with CCT in MCI was associated with similar gains with fewer FUNSAT training sessions. This is the first treatment study in MCI to demonstrate transfer to untrained measures of functional capacity. NC improved in cognition and functional capacity with skills training alone. These findings have implications for other conditions, such as schizophrenia, where functional capacity is a treatment target.

Identification of amnestic mild cognitive impairment by structural and functional MRI using a machine-learning approach

ObjectiveThe importance of early treatment for mild cognitive impairment (MCI) has been extensively shown. However, classifying patients presenting with memory complaints in clinical practice as having MCI vs normal results is difficult. Herein, we assessed the feasibility of applying a machine learning approach based on structural volumes and functional connectomic profiles to classify the cognitive levels of cognitively unimpaired (CU) and amnestic MCI (aMCI) groups. We further applied the same method to distinguish aMCI patients with a single memory impairment from those with multiple memory impairments. MethodsFifty patients with aMCI were enrolled and classified as having either verbal or visual-aMCI (verbal or visual memory impairment), or both aMCI (verbal and visual memory impairments) based on memory test results. In addition, 26 CU patients were enrolled in the control group. All patients underwent structural T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. We obtained structural volumes and functional connectomic profiles from structural and functional MRI, respectively, using graph theory. A support vector machine (SVM) algorithm was employed, and k-fold cross-validation was performed to discriminate between groups. ResultsThe SVM classifier based on structural volumes revealed an accuracy of 88.9% at classifying the cognitive levels of patients with CU and aMCI. However, when the structural volumes and functional connectomic profiles were combined, the accuracy increased to 92.9%. In the classification of verbal or visual-aMCI (n = 22) versus both aMCI (n = 28), the SVM classifier based on structural volumes revealed a low accuracy of 36.7%. However, when the structural volumes and functional connectomic profiles were combined, the accuracy increased to 53.1%. ConclusionStructural volumes and functional connectomic profiles obtained using a machine learning approach can be used to classify cognitive levels to distinguish between aMCI and CU patients. In addition, combining the functional connectomic profiles with structural volumes results in a better classification performance than the use of structural volumes alone for identifying both “aMCI versus CU” and “verbal- or visual-aMCI versus both aMCI” patients.

Development of a digital multidomain lifestyle intervention for mild cognitive impairment: A pilot study on the feasibility and efficacy of cognitive training.

The heterogeneous etiology of mild cognitive impairment (MCI) presents significant challenges in monitoring its progression and impeding its advancement toward dementia. Digital multidomain lifestyle interventions have shown promise as potential solutions for their ability to treat MCI. This study is the first phase in a series of evaluations aimed at assessing various components of Silvia-Rx, which was originally designed as a digital multidomain lifestyle intervention. Specifically, this study focused on a 60-session core cognitive training program to evaluate its feasibility and efficacy in addressing cognitive decline in individuals with MCI. Individuals aged 60 to 80 years diagnosed with MCI were enrolled to participate in a 60-session tablet-based cognitive regimen of Silvia-Rx. Feasibility was assessed through adherence and retention rates, while the Alzheimer's Disease Assessment Scale-Cognitive (ADAS-cog) scale was utilized to measure cognitive function as the primary indicator of efficacy. The mean age of the participants was 71.11 years, and 13 (68.42%) were women. Only one withdrawal occurred, resulting in a 95% retention rate (19 participants) post-intervention. The completion rate was excellent at 100%, indicating that the 60-session core cognitive program in Silvia-Rx was well tolerated by older participants with MCI. Regarding efficacy, there was a statistically significant improvement in cognitive function among MCI participants after the intervention, as evidenced by changes in total ADAS-cog scores. Results demonstrated excellent adherence throughout the program and significant cognitive improvements after the intervention. This pilot study indicates that Silvia-Rx's digital cognitive program is feasible for people diagnosed with MCI, suggests potential for improving cognitive function, though further research with large sample size is needed to confirm these results.

Risk factors and metabolomics of mild cognitive impairment in type 2 diabetes mellitus.

Objective: This study aimed to explore the risk factors, metabolic characteristics, and potential biomarkers of mild cognitive impairment in type 2 diabetes mellitus (T2DM-MCI) and to provide potential evidence for the diagnosis, prevention, and treatment of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 103 patients with T2DM were recruited from the Endocrinology Department of The Second Affiliated Hospital of Dalian Medical University for inclusion in the study. The Montreal Cognitive Assessment (MoCA) was utilized to evaluate the cognitive functioning of all patients. Among them, 50 patients were categorized into the T2DM-MCI group (MoCA score < 26 points), while 53 subjects were classified into the T2DM without cognitive impairment (T2DM-NCI) group (MoCA score ≥ 26 points). Serum samples were collected from the subjects, and metabolomics profiling data were generated by Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). These groups were analyzed to investigate the differences in expression of small molecule metabolites, metabolic pathways, and potential specific biomarkers. Results: Comparison between the T2DM-MCI group and T2DM-NCI group revealed significant differences in years of education, history of insulin application, insulin resistance index, insulin-like growth factor-binding protein-3 (IGFBP-3), and creatinine levels. Further binary logistic regression analysis of the variables indicated that low educational level and low serum IGFBP-3 were independent risk factor for T2DM-MCI. Metabolomics analysis revealed that differential expression of 10 metabolites between the T2DM-MCI group and T2DM-NCI group (p < 0.05 and FDR<0.05, VIP>1.5). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that fatty acid degradation was the most significant pathway. Receiver operating characteristic (ROC) analysis shows that lysophosphatidylcholine (LPC) 18:0 exhibited greater diagnostic efficiency. Conclusion: This study revealed that a shorter duration of education and lower serum IGFBP-3 levels are independent risk factors for T2DM-MCI. Serum metabolites were found to be altered in both T2DM-MCI and T2DM-NCI groups. T2DM patients with or without MCI can be distinguished by LPC 18:0. Abnormal lipid metabolism plays a significant role in the development of MCI in T2DM patients.

Factors influencing the help-seeking behavior in patients with mild cognitive impairment: a qualitative study

BackgroundThe early diagnosis and intervention of mild cognitive impairment (MCI) patients is expected to delay the progression of AD. Delayed treatment will lead to MCI patients missing the best intervention expectation. At present, the medical help-seeking behavior of this group is not optimistic. This study aimed to explore influencing factors of help-seeking behavior among patients with MCI in China based on the help-seeking behavior model.MethodsTwenty-two patients with MCI were recruited to participate in semi-structured interviews via purposeful sampling with a qualitative, descriptive design. Data were analyzed by qualitative content analysis.ResultsThe study revealed the main influencing factors of help-seeking behavior among MCI patients in China included perceived disease threat, symptom attribution, disease knowledge, use of cognitive compensation strategies, sense of foreseeable burden, social support, economic condition, and accessibility of medical service.ConclusionsThe help-seeking behavior of patients with MCI is affected by multiple factors. There are some key factors in different stages of the help-seeking process. Healthcare providers can utilize these factors to design targeted interventions for promoting early help-seeking of patients with MCI.

The potential cost‐effectiveness of roflumilast drug treatment in mild cognitive impairment

AbstractBackgroundEvidence is needed on the value of new (pharmacological) health technologies in their early stage of development, to support stakeholders (industry, regulators, payers, and health care providers) in decision‐making linked to their further development and introduction in routine care. Early health‐technology assessment supports stakeholders by providing insight into the size and uncertainty of the expected benefits new technologies may have. This can facilitate early guidance on positioning in clinical practice and research recommendations. Our objective was to provide a pragmatic example of the potential cost‐effectiveness of roflumilast treatment in addition to usual care versus usual care alone if prevention of progression to dementia is in part realized in a population of patients diagnosed with a mild cognitive impairment (MCI) at a memory clinic.MethodThe IPECAD open‐source decision‐analytic model was used to simulate the natural disease progression of MCI and dementia and estimate the quality‐adjusted life years (QALYs) and care costs, comparing roflumilast treatment added to usual care with usual care alone. In this model roflumilast proof of concept evidence on a visual 30‐word verbal learning test (0.39 z‐score) was translated using a published risk equation model to a relative risk of 0.93 for developing dementia. The treatment was assumed symptomatic with no effect on mortality.ResultMore lifeyears were spent in MCI in the roflumilast strategy compared with usual care, with 0.2 increment lifeyears (95%CI: 0.0 to 0.6) (see figure 1), and 0.04 incremental lifetime QALYs (95%CI: 0.00 to 0.11) and k€1.3 adjusted societal costs (95%CI: ‐6.3 to 5.5) (see figure 2). This resulted in an incremental cost‐effectiveness ratio of k€34 per QALY (see table 1). Roflumilast was estimated to have a 37% probability of being cost‐effective (net health benefit 95% interval ‐0.27 to 0.42), with uncertainty mainly driven by extrapolating the word learning surrogate outcome to the patient‐relevant outcome of dementia onset, and the efficacy estimate (see figure 3).ConclusionThe potential cost‐effectiveness of roflumilast treatment is uncertain, driven by uncertainty in treatment efficacy and extrapolation to postponing dementia onset. We believe the results indicate a potential for roflumilast and provide several recommendations to consider investing in its future research.