Memory assessment is a key factor for the diagnosis of cognitive impairment. However, memory performance over time may be quite heterogeneous within diagnostic groups. To identify latent trajectories in memory performance and their associated risk factors, we analyzed data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants who were classified either as cognitively normal or as Mild Cognitive Impairment (MCI) at baseline and were administered the Rey Auditory Verbal Learning test (RAVLT) for up to 9 years. Group-based trajectory modeling on the 30-minute RAVLT delayed recall score was applied separately to the two baseline diagnostic groups. There were 219 normal subjects with mean age 75.9 (range from 59.9 to 89.6) and 52.5% male participants, and 372 MCI subjects with mean age 74.8 (range from 55.1 to 89.3) and 63.7% male participants included in the analysis. For normal subjects, six trajectories were identified. Trajectories were classified into three types, determined by the shape, each of which may comprise more than one trajectory: stable (~30% of subjects), curvilinear decline (~ 28%), and linear decline (~ 42%). Notably, none of the normal subjects assigned to the stable stratum progressed to dementia during the study period. In contrast, all trajectories identified for the MCI group tended to decline, although some participants were later re-diagnosed with normal cognition. Age, sex, and education were significantly associated with trajectory membership for both diagnostic groups, while APOE ɛ4 was only significantly associated with trajectories among MCI participants. Memory trajectory is a strong indicator of dementia risk. If likely trajectory of memory performance can be identified early, such work may allow clinicians to monitor or predict progression of individual patient cognition. This work also shows the importance of longitudinal cognitive testing and monitoring.

The Medical Outcomes Study Questionnaire Short Form 36 health survey (SF-36) measures health-related quality of life (HRQoL) from the individual’s po

Background: The Medical Outcomes Study Questionnaire Short Form 36 health survey (SF‐36) measures health‐related quality of life (QOL) from the patient’s point of view and is an indicator of overall health status. QOL measures may show differential changes over time prior to dementia onset.Methods: We analyzed data from the Prevention of Alzheimer’s Disease (AD) by Vitamin E and Selenium (PREADViSE) trial, which recruited 7,547 non‐demented men between 2002 and 2009. A subset of 2,746 PREADViSE participants who completed up to five SF‐36 assessments at annual visits were included in the current analysis. Two summary scores were generated for analysis: physical component score (PCS) and mental component score (MCS), each with a mean 50 with standard deviation of 10. Linear mixed models (LMM) were applied to determine how SF‐36 scores varied over time and by eventual dementia status. Cox proportional hazards regression was used to determine if the baseline SF‐36 scores were associated with dementia incidence, adjusting for baseline age, race, APOE‐4 status, diabetes, and self‐reported memory complaint at baseline.Results: The mean of MCS at baseline for subjects with dementia diagnosis later (mean± SD: 53.86±9.47) was significantly lower than for subjects without dementia diagnosis (mean± SD: 56.42±6.48) (p = 0.005), while the means of PCS at baseline (Dementia: 49.31±7.93 vs. Non‐dementia: 49.77±7.81) were not significantly different (p = 0.54). The LMM analysis showed a significant effect only for time in PCS. For MCS, the indicator for dementia was significantly associated with poorer self‐reported mental health after adjusting baseline age, black race, and memory complaint. Given adjustments for other risk factors, results from the Cox model showed that a 10‐unit increase in MCS was associated with a 44% decrease in the hazard of a future dementia diagnosis (95% CI: 32%‐55%).Conclusion: The SF‐36 MCS summary score may be a predictor for future dementia and could be useful in longitudinal dementia research.

Purpose: The purpose of this article was to describe the validity and reliability of the Fun and Social Engagement Evaluation (FUSE) developed to evaluate and measure social engagement displayed by nursing home residents during Bingocize. The FUSE combines health care worker observation and a resident self-report measure to produce a score that represents a resident's total engagement. Method: To describe validity, trained health care workers who implement Bingocize were surveyed about the items on the FUSE. Visual inspection of bar graphs of responses to survey questions were used to determine content validity. To assess reliability of the FUSE, nursing home residents were evaluated by trained research assistants. Test–retest reliability of the participant scores 1 week apart was determined with the bivariate correlation (Pearson product–moment correlation coefficient). Results: For validity, the majority of survey respondents indicated that the behaviors were representative of nursing home residents during Bingocize. For reliability, there was moderate–strong test–retest reliability over 1 week ( r = .60). Interrater reliability between two raters observing eight participants across two sessions was significant, κ = .68 (95% CI [.504,.848]), p < .0001. Conclusion: Results offer evidence that the FUSE is a valid and reliable method for determining social engagement during Bingocize.

Background: Previous studies have shown that SF36 summary scores predict incident dementia. However, it is unclear whether SF36 summary scores follow different temporal trajectories. Thus, the goal of this study is to examine possible trajectories for SF36 summary scores.Method: A subset of 2,746 Prevention of Alzheimer’s Disease (AD) by Vitamin E and Selenium (PREADViSE) participants who completed SF‐36 assessments at annual visits was included in the current analysis. First, group‐based trajectory modeling (GBTM) was applied to fit SF‐36 Mental Component summary (MCS) scores and Physical Component Summary (PCS) scores. The final models were selected based on perceptions of interpretability and reproducibility with the assistance of the Bayesian information criterion (BIC). Then joint trajectory modeling was used to examine overlaps between trajectory groups based on MCS scores and trajectory groups based on PCS scores.Result: Four trajectories were identified for each of MCS and PCS, when examined separately. In terms of shape, MCS trajectories were described as stable (∼81.3% of subjects), curvilinear decline (∼ 4.3%), linear decline (∼ 11.2%) and slight increase (∼ 3.2%), while PCS trajectories were described as stable (∼48.7%) and slight decline (∼51.3% encompassing three groups). Joint trajectory modelling showed overlaps suggesting that MCS and PCS trajectories are not independent.Conclusion: Both MCS scores and PCS scores showed multiple trajectories over time; some were stable, and some exhibited decline. We were also able to estimate how many subjects belonged to each group and to quantify overlaps in group membership for MCS and PCS scores.

Dementia has a significant impact on individuals, families, communities, and the economy. Alzheimer’s disease (AD) accounts for 60–80% of dementia cases. The APOE e4 allele is well known as the primary genetic risk factor for AD and dementia. Studies have also shown that sleep apnea increases the risk of dementia. Some research further suggests a possible interaction between sleep apnea and the APOE in dementia development; however, this relationship remains unclear. The purpose of this study is to synthesize evidence from the existing literature and report findings on the relationship between APOE, sleep apnea, and dementia. A systematic search of multiple databases was conducted using selected keywords. Articles were screened and selected according to predefined inclusion criteria. Only original, peer-reviewed articles published between 2000 and 2021 in English were included. Data from the included studies were extracted and summarized descriptively, including information on population characteristics, study design, key findings, and other relevant variables. Of the 328 records identified, 3 studies met inclusion criteria and were included in the final analysis. Their findings suggest a potential interaction between sleep apnea and APOE that may influence dementia risk. This review highlights the need for further research to clarify the role of sleep apnea in the APOE pathway and its contribution to dementia.