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009) and insulin-like growth factor-binding protein 2 (AD APOE- PRS p = 0.025, protein APOE- PRS p = 0.045) displayed suggestive signals and were selected for MR. In bi-directional MR, none of the five proteins demonstrated a causal association (p <  0.05) in either direction.

Apolipoproteins and CRP PRS are associated with AD and provide a genetic signal linked to a specific, accessible risk factor. While evidence of causality was limited, this study was conducted in a moderate sample size and provides a framework for larger samples with greater statistical power.

Apolipoproteins and CRP PRS are associated with AD and provide a genetic signal linked to a specific, accessible risk factor. While evidence of causality was limited, this study was conducted in a moderate sample size and provides a framework for larger samples with greater statistical power.

Meta-analyses of individuals' cognitive data are increasing to investigate the biomedical, lifestyle, and sociocultural factors that influence cognitive decline and dementia risk. Pre-statistical harmonization of cognitive instruments is a critical methodological step for accurate cognitive data harmonization, yet specific approaches for this process are unclear.

To describe pre-statistical harmonization of cognitive instruments for an individual-level meta-analysis in the blood pressure and cognition (BP COG) study.

We identified cognitive instruments from six cohorts (the Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Coronary Artery Risk Development in Young Adults study, Framingham Offspring Study, Multi-Ethnic Study of Atherosclerosis, and Northern Manhattan Study) and conducted an extensive review of each item's administration and scoring procedures, and score distributions.

We included 153 cognitive instrument items from 34 instruments across the six cohorts. Of these items, 42%were common across ≥2 cohorts. 86%of common items showed differences across cohorts. We found administration, scoring, and coding differences for seemingly equivalent items. These differences corresponded to variability across cohorts in score distributions and ranges. We performed data augmentation to adjust for differences.

Cross-cohort administration, scoring, and procedural differences for cognitive instruments are frequent and need to be assessed to address potential impact on meta-analyses and cognitive data interpretation. Detecting and accounting for these differences is critical for accurate attributions of cognitive health across cohort studies.

Cross-cohort administration, scoring, and procedural differences for cognitive instruments are frequent and need to be assessed to address potential impact on meta-analyses and cognitive data interpretation. Detecting and accounting for these differences is critical for accurate attributions of cognitive health across cohort studies.

Low-value care (LvC) is defined as care unlikely to provide a benefit to the patient regarding the patient's preferences, potential harms, costs, or available alternatives. Avoiding LvC and promoting recommended evidence-based treatments, referred to as high-value care (HvC), could improve patient-reported outcomes for people living with dementia (PwD).

This study aims to determine the prevalence of LvC and HvC in dementia and the associations of LvC and HvC with patients' quality of life and hospitalization.

The analysis was based on data of the DelpHi trial and included 516 PwD. Dementia-specific guidelines, the "Choosing Wisely" campaign and the PRISCUS list were used to indicate LvC and HvC treatments, resulting in 347 LvC and HvC related recommendations. Of these, 77 recommendations (51 for LvC, 26 for HvC) were measured within the DelpHi-trial and finally used for this analysis. The association of LvC and HvC treatments with PwD health-related quality of life (HRQoL) and hospitalization was assessed using multiple regression models.

LvC was highly prevalent in PwD (31%). PwD receiving LvC had a significantly lower quality of life (b = -0.07; 95%CI -0.14--0.01) and were significantly more likely to be hospitalized (OR = 2.06; 95%CI 1.26-3.39). Different HvC treatments were associated with both positive and negative changes in HRQoL.

LvC could cause adverse outcomes and should be identified as early as possible and tried to be replaced. Future research should examine innovative models of care or treatment pathways supporting the identification and replacement of LvC in dementia.

LvC could cause adverse outcomes and should be identified as early as possible and tried to be replaced. Future research should examine innovative models of care or treatment pathways supporting the identification and replacement of LvC in dementia.

Many cases of dementia with Lewy bodies (DLB) present with various psychotic features, including hallucinations, depression, catatonia, and delusions before the onset of cognitive impairment. However, the characteristic features of these psychotic symptoms in prodromal DLB have not been sufficiently described.

To clarify and describe the psychotic features of prodromal DLB before overt cognitive impairment.

The authors analyzed the characteristic psychotic features of prodromal DLB in 21 subjects who developed severe psychotic symptoms without dementia and were diagnosed as DLB after the longitudinal observation period. They were then confirmed to have DLB through indicative and supportive biomarkers of scintigraphy.

The psychotic features included a wide variety of symptoms, but convergent to three principal categories catatonia, delusions-hallucinations, and depression and/or mania. Catatonia was observed in nine cases, five were delusional-hallucinatory, and seven were manic and/or depressive. Seve is required to avoid misdiagnosis.

The Smart Aging Serious Game (SASG) is an ecologically-based digital platform used in mild neurocognitive disorders. Considering the higher risk of developing dementia for mild cognitive impairment (MCI) and vascular cognitive impairment (VCI), their digital phenotyping is crucial. A new understanding of MCI and VCI aided by digital phenotyping with SASG will challenge current differential diagnosis and open the perspective of tailoring more personalized interventions.

To confirm the validity of SASG in detecting MCI from healthy controls (HC) and to evaluate its diagnostic validity in differentiating between VCI and HC.

161 subjects (74 HC 37 males, 75.47±2.66 mean age; 60 MCI 26 males, 74.20±5.02; 27 VCI 13 males, 74.22±3.43) underwent a SASG session and a neuropsychological assessment (Montreal Cognitive Assessment (MoCA), Free and Cued Selective Reminding Test, Trail Making Test). A multi-modal statistical approach was used receiver operating characteristic (ROC) curves comparison, random forest (RFd a useful digital phenotyping tool, allowing a non-invasive and valid neuropsychological evaluation, with evident implications for future digital-health trails and rehabilitation.

Some studies have demonstrated an association between low and high body mass index (BMI) and an increased risk of dementia. However, only a few of these studies were performed in rural areas.

This cross-sectional study investigated the associations between BMI and cognitive impairment among community-dwelling older adults from rural and urban areas.

8,221 older persons enrolled in the Hubei Memory & Ageing Cohort Study (HMACS) were recruited. Sociodemographic and lifestyle data, comorbidities, physical measurements, and clinical diagnoses of cognitive impairment were analyzed. Logistic regression was performed to assess the associations of BMI categories with cognitive impairment. A series of sensitivity analyses were conducted to test whether reverse causality could influence our results.

Being underweight in the rural-dwelling participants increased the risk of cognitive impairment. Being overweight was a protective factor in rural-dwelling participants aged 65-69 years and 75-79 years, whereas being underweight was significantly associated with cognitive impairment (OR, 1.37; 95% CI 1.03-1.83; p < 0.05). Sensitivity analyses support that underweight had an additive effect on the odds of cognitive impairment and was related to risk of dementia. Interaction test revealed that the differences between urban/rural in the relationship between BMI and cognitive impairment are statistically significant.

Associations between BMI and cognitive impairment differ among urban/rural groups. Older people with low BMI living in rural China are at a higher risk for dementia than those living in urban areas.

Associations between BMI and cognitive impairment differ among urban/rural groups. Older people with low BMI living in rural China are at a higher risk for dementia than those living in urban areas.

Use of specialists and recommended drugs has beneficial effects for older adults living with Alzheimer's disease and related dementia (ADRD). Gaps in care may exist for minorities, e.g., Blacks, and especially in the United States (U.S.) Deep South (DS), a poor U.S. region with rising ADRD cases and minority overrepresentation. Currently, we have little understanding of ADRD care utilization in diverse populations in this region and elsewhere in the U.S. (non-DS), and the factors that adversely impact it.

To examine utilization of specialists and ADRD drugs (outcomes) in racial/ethnic groups of older adults with ADRD and the personal or context-level factors affecting these outcomes in DS and non-DS.

We obtained outcomes and personal-level covariates from claims for 127,512 Medicare beneficiaries with ADRD in 2013-2015, and combined county-level data in exploratory factor analysis to define context-level covariates. Adjusted analyses tested significant association of outcomes with Black/White race and other factors in DS and non-DS.

Across racial/ethnic groups, 33%-43% in DS and 43%-50% in non-DS used specialists; 47%-55% in DS and 41%-48% in non-DS used ADRD drugs. In adjusted analyses, differences between Blacks and Whites were not significant. Vascular dementia, comorbidities, poverty, and context-level factor "Availability of Medical Resources" were associated with specialist use; Alzheimer's disease and senile dementia, comorbidities, and specialist use were associated with drug use. In non-DS only, other individual, context-level covariates were associated with the outcomes.

We did not observe significant gaps in ADRD care in DS and non-DS; however, research should further examine determinants of low specialist and drug use in these regions.

We did not observe significant gaps in ADRD care in DS and non-DS; however, research should further examine determinants of low specialist and drug use in these regions.

The transition from mild cognitive impairment (MCI) to dementia is of great interest to clinical research on Alzheimer's disease and related dementias. This phenomenon also serves as a valuable data source for quantitative methodological researchers developing new approaches for classification. Sotrastaurin supplier However, the growth of machine learning (ML) approaches for classification may falsely lead many clinical researchers to underestimate the value of logistic regression (LR), which often demonstrates classification accuracy equivalent or superior to other ML methods. Further, when faced with many potential features that could be used for classifying the transition, clinical researchers are often unaware of the relative value of different approaches for variable selection.

The present study sought to compare different methods for statistical classification and for automated and theoretically guided feature selection techniques in the context of predicting conversion from MCI to dementia.

We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to evaluate different influences of automated feature preselection on LR and support vector machine (SVM) classification methods, in classifying conversion from MCI to dementia.