Pattern Recognition to Identify Stroke in the Cognitive Profile: Secondary Analyses of a Prospective Cohort Study

Modelling of longitudinal data to predict cardiovascular disease risk: a methodological review

OBJECTIVE

The identification of methodology for modelling cardiovascular disease (CVD) risk using longitudinal data and risk factor trajectories.

METHODS

We screened MEDLINE-Ovid from inception until 3 June 2020. MeSH and text search terms covered three areas: data type, modelling type and disease area including search terms such as "longitudinal", "trajector*" and "cardiovasc*" respectively. Studies were filtered to meet the following inclusion criteria: longitudinal individual patient data in adult patients with ≥3 time-points and a CVD or mortality outcome. Studies were screened and analyzed by one author. Any queries were discussed with the other authors. Comparisons were made between the methods identified looking at assumptions, flexibility and software availability.

RESULTS

From the initial 2601 studies returned by the searches 80 studies were included. Four statistical approaches were identified for modelling the longitudinal data: 3 (4%) studies compared time points with simple statistical tests, 40 (50%) used single-stage approaches, such as including single time points or summary measures in survival models, 29 (36%) used two-stage approaches including an estimated longitudinal parameter in survival models, and 8 (10%) used joint models which modelled the longitudinal and survival data together. The proportion of CVD risk prediction models created using longitudinal data using two-stage and joint models increased over time.

CONCLUSIONS

Single stage models are still heavily utilized by many CVD risk prediction studies for modelling longitudinal data. Future studies should fully utilize available longitudinal data when analyzing CVD risk by employing two-stage and joint approaches which can often better utilize the available data.

Elevated C-Reactive Protein in Alzheimer's Disease without Depression in Older Adults: Findings from the Health and Retirement Study

We examined the association between differential diagnoses of major stroke and probable Alzheimer's disease (AD) and Mixed AD on c-reactive protein (CRP) in older adults with and without depression. Secondary data analyses examined associations between blood-based measures of probable peripheral inflammation using CRP collected from dried blood spots in the Health and Retirement Study (HRS), a nationally representative sample of individuals aged 50 and older. A validated pattern recognition algorithm was utilized to identify cognitive decline indicative of probable AD, Mixed AD, and major stroke. Negative binomial regressions were utilized to model concentrations of serologic CRP. On average, participants (N=4,601) were 70 years old, female, and non-Hispanic white. Mixed AD participants had 0.26 mg/dL increase in CRP compared to unimpaired participants, controlling for demographics, health behaviors and comorbidities. Those with Mixed AD had 2.14 times increased odds of having high CRP (OR=2.14; [1.19-3.85]). In analyses stratified by depression, adults with Mixed AD and without depression had an additional 0.37 mg/dL increase in CRP (SE=0.06; p<0.001) compared to unimpaired adults. Those with AD without depression had an 0.20 mg/dL increase in CRP (SE=0.07; p<0.01). Age was not associated with increased CRP in non-depressed older adults. Depressed adults with major stroke had a -0.26 mg/dL decrease in CRP (SE=0.11; p=0.02), controlling for hypertension, alcoholic drinks/beverages per week and smoking status. Concentration modeling revealed that participants with major stroke, probable AD and probable mixed AD without depression had significantly higher CRP concentrations when compared to unimpaired older adults.

Incidence of Mild Cognitive Impairment, Conversion to Probable Dementia, and Mortality

BACKGROUND

Few studies have jointly estimated incidence of MCI, conversion to probable dementia, and mortality in a nationally representatie sample.

METHODS

We used data from six waves of the National Health and Aging Trends Study (2011-2016). Multivariable-adjusted multi-state survival models (MSMs) were used to model incidence upon accounting for misclassification.

RESULTS

A total of 6,078 eligible NHATS participants were included (average age: 77.49 ± 7.79 years; 58.42% females; 68.99% non-Hispanic white). The incidence of MCI was estimated to be 41.0 [35.5, 47.3]/1,000 person-years (PY). Participants converted to probable dementia at a high rate of 241.3 [189.6, 307.0]/1,000 PY, though a small number also reverted from MCI to cognitively normal. Education was associated with lower incidence of MCI and conversion to probable dementia, but increased mortality in those with MCI. There were also substantial racial and ethnic disparities in the incidence of MCI and dementia.

CONCLUSIONS

Our results underscore the relatively common incidence of and conversions between MCI and dementia in community-dwelling older Americans and uncover the beneficial impact of education to withstand cognitive impairment before death.

The Characteristics of Social Network Structure in Later Life in Relation to Incidence of Mild Cognitive Impairment and Conversion to Probable Dementia

BACKGROUND

Larger, more active social networks are estimated to be associated with lower risks of cognitive decline. However, roles of various social relationships in a broad social network in protecting against cognitive decline remain to be elucidated.

OBJECTIVE

We aimed to investigate how social roles within a social network and number of social network members are associated with cognitive decline.

METHODS

Six waves of National Health and Aging Trends Study (2011-2016, NHATS) were utilized to examine the development of mild cognitive impairment (MCI) and probable dementia determined using validated criteria. Multivariable-adjusted multi-state survival models were used to model incidences and transitions, jointly with misclassification errors.

RESULTS

A total of 6,078 eligible NHATS participants were included (average age: 77.49±7.79 years; female: 58.42%; non-Hispanic white: 68.99%). Multivariable-adjusted analyses revealed that having more social network members was associated with lower hazards of conversion from MCI to probable dementia (adjusted Hazard Ratio; aHR = 0.82; 95%confidence intervals; 95%CI = [0.67-0.99]), meanwhile having at least one college-educated family member within a social network was associated with lower incidence of probable dementia (aHR = 0.37 [0.26-0.51]). Having at least one friend within a social network was associated with a lower hazard of incidence of probable dementia (aHR = 0.48 [0.33-0.71]), but a higher risk of mortality in the MCI group (aHR = 2.58 [1.47-4.51]).

CONCLUSION

Having more social network members, having at least one friend, and having at least one college-educated family member within a social network, were associated with lower risks of incidence of dementia or conversion from MCI to dementia.

Pattern Recognition to Objectively Differentiate the Etiology of Cognitive Decline: Analysis of the Impact of Stroke and Alzheimer's Disease

BACKGROUND

Undetected Alzheimer's disease (AD) and stroke neuropathology is believed to account for a large proportion of decline in cognitive performance that is attributed to normal aging. This study examined the amount of variance in age-related cognitive change that is accounted for by AD and stroke using a novel pattern recognition protocol.

METHOD

Secondary analyses of data collected for the Health and Retirement Study (N = 17,579) were used to objectively characterize patterns of cognitive decline associated with AD and stroke. The rate of decline in episodic memory and orientation was the outcome of interest, while algorithms indicative of AD and stroke pathology were the predictors of interest.

RESULTS

The average age of the sample was 67.54 ± 10.45 years at baseline, and they completed, on average, 14.20 ± 3.56 years of follow-up. After adjusting for demographics, AD and stroke accounted for approximately half of age-associated decline in cognition (51.07-55.6% for orientation and episodic memory, respectively) and explained variance attributed to random slopes in longitudinal multilevel models.

DISCUSSION

The results of this study suggested that approximately half of the cognitive decline usually attributed to normal aging are more characteristic of AD and stroke.