Diagnosis Of Mild Cognitive Impairment Research Articles

The Intersecting Effects of Lifetime Experiences of Homelessness and Incarceration on Cognitive Aging and Dementia Risk Factors in the United States.

Alzheimer's disease and related dementias (ADRD) remain a pressing concern in the US, which also has one of the highest incarceration rates worldwide. Existing research has analyzed dementia risk and care among currently incarcerated and homeless populations; this paper fills a gap by examining later-life cognitive disparities facing formerly incarcerated and/or homeless individuals. Using Health and Retirement Study data (HRS; 1998-2018), we tested whether formerly homeless and/or incarcerated people had earlier onset of cognitive decline, and whether they were more likely to have modifiable risk factors for ADRD than those without such experiences. We estimated prevalence of mild cognitive impairment (MCI), dementia, and self-reported ADRD diagnosis. We also used repeated observations of cognitive functioning coupled with nested nonlinear regression to examine the onset of accelerated cognitive decline. Adjusting for demographic variables, formerly homeless and/or incarcerated participants have increased odds of having risk factors for dementia, including smoking, drinking alcohol, depression, mental illness, and discrimination from healthcare providers and police. Diagnosis of MCI and ADRD were more common among participants reporting a history of incarceration or homelessness. Nested nonlinear regression revealed that previous experiences of incarceration or homelessness-alone or together-are associated with earlier onset of accelerated cognitive decline compared to those who experienced neither. This study suggests that, even if they occur earlier in life, homelessness and incarceration experiences may increase risk of poorer cognitive health in late life. Future work is warranted to understand the lifelong consequences linked to this adversity.

Cortico-limbic volume abnormalities in late life depression are distinct from β amyloid and white matter pathologies.

This study was conducted to clarify patterns of cortico-limbic volume abnormalities in late life depression (LLD) relative to non-depressed (ND) adults matched for amyloid β (Aβ) deposition and to evaluate the relationship of volume abnormalities with cognitive performance. Participants included 116 LLD and 226 ND. Classification accuracy of LLD status was estimated using area under the receiver operator characteristic curve. Twenty-one percent of LLD and ND participants were Aβ positive and the groups did not differ on white matter hyperintensity volume (WMH (logscale); β = 0.12, p = 0.28). Compared to ND, the LLD group exhibited significantly lower bilateral volume in the lateral orbitofrontal cortex, hippocampus, accumbens area, superior temporal lobe, temporal pole, and amygdala after multiple comparison correction (p < 0.009 for all). Cortico-limbic volumes significantly improved classification of LLD beyond demographic characteristics, Aβ status, and WMH (AUCVol = 0.71, AUCWMH, Aβ = 0.62, AUC difference, 0.09 [0.03 to 0.15]). LLD exhibited poorer performance on measures of global cognition, set shifting, and verbal learning and memory relative to ND. Cognitive function was positively associated with cortico-limbic volumes and these relationships did not differ by group. Secondary analyses with an ND sample additionally matched for Mild Cognitive Impairment (MCI) diagnosis showed a similar but attenuated pattern of volume abnormalities. Overall, our results support LLD as being associated with cortico-limbic volume abnormalities that are distinct from Aβ and white matter pathologies and that these volume abnormalities are important factors associated with cognitive dysfunction in LLD.

Motor signs and incident dementia with Lewy bodies in older adults with mild cognitive impairment.

Motor signs may herald incident dementia and allow the earlier detection of high-risk individuals and the timely implementation of preventive interventions. The current study was performed to investigate the prognostic properties of motor signs with respect to incident dementia with Lewy bodies (DLB) in older adults with mild cognitive impairment (MCI). Emphasis was placed on sex differences. The specificity of these associations was explored. We analyzed data from the National Alzheimer's Coordinating Center Uniform Data Set. Participants 55 + years old with a diagnosis of MCI were included in the analysis. Those with Parkinson's disease (PD) or other parkinsonian disorders at baseline and those with PD dementia at follow-up were excluded. UPDRS III was used to assess the presence or absence of motor signs in nine domains: hypophonia; masked facies; resting tremor; action/postural tremor; rigidity; bradykinesia; impaired chair rise; impaired posture/gait; postural instability. Αdjusted Cox proportional hazards models featuring sex by motor sign interactions were estimated. Throughout the average follow-up of 3.7 ± 3.1 years, among 4623 individuals with MCI, 2211 progressed to dementia (66 of whom converted to DLB). Masked facies [HR = 4.21 (1.74-10.18)], resting tremor [HR = 4.71 (1.44-15.40)], and bradykinesia [HR = 3.43 (1.82-6.45)] exclusively increased the risk of DLB. The HR of DLB was approximately 15 times greater in women compared to men with masked facies. Impaired posture-gait (approximately 10 times) and resting tremor (approximately 8.5 times) exhibited a similar trend (prominent risk-conferring properties in women compared to men) but failed to achieve statistical significance. Rigidity and hypophonia elevated the risk of other dementia entities, as well. The remaining motor features were not related to incident dementia of any type. Specific motor signs may herald DLB among individuals with MCI. Different associations may exist between masked facies, impaired posture-gait, resting tremor, and incident DLB in men versus women.

Mild cognitive impairment and early Alzheimer's disease eligibility for disease modification therapies in a tertiary centre for cognitive disorders: A simultaneous real-word study on aducanumab and lecanemab.

The Food and Drug Administration approved two disease-modifying treatments (DMTs) for Alzheimer's disease (AD), aducanumab and lecanemab, with limited clinical impact but significant biomarker changes. Identifying suitable candidates for these DMTs outside randomized clinical trials (RCTs) remains uncertain. This cross-sectional study, conducted in an Italian tertiary centre for cognitive disorders, aimed to evaluate how the RCT eligibility criteria for DMT treatments applies to participants with early AD. The broader Cummings etal. (Journal of Prevention of Alzheimer's Disease, 2021, 2023) criteria and the clinical differences between DMT candidates were also assessed. The study involved 408 participants (mean age 71.1 ± 8.5 years, 48% male) with a clinical diagnosis of mild cognitive impairment (161/408, 39.5%) or mild dementia (247/408, 60.5%). Amongst them, 169 individuals (41%) showed positive AD pathology biomarkers. Eligibility RCT assessment revealed 14 patients eligible for aducanumab (3.43% of 408) and 28 for lecanemab (6.86% of 408). Following Cummings' real-world criteria, aducanumab eligibility increased to 9.56%, whereas lecanemab eligibility rose to 8.33%. Applying selection criteria to only the amyloid positive (169 out of 408), the selection for DMTs was 8.3% for aducanumab and 16.5% for lecanemab. Amongst subjects diagnosed with mild AD and mild cognitive impairment in a tertiary centre for cognitive disorders, only a small percentage of patients using RCT diagnostic criteria are eligible for DMT. The application of Cummings criteria strongly increased the DMT candidates. Nevertheless, the majority of patients with cognitive disorders have been excluded from DMTs approved so far.

Behavioral and Psychological Symptoms of Dementia and Mortality Risk Among People With Cognitive Impairment: An 8-year Longitudinal Study From the NCGG-STORIES.

Behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia from the early stages and can appear even in mild cognitive impairment (MCI). However, the prognostic impact of BPSD is unclear. This study examined the association between BPSD and mortality among people with cognitive impairment. This longitudinal study involved 1,065 males and 1,681 females (mean age: 77.1 years for males and 78.6 years for females) with MCI or dementia diagnosis from the National Center for Geriatrics and Gerontology-Life Stories of People with Dementia (NCGG-STORIES), a single-center memory clinic-based cohort study in Japan that registered first-time outpatients from 2010-2018. Information about death was collected through a mail survey returned by participants or their close relatives, with an up to 8-year follow-up. BPSD was assessed using the Dementia Behavior Disturbance Scale (DBD) at baseline. During the follow-up period, 229 (28.1%) male and 254 (15.1%) female deaths occurred. Cox proportional hazards regression analysis showed that higher DBD scores were significantly associated with increased mortality risk among males, but not females (compared with the lowest quartile score group, hazard ratios for the highest quartile score group were 1.59; 95% confidence interval, [CI] 1.11-2.29 for males and 1.06; 95% CI, 0.66-1.70 for females). Among the DBD items, lack of interest in daily living, excessive daytime sleep, and refusal to receive care had a higher mortality risk. The findings suggest a potential association between BPSD and poor prognosis among males with cognitive impairment.

The Italian guideline on diagnosis and treatment of dementia and mild cognitive impairment.

Approximately 2 million people in Italy are currently living with dementia or mild cognitive impairment (MCI), and 4 million are involved as family members or caregivers. Considering the significant impact of dementia, the Italian Ministry of Health entrusted the Italian National Institute of Health (Istituto Superiore di Sanità) with the development of a guideline within the Italian National Guideline System (Sistema Nazionale Linee Guida, SNLG) on the diagnosis and treatment of dementia and MCI. The main objective was to provide evidence-based recommendations aimed at reducing the variability and ensuring the appropriateness of clinical practices throughout the whole care process from identification and diagnosis to the end of life for people with dementia (PwD) or MCI and their families/caregivers. The GRADE-ADOLOPMENT approach was used to adopt, adapt and update the guideline developed by the National Institute for Health and Care Excellence in 2018 (NG97). The methodology was based on the Methodological Handbook produced by the SNLG. A multidisciplinary panel of 29 experts and four representatives of family members/caregivers discussed and approved 47 review questions. Of these, 34 questions were adopted from the NG97, and 13 were new questions, including 10 questions referring to MCI. Systematic literature reviews were performed for each question, and a team of methodological and clinical experts qualitatively assessed and summarised results from included studies based on the GRADE approach. To facilitate the implementation and dissemination of the contents of this guideline, a care pathway and a leaflet dedicated to PwD or MCI and their families/caregivers were also developed. The literature review for this guideline included studies published up to November 2023. More than 1000 peer-reviewed publications were included, covering the following areas: (i) identification, diagnosis and post-diagnostic support; (ii) care models and care coordination; (iii) pharmacological interventions for cognitive symptoms; (iv) non-pharmacological interventions for cognitive symptoms; (v) non-cognitive symptoms, intercurrent illnesses and palliative care. The multidisciplinary panel discussed and approved 167 clinical practice recommendations and 39 research recommendations. Italy's first National Guideline on dementia and MCI addresses diagnosis, treatment and care within the National Healthcare System. It includes recommendations on pharmacological and non-pharmacological approaches, and emphasises tailored interventions, comprehensive cognitive assessment, staff training and palliative care. The guideline also underlines the need to involve PwD in decision-making and supporting caregivers throughout the entire course of the disease. Structured strategies for the dissemination and implementation of the guideline will be defined within the Italian Fund for Alzheimer and other Dementias 2024-2026. An interactive care pathway and a leaflet dedicated to PwD and their carers are already available. The guideline will be updated starting January 2027, but early updates may be planned in case of breakthrough advancements.

Intersectionality of gender with social determinants of health and asymptomatic Alzheimer's disease neuropathology.

Women comprise approximately two-thirds of Alzheimer's disease cases. This is the first known study to investigate the role of intersectionality between gender and other social determinants of health (SDOH) in the presentation of cognitive symptoms (i.e., being asymptomatic or symptomatic) among those with pathologically confirmed Alzheimer's disease. We studied 3107 individuals with Alzheimer's disease neuropathology (ADNP) confirmed at autopsy. Asymptomatic ADNP was defined as the absence of a clinical diagnosis of mild cognitive impairment (MCI) or dementia before death (versus symptomatic: diagnosis of MCI/dementia). SDOH included gender, education, ethnoracial group, living alone, and primary language. Multivariable logistic regression tested associations between SDOH and asymptomatic ADNP (versus symptomatic); models were also stratified by gender. Women, Hispanics, those living alone, and more educated individuals were found to have higher odds of asymptomatic ADNP. Non-English speakers had lower odds of asymptomatic ADNP. Both women and men had higher odds of asymptomatic ADNP if Hispanic or living alone. In only women, non-English speakers had lower odds while in only men, more education was associated with higher odds of asymptomatic ADNP. Gender, education, ethnicity, primary language, and living alone, and intersectionality of gender with primary language, may differentially influence MCI and dementia diagnosis prior to death among those with underlying ADNP. These findings emphasize the need for future Alzheimer's disease research to prioritize social determinants of brain health including their intersectionality with gender and how to inform targeted interventions.

Enhancing early detection of cognitive decline in the elderly: a comparative study utilizing large language models in clinical notes

BackgroundLarge language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement. MethodsThis study, conducted at Mass General Brigham in Boston, MA, analysed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We developed prompts for two LLMs, Llama 2 and GPT-4, on Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud-computing platforms using multiple approaches (e.g., hard prompting, retrieval augmented generation, and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach. Confusion-matrix-based scores were used for model evaluation. FindingsWe used a randomly annotated sample of 4,949 note sections from 1,969 patients (women: 1,046 [53.1%]; age: mean, 76.0 [SD, 13.3] years), filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1,996 note sections from 1,161 patients (women: 619 [53.3%]; age: mean, 76.5 [SD, 10.2] years) without keyword filtering was utilised. GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models in terms of all evaluation metrics with statistical significance (p<0.01), achieving a precision of 90.2% [95% CI: 81.9%-96.8%], a recall of 94.2% [95% CI: 87.9%-98.7%], and an F1-score of 92.1% [95% CI: 86.8%-96.4%]. Notably, the ensemble model showed a significant improvement in precision, increasing from a range of 70%-79% to above 90%, compared to the best-performing single model. Error analysis revealed that 63 samples were incorrectly predicted by at least one model; however, only 2 cases (3.2%) were mutual errors across all models, indicating diverse error profiles among them. InterpretationLLMs and traditional machine learning models trained using local EHR data exhibited diverse error profiles. The ensemble of these models was found to be complementary, enhancing diagnostic performance. Future research should investigate integrating LLMs with smaller, localised models and incorporating medical data and domain knowledge to enhance performance on specific tasks.

Association of dietary choline intake with incidence of dementia, Alzheimer's disease and mild cognitive impairment: a large population-based prospective cohort study

ObjectiveExplore the associations between dietary choline intake and the incidence of dementia, Alzheimer's disease (AD), mild cognitive impairment (MCI), and current cognitive performance in the UK Biobank cohort. MethodsDietary choline intake was categorized into quartiles of consumption based on 24-hour dietary recalls, with units expressed as milligrams per day. Diagnoses of dementia, AD, and MCI were identified using ICD-9/10 codes. Current cognitive performance was assessed via the computerized touchscreen interface. After adjusting for sociodemographic factors, dietary and lifestyle behaviors, and comorbid conditions, Cox proportional hazards regression, logistic regression, and restricted cubic splines were used to analyze the association between choline intake and dementia or cognitive performance. ResultsAmong 125,594 participants (55.8% female), with a mean age of 56.1 years (range: 40 to 70 years) at baseline, and a median follow-up of 11.8 years, 1,103 cases of dementia (including 385 AD) and 87 cases of MCI were recorded. U-shaped associations were observed between choline intake and dementia and AD. Participants in the 2nd quartile of total choline intake had lower risks compared to those in the lowest quartile, with HR of 0.80 (95% CI: 0.67, 0.96) for dementia and 0.76 (0.58, 1.00) for AD. Moderate intake of choline derivative, including free choline (HR, 0.77; 95%CI, 0.65, 0.92), phosphatidylcholine (0.82; 0.68, 0.98), sphingomyelin (0.82; 0.69, 0.98) and glycerophosphocholine (0.83; 0.70, 1.00), were associated with a 17% to 23% lower odds of dementia. Additionally, moderate total choline intake was associated with an 8% to 13% lower odds of poor cognitive performance in visual attention (OR, 0.92; 95%CI, 0.86, 0.99), fluid intelligence (0.87; 0.82, 0.92), and complex processing speed (0.90; 0.84, 0.95). ConclusionsIn conclusion, our findings suggest that moderate dietary choline intake, ranging from 332.89 mg/d to 353.93 mg/d, is associated with lower odds of dementia and better cognitive performance.

Diagnostic Accuracy of Combined Measurement of Serum Homocysteine, C-Reactive Protein, and Serum Ferritin in Mild Cognitive Impairments and Alzheimer's Disease.

Evaluation of the diagnostic accuracy of combined detection of serum homocysteine (Hcy), C-reactive protein (CRP), and serum ferritin (SF) levels in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Descriptive study. Place and Duration of the Study: Clinical Laboratory Section, Affiliated Hospital of Hebei University, Baoding, Heibei, China, from May 2022 to June 2023. Data of 120 patients with memory decline were retrospectively collected. They were divided into an MCI group and an AD group. A further 50 healthy participants were used as a normal control (NC) group. Differences in the Hcy, CRP, and SF levels between the three groups were evaluated. The specificity, accuracy, and sensitivity of these three indices in the combined or single diagnosis of AD and MCI were compared. Their associations with the severity of AD and MCI were also compared. The AD group had the highest levels of Hcy, CRP, and SF (18.79 ± 4.50, 6.35 ± 2.04, and 355.69 ± 120.36), followed by MCI (16.75 ± 3.06, 4.58 ± 2.31, and 203.48 ± 12.76), and NC group (14.32 ± 2.06, 2.06 ± 0.76, and 98.46 ± 5.06), with statistically significant differences (all p <0.001). The diagnostic efficacy of AD for CRP was 98.50%, sensitivity was 96.00%, and specificity was 94.00%, which was higher than Hcy and SF. Tested together, the area under the ROC curve was 99.90%, specificity was 98.00%, and sensitivity was 98.00%. The diagnostic efficacy of SF for MCI had sensitivity of 100.00%, and specificity of 100.00%, which was higher than that of Hcy and CRP. When the three were combined for detection, the area under the curve of SF was 100.00%, sensitivity of 100.00%, and specificity of 100.00%. The levels of Hcy, CRP, and SF were positively correlated with the severity of AD (p <0.01), while negatively correlated with the mini-mental state examination (MMSE) score (p <0.01). The combined detection of Hcy, CRP, and SF improved the diagnostic accuracy of comorbid AD and MCI. Homocysteine, C-reactive protein, Cognitive impairment, Serum ferritin, Alzheimer's disease.

Diagnostic Accuracy of Combined Measurement of Serum Homocysteine, C-Reactive Protein, and Serum Ferritin in Mild Cognitive Impairments and Alzheimer's Disease.

Evaluation of the diagnostic accuracy of combined detection of serum homocysteine (Hcy), C-reactive protein (CRP), and serum ferritin (SF) levels in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Descriptive study. Place and Duration of the Study: Clinical Laboratory Section, Affiliated Hospital of Hebei University, Baoding, Heibei, China, from May 2022 to June 2023. Data of 120 patients with memory decline were retrospectively collected. They were divided into an MCI group and an AD group. A further 50 healthy participants were used as a normal control (NC) group. Differences in the Hcy, CRP, and SF levels between the three groups were evaluated. The specificity, accuracy, and sensitivity of these three indices in the combined or single diagnosis of AD and MCI were compared. Their associations with the severity of AD and MCI were also compared. The AD group had the highest levels of Hcy, CRP, and SF (18.79 ± 4.50, 6.35 ± 2.04, and 355.69 ± 120.36), followed by MCI (16.75 ± 3.06, 4.58 ± 2.31, and 203.48 ± 12.76), and NC group (14.32 ± 2.06, 2.06 ± 0.76, and 98.46 ± 5.06), with statistically significant differences (all p <0.001). The diagnostic efficacy of AD for CRP was 98.50%, sensitivity was 96.00%, and specificity was 94.00%, which was higher than Hcy and SF. Tested together, the area under the ROC curve was 99.90%, specificity was 98.00%, and sensitivity was 98.00%. The diagnostic efficacy of SF for MCI had sensitivity of 100.00%, and specificity of 100.00%, which was higher than that of Hcy and CRP. When the three were combined for detection, the area under the curve of SF was 100.00%, sensitivity of 100.00%, and specificity of 100.00%. The levels of Hcy, CRP, and SF were positively correlated with the severity of AD (p <0.01), while negatively correlated with the mini-mental state examination (MMSE) score (p <0.01). The combined detection of Hcy, CRP, and SF improved the diagnostic accuracy of comorbid AD and MCI. Homocysteine, C-reactive protein, Cognitive impairment, Serum ferritin, Alzheimer's disease.

The efficacy of cognitive stimulation, cognitive training, and cognitive rehabilitation for people living with dementia: a systematic review and meta-analysis.

Cognition-oriented treatments (COTs) are a group of non-pharmacological treatments aimed at maintaining or improving cognitive functioning. Specific recommendations on the use of these interventions in people living with dementia (PLwD) are included in the Italian Guideline on the Diagnosis and Treatment of Dementia and Mild Cognitive Impairment, developed by the Italian National Institute of Health. This systematic review and meta-analysis, based on the GRADE methodology, is part of the guideline. Considered outcomes included the cognitive functions, quality of life, and functional abilities of PLwD, taking into account disease severity, modality and system of delivery, and form of the intervention. The effectiveness of these interventions on caregivers' outcomes was also assessed. Both group and individual cognitive stimulation were reported as effective in supporting cognitive functions in PLwD at any degree of severity. Individual cognitive training and group cognitive training were reported as effective in improving global cognitive functions in people with mild dementia. Cognitive rehabilitation appeared to be effective only in improving the functional abilities of people with mild dementia. Cognitive rehabilitation appeared to be the most effective in improving caregivers' outcomes, with results suggesting a reduction in care burden. The observed differences in the effectiveness of these interventions in people with different disease severity can be explained by the intrinsic characteristics of each intervention. Despite the large number of available studies, a high clinical, statistical, and methodological heterogeneity was observed. More methodologically rigorous studies are needed to clarify the effectiveness of each protocol and modality of intervention.

The influence of alterations in the composition of intestinal microbiota on neurovascular coupling and cognitive dysfunction in individuals afflicted with CSVD

IntroductionAn expanding body of research has explored the crucial role of gut microbiota in cerebral small vessel disease (CSVD). The objective of this study is to investigate alterations in the gut microbiota structure among CSVD patients, to explore the correlation between differential taxonomic levels and the neurovascular coupling index as well as cognitive function and to elucidate the imaging and biomarkers of mild cognitive impairment (MCI) in CSVD. MethodsWe enrolled 104 patients with CSVD and 40 healthy controls (HC). Based on cognitive test scores, CSVD patients were categorized into a cognitively normal group (CSVD-NCI, n=61) and a mild cognitive impairment group (CSVD-MCI, n=43). Performing magnetic resonance imaging (MRI) scans, gut microbiota analysis, as well as clinical and neuropsychological assessments for all participants. Based on arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) imaging data, cerebral blood flow (CBF) and neural activity indices are computed. The coupling indices of CBF/mReHo, CBF/mfALFF, CBF/mALFF, and CBF/mDC are calculated to assess the whole-brain neurovascular coupling changes in patients with CSVD. ResultsSpecies annotation revealed differences in the composition at the phylum and genus levels among the HC, CSVD-NCI, and CSVD-MCI groups. Additionally, differential analysis using the Kruskal-Wallis test demonstrated specific dominant microbial communities in all three groups. The relative abundance of certain dominant microbial communities in CSVD patients exhibited correlations with neurovascular coupling and cognitive function. The combined assessment of Bacteroides genus and CBF/mDC proved effective in distinguishing between CSVD-NCI and CSVD-MCI, providing a novel non-invasive approach for the diagnosis of MCI in CSVD.

Deep Learning Based Diagnosis of Mild Cognitive Impairment Using Resting-State Functional MRI

Deep Learning Based Diagnosis of Mild Cognitive Impairment Using Resting-State Functional MRI

Outdoor artificial light at night and risk of conversion from mild cognitive impairment to dementia

Abstract Background A few studies have suggested that exposure to lighting during night hours, i.e. light at night (LAN), may increase the risk of dementia. In this study, we aimed to evaluate the association between exposure to outdoor artificial LAN and risk of conversion to dementia in an Italian cohort of subjects with mild cognitive impairment (MCI). Methods We recruited subjects with a diagnosis of MCI at the Cognitive Neurology Clinic of Modena Hospital in the period 2008-2014, and we followed these subjects up to 2021 for conversion to dementia. We collected their residential history and we assessed LAN exposure at subjects’ residences using satellite imagery data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) for the period 2014-2022. Using a Cox-proportional hazards model adjusted for relevant confounders, we computed the hazard ratio (HR) of dementia with 95% confidence interval (CI) according to increasing LAN exposure through linear, categorical, and non-linear restricted-cubic spline models. Results Out of 53 recruited subjects, 34 converted to dementia of any type including 26 Alzheimer’s dementia. In linear regression analysis, LAN exposure was positively associated with dementia conversion (HR 1.03, 95% CI 1.00-1.06 for 1-unit increase). Using as reference the lowest tertile, subjects at both intermediate and highest tertiles of LAN exposure showed increased risk of dementia conversion (HRs 2.26, 95% CI 0.88-5.85, and 2.89, 95% CI 1.10-7.58). In spline regression analysis, the risk linearly increased up to a LAN exposure of 30 nW/cm2/sr, above which a plateau seemed to be reached. Results were almost confirmed when limited to conversion to Alzheimer’s dementia, except for an almost linear relation. Conclusions Our findings suggest that exposure to outdoor artificial LAN may increase conversion from MCI to any type of dementia, especially above 30 nW/cm2/sr, while such relation appears to be almost linear for Alzheimer’s dementia. Key messages • Light at night exposure above 30 nW/cm2/sr was associated with risk of conversion to dementia. • Light at night showed almost linear association with risk of conversion to Alzheimer’s dementia.

Asynchronous Functional Brain Network Construction with Spatiotemporal Transformer for MCI Classification.

Construction and analysis of functional brain networks (FBNs) with resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method to diagnose functional brain diseases. Nevertheless, the existing methods suffer from several limitations. First, the functional connectivities (FCs) of the FBN are usually measured by the temporal co-activation level between rs-fMRI time series from regions of interest (ROIs). While enjoying simplicity, the existing approach implicitly assumes simultaneous co-activation of all the ROIs, and models only their synchronous dependencies. However, the FCs are not necessarily always synchronous due to the time lag of information flow and cross-time interactions between ROIs. Therefore, it is desirable to model asynchronous FCs. Second, the traditional methods usually construct FBNs at individual level, leading to large variability and degraded diagnosis accuracy when modeling asynchronous FBN. Third, the FBN construction and analysis are conducted in two independent steps without joint alignment for the target diagnosis task. To address the first limitation, this paper proposes an effective sliding-window-based method to model spatiotemporal FCs in Transformer. Regarding the second limitation, we propose to learn common and individual FBNs adaptively with the common FBN as prior knowledge, thus alleviating the variability and enabling the network to focus on the individual disease-specific asynchronous FCs. To address the third limitation, the common and individual asynchronous FBNs are built and analyzed by an integrated network, enabling end-to-end training and improving the flexibility and discriminativity. The effectiveness of the proposed method is consistently demonstrated on three data sets for mild cognitive impairment (MCI) diagnosis.

Prevalence of Unrecognized Cognitive Impairment in Federally Qualified Health Centers

There is a need for early and equitable detection of cognitive impairment among older adults. To examine the prevalence of unrecognized cognitive impairment among older adults receiving primary care from federally qualified health centers (FQHCs). This cross-sectional study was conducted at 5 FQHCs providing primary care in Indianapolis, Indiana, between 2021 and 2023. Participants were adults aged 65 years and older, without a diagnosis of mild cognitive impairment (MCI), dementia, or severe mental illness. Data analysis was performed from September 2023 to April 2024. The primary outcome was a diagnosis of dementia or MCI, as determined by an interdisciplinary clinical team using data from structured patient and study partner interviews, medical record reviews, and a detailed cognitive assessment, including neuropsychological testing. Differences between participants determined to have normal cognition, MCI, and dementia were assessed statistically using analysis of variance for continuous variables, χ2 or Fisher exact tests for categorical variables, or Fisher exact test alone when expected cell counts were 5 or less. A total of 844 eligible individuals were consecutively approached, 294 consented to participate, and 204 completed the study (mean [SD] age, 70.0 [5.1] years; 127 women [62.3%]). One hundred eight participants (52.9%) were African American, 5 (2.5%) were Hispanic, 199 (97.5%) were not Hispanic, and 90 (44.1%) were White. The mean (SD) duration of education was 13.1 (2.6) years, and the mean (SD) Area Deprivation Index score was 78.3 (19.9), indicating a high level of neighborhood disadvantage. In total, 127 patients (62.3%) met the diagnostic criteria for MCI, 25 (12.3%) had dementia, and 52 (25.5%) had no cognitive impairment. Compared with non-Hispanic White individuals and after adjusting for age, sex, and education level, African American individuals were more than twice as likely to have MCI or dementia (odds ratio, 2.73; 95% CI, 1.38-5.53; P = .02). This cross-sectional study found that unrecognized cognitive impairment is ubiquitous among older adults from underrepresented, minoritized racial and ethnic groups and those who are socially vulnerable receiving primary care from FQHCs. To overcome the disparity in early detection of cognitive impairment, timely, equitable, scalable, and sustainable detection approaches need to be developed.

Characterizing the progression from mild cognitive impairment to dementia: a network analysis of longitudinal clinical visits

BackgroundWith the recent surge in the utilization of electronic health records for cognitive decline, the research community has turned its attention to conducting fine-grained analyses of dementia onset using advanced techniques. Previous works have mostly focused on machine learning-based prediction of dementia, lacking the analysis of dementia progression and its associations with risk factors over time. The black box nature of machine learning models has also raised concerns regarding their uncertainty and safety in decision making, particularly in sensitive domains like healthcare.ObjectiveWe aimed to characterize the progression of health conditions, such as chronic diseases and neuropsychiatric symptoms, of the participants in Mayo Clinic Study of Aging (MCSA) from initial mild cognitive impairment (MCI) diagnosis to dementia onset through network analysis.MethodsWe used the data from the MCSA, a prospective population-based cohort study of cognitive aging, and examined the changing association among variables (i.e., participants’ health conditions) from the first visit of MCI diagnosis to the visit of dementia onset using network analysis. The number of participants for this study are 97 with the number of visits ranging from 2 visits (30 months) to 7 visits (105 months). We identified the network communities among variables from three-fold collection of instances: (i) the first MCI diagnosis, (ii) progression to dementia, and (iii) dementia diagnosis. We determine the variables that play a significant role in the dementia onset, aiming to identify and prioritize specific variables that prominently contribute towards developing dementia. In addition, we explore the sex-specific impact of variables in relation to dementia, aiming to investigate potential differences in the influence of certain variables on dementia onset between males and females.ResultsWe found correlation among certain variables, such as neuropsychiatric symptoms and chronic conditions, throughout the progression from MCI to dementia. Our findings, based on patterns and changing variables within specific communities, reveal notable insights about the time-lapse before dementia sets in, and the significance of progression of correlated variables contributing towards dementia onset. We also observed more changes due to certain variables, such as cognitive and functional scores, in the network communities for the people who progressed to dementia compared to those who does not. Most changes for sex-specific analysis are observed in clinical dementia rating and functional activities questionnaire during MCI onset are followed by chronic diseases, and then by NPI-Q scores.ConclusionsNetwork analysis has shown promising potential to capture significant longitudinal changes in health conditions, spanning from the MCI diagnosis to dementia progression. It can serve as a valuable analytic approach for monitoring the health status of individuals in cognitive impairment assessment. Furthermore, our findings indicate a notable sex difference in the impact of specific health conditions on the progression of dementia.

The Effect of Segmentation Method on Medial Temporal Lobe Subregion Volumes in Aging.

Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method-the Olsen-Amaral-Palombo (OAP) protocol-previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS-OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS-OAP atlas were also contrasted against those from the ASHS-PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS-OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS-OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS-OAP and ASHS-PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA2/CA3/DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas.

Individualised computerised cognitive training (iCCT) for community-dwelling people with mild cognitive impairment (MCI): results on cognition in the 6-month intervention period of a randomised controlled trial (MCI-CCT study)

BackgroundComputerised cognitive training (CCT) can improve the cognitive abilities of people with mild cognitive impairment (MCI), especially when the CCT contains a learning system, which is a type of machine learning (ML) that automatically selects exercises at a difficulty that corresponds to the person’s peak performance and thus enables individualised training.MethodsWe developed one individualised CCT (iCCT) with ML and one basic CCT (bCCT) for an active control group (CG). The study aimed to determine whether iCCT in the intervention group (IG) resulted in significantly greater enhancements in overall cognitive functioning for individuals with MCI (age 60+) compared with bCCT in the CG across a 6-month period. This double-blind randomised controlled study was conducted entirely virtually. The 89 participants were community-dwelling people with a psychometric diagnosis of MCI living in Germany. The iCCT stimulates various cognitive functions, especially working memory, visuo-constructional reasoning, and decision-making. The bCCT includes fewer and simpler tasks. Both CCTs were used at home. At baseline and after 6 months, we assessed cognitive functioning with the Montreal Cognitive Assessment (MoCA). A mixed-model ANCOVA was conducted as the main analysis.ResultsBoth CCTs led to significant increases in average global cognition. The estimated marginal means of the MoCA score increased significantly in the CG by an average of 0.9 points (95% CI [0.2, 1.7]) from 22.3 (SE = 0.25) to 23.2 (SE = 0.41) points (p = 0.018); in the IG, the MoCA score increased by an average of 2.2 points (95% CI [1.4, 2.9]) from 21.9 (SE = 0.26) to 24.1 (SE = 0.42) points (p < 0.001). In a confound-adjusted multiple regression model, the interaction between time and group was statistically significant (F = 4.92; p = 0.029). The effect size was small to medium (partial η2 = 0.057). On average, the participants used the CCTs three times per week with an average duration of 34.9 min per application. The iCCT was evaluated as more attractive and more stimulating than the bCCT.ConclusionsBy using a multi-tasking CCT three times a week for 30 min, people with MCI living at home can significantly improve their cognitive abilities within 6 months. The use of ML significantly increases the effectiveness of cognitive training and improves user satisfaction.Trial registrationISRCTN14437015; registered February 27, 2020.