Power, Melinda C.

Abstract There is an urgent need to improve dementia ascertainment robustness in real-world studies assessing drug effects on dementia risk. We developed algorithms to dementia identification algorithms using Medicare claims (inpatient/outpatient/prescription) from 3318 Visit 5 (2011-2013) and 1828 Visit 6 (2016-2017) participants of the Atherosclerosis Risk in Communities (ARIC) Study, validated against ARIC's rigorous syndromic dementia classification. Algorithm performance was compared to existing algorithms (Jain, Bynum, Lee). We further evaluated algorithms effectiveness in a 20% random Medicare sample aged ≥70 years who initiating liraglutide or dipeptidyl peptidase 4 inhibitors (DPP4i) to assess 3-year adjusted risk difference (aRD) for dementia. Our incident dementia algorithm required two dementia diagnostic codes within 1-year, or one dementia code plus a new dementia prescription within 90 days. It achieved a positive predictive value (PPV) of 69.2%, specificity of 99.0%, and sensitivity of 34.6% (population prevalence: 8.8%), comparable to extant algorithms (PPV, 58.7–68.6%; sensitivity 25.5–40.4%). Prevalent dementia algorithm (without requiring incident diagnoses/prescriptions) demonstrated similar performance. In the Medicare sample, dementia risk ranged from 3.0% to 12.5%, aRD comparing liraglutide to DPP4i varied −1.2% to −3.6%, with our algorithm closely matching the Bynum algorithm. Algorithm selection significantly impacts treatment effect estimates, highlighting its importance in in pharmacoepidemiologic research.

Importance SARS-CoV-2 infection has been linked to neurotoxic effects and cognitive deficits. Objective To determine whether decreases in cognitive function were accelerated after SARS-CoV-2 infection compared with individuals not infected. Design, Setting, and Participants Multicenter, prospective cohort study from 2016 to 2022 among 3525 participants alive on March 1, 2020, and enrolled in The Atherosclerosis Risk in Communities (ARIC) study and the Collaborative Cohort of Cohorts for COVID-19 Research study who completed a prepandemic cognitive assessment and a pandemic-era assessment of SARS-CoV-2 infection. Final analyses performed in November 2024. Exposure SARS-CoV-2 infection determined via self-report of a positive SARS-CoV-2 test or health care professional diagnosis of COVID-19, a positive SARS-CoV-2 antinucleocapsid antibody response, or presence of an administrative code for COVID-19 on medical records. Main outcomes and measures A neuropsychological battery assessed multiple cognitive domains, and a cocalibrated confirmatory factor analysis generated factor scores for global cognitive function. The primary outcome was the rate of excess change in cognitive function. Results The 3525 eligible participants had a mean (SD) age of 80.8 (4.7) years, 2085 (59.1%) were female, 752 (21.4%) were Black, and 2773 (78.6%) were White. SARS-CoV-2 infection was detected among 307 participants (8.7%), 103 of whom (33.6%) were hospitalized. Among uninfected participants, the mean annualized change in cognitive function was −0.09 (95% CI, −0.13 to −0.04). Compared with this rate, change was faster (β = −0.06; 95% CI, −0.09 to −0.02) among participants hospitalized for infection, but not different from participants who were infected but not hospitalized (β = 0.00; 95% CI, −0.02 to 0.03). The association among participants hospitalized for infection was evident in the cognitive domains of memory and executive function, but not language. Conclusions and relevance This cohort study of older participants found accelerated decreases in cognition among individuals hospitalized for SARS-CoV-2 infection, but not nonhospitalized infection, in comparison with individuals not yet infected.

AbstractBackgroundPharmacoepidemiologic studies assessing drug effectiveness for Alzheimer’s disease and related dementias (ADRD) are increasingly popular given the critical need for effective therapies for ADRD. To meet the urgent need for robust dementia ascertainment from real‐world data, we aimed to develop a novel algorithm for identifying incident and prevalent dementia in claims.MethodWe developed algorithm candidates by different timing/frequency of dementia diagnosis/treatment to identify dementia from inpatient/outpatient/prescription claims for 6,515 and 3,997 participants from Visits 5 (2011‐2013; mean age 75.8 (SD 5.3) years) and 6 (2016‐2017; mean age 79.8 (SD 4.8) years) of the ARIC cohort with ≥ 1‐year continuous Medicare Part A & B enrollment prior to each visit. We evaluated algorithm performance (sensitivity/specificity/positive predictive value (PPV)/negative predictive value (NPV)) against the gold standard of the ARIC dementia classification based on an extensive battery of neurocognitive tests administered at each visit. We compared performance of the new algorithm with that of three existing algorithms (Jain, Bynum, Lee) and their relaxed forms (4‐year window, dementia diagnosis plus a depression diagnosis or dementia evaluation procedure, ignoring code position) to identify incident (n = 90 at V6) and prevalent dementia (n = 190 at V5; n = 160 at V6).ResultThe newly developed primary algorithm requires presence of a dementia diagnosis code followed by another diagnosis code within 1 year (under condition that the following non‐specific ICD‐9 diagnostic codes, 290.40, 290.41, 290.11, 290.3, should appear no more than once), or a subsequent dementia treatment prescription within 90 days (requiring Medicare Part D enrollment ≥ 6 months). The PPV of the new algorithm in the identification of incident dementia was PPV of 72.7%, with a specificity of 99.1%, outperforming existing algorithms. Its sensitivity of 38.7% and NPV of 96.2% were comparable to those achieved by existing algorithms. Sensitivity analysis restricting to ICD‐10 diagnostic codes increased the PPV and attenuated its sensitivity by 6%. Similar comparative performance was observed in the identification of prevalent dementia.ConclusionA novel algorithm for identifying dementia from Medicare claims, developed using linked ARIC‐Medicare data, outperforms previous algorithms and stands as a valuable tool in the assessment of ADRD drugs from real‐world data.

Background White matter hyperintensities (WMH) and their progression are associated with risk of dementia and stroke, so are an important target for clinical trials. The cost of broad magnetic resonance imaging (MRI) screening to identify eligible individuals, however, limits the feasibility of designing clinical trials targeting WMH. A low‐cost retinal or clinical screening measure before MRI could reduce recruitment costs versus an MRI‐only screening design in a hypothetical clinical trial. Methods and Results Data from the Atherosclerosis Risk in Communities study with valid retinal and WMH measurements ( N =1311) were used. To identify a population at greater likelihood of significant WMH on MRI and thus reduce the number of screening MRIs required, we evaluated 3 theoretical prescreening measures: (1) retinal, (2) clinical, (3) combined clinical‐retinal. Given a target sample for clinical trials ( N =646), we calculated screening sample sizes based on the proportion within the population having an elevated score for each prescreening measure (separately) multiplied by the proportion of significant WMH among those with that prescreening feature. Recruitment costs were calculated using estimated retinal and MRI cost estimates. Compared with the estimated cost of MRI‐only screening (>$4.24 million, requiring MRI on 6526 participants), prescreening for a high clinical score resulted in total cost of $2.47 million, with an initial screening group of 52 778 participants, with MRI in 3801. A high clinical‐retinal score cutoff resulted in costs of $2.9 million while requiring 13 572 participants, with 3801 completing MRI. Conclusions A 2‐stage design with low‐cost prescreening measures is a promising approach, resulting in reduced theoretical recruitment costs compared with an MRI‐only design.

Background: White matter hyperintensities (WMH) are associated with risk of dementia and stroke, so are an important therapeutic target for clinical trials. The cost of broad MRI screening to identify those individuals with significant WMH, however, limits the feasibility of designing clinical trials which target WMH presence and which test treatments that slow progression. Hypothesis: A low-cost retinal or clinical screening measure prior to an MRI screening stage reduces the cost of recruiting persons with significant WMH burden in a hypothetical clinical trial vs an MRI-only screening design. Method: Data were from participants in the Atherosclerosis Risk in Communities-Neurocognitive study with clinical, retinal and WMH measurements ( N = 1311) at ages 53-70 years. Significant WMH burden was defined as a Cardiovascular Health Study score >2. Three low-cost pre-screening measures were assessed: (1) retinal: a score incorporating multiple markers of abnormal retinal vasculature, (2) clinical: a score incorporating hypertension, diabetes, and age, (3) combined retinal-clinical: a score incorporating retinal and clinical factors. Given a prior published target sample for a WMH clinical trial (N= 646), we calculated a theoretical screening sample size based on the proportion of each pre-screening measure in the population multiplied by the proportion of significant WMH burden among those with a prevalent pre-screening feature. Total recruitment cost was calculated using standard retinal ($32.50) and MRI ($650) cost estimates. Results: Compared to the estimated cost of MRI-only screening (>$4.24M, requiring MRI screening 6,526 participants), pre-screening for a high clinical score reduced total cost to $2.47M, but increased the initial screening group to 52,778 participants, of whom 3,801 would be screened by MRI). A high retinal-clinical score cutoff reduced costs to $2.9M while only requiring 13,572 screened participants (of these only 3,801 would require MRI). Conclusion: A 2-stage recruitment design with a low-cost pre-screening retinal and clinical measure is a promising approach, resulting in a reduction of theoretical recruitment costs for recruiting persons with significant WMH burden compared to an MRI-only design.

AbstractBackgroundDementia disproportionately impacts people of color in the U.S.. Whether these disparities are due to differences in vascular risk factors, cognitive reserve, or AD pathophysiology remains unclear.MethodBlack and White participants from four U.S. communities were recruited into the Atherosclerosis Risk in Communities (ARIC) study at ages 45‐64. Vascular risk factors were evaluated in midlife and at multiple visits over 30+ years, as were markers of cognitive reserve, with expert classification of dementia. In participants with brain MRI, brain volumes were evaluated in association with dementia. In nondemented participants in the ARIC‐PET ancillary study, florbetapir PET scans were used to quantify brain cortical amyloid; differences in levels by race, vascular risk factors, and white matter hyperintensities (WMH) were evaluated.ResultIn 15744 ARIC participants, dementia was more common in Black vs White participants. Although midlife vascular risk factors were related to dementia, the impact of these risk factors on dementia risk and cortical volumes didn’t differ by race. Lower education was nonsignificantly more strongly associated with dementia in Blacks vs Whites, and an APOE e4 allele was more strongly associated with dementia in Whites. In ARIC‐PET (N=322), vascular risk factors from midlife were associated with PET amyloid, without similar associations for late‐life risk factors; these associations did not significantly differ by race. WMH volume was more strongly associated (cross‐sectionally) with PET amyloid in Blacks vs Whites, but differences were not statistically significantly different. Finally, Blacks had an over two‐fold increased odds of elevated florbetapir PET vs Whites, independent of vascular risk factors, demographics, WMH volume, cognitive status, and APOE genotype.ConclusionConsideration of racial disparities in dementia should consider vascular risk, cognitive reserve, and social determinants of health, across the life course. Vascular risk factors do not appear to differentially impact dementia risk or brain amyloid in Blacks vs Whites, but the greater prevalence of these risk factors in Blacks must be considered. Although the A/T/N framework may clarify underlying biology contributing to Alzheimer’s disease, inclusion of these additional factors is needed to understand and reduce racial disparities in dementia rates.

Introduction: Small vessel disease is associated with decreased cognitive function, possibly differential by race. Age-related central arterial stiffening increases pulsatility resulting in hypoperfusion, microvascular damage and remodeling in the brain, potentially impairing cognition. We examined if arterial stiffness and pressure amplification are associated with lacunar infarcts and greater volumes of white matter hyperintensities (WMH) in a sample of Caucasian and African American (AA) older adults. Methods: We analyzed a cross-sectional sample of ARIC participants aged 67-90 years (n=1486) from visit 5 (2011-2013), with brain magnetic resonance imaging (MRI). The Omron VP-1000 Plus was used to measure aortic stiffness (carotid-femoral pulse wave velocity [cfPWV]) and pressure amplification measures (pulse pressure amplification [PPA], central pulse pressure [cPP], and estimated central systolic blood pressure [cSBP]). Aortic stiffness and pressure amplification were dichotomized at race-specific 25th percentile cut points. Brain MRI using 3D-1.5T equipment quantified the presence of lacunar infarcts and volumes of WMH following a standardized protocol. Logistic regression, adjusted for age, sex, education, ApoE4, heart rate, smoking and body mass index, was used to quantify the odds of lacunar infarcts in participants with high vs. low cfPWV, cPP, cSBP, and low vs. high PPA. Linear regression models, additionally adjusted for intracranial volume, estimated the difference in log-transformed volumes of WMH among participants with high vs. low cfPWV, cPP, cSBP, and low vs. high PPA. Probability sampling weights for an MRI were included to allow for generalizability to the full visit 5 cohort. Results: Among the 1486 participants with a brain MRI (mean age: 76, 41% male, 26% AA), measures of aortic stiffness and pressure amplification were associated with lacunar infarcts in Caucasians, but not in AAs. Caucasian participants with a high cfPWV had greater odds of lacunar infarcts (Odds Ratio [OR] =2.02, 95% confidence interval [CI]: 1.23, 2.20). Caucasians with high cSBP had higher odds of lacunar infarcts (OR=1.72, 95% CI: 1.10, 2.69). In Caucasians, high cfPWV was associated with a 21% (95% CI: 6, 38) greater volume of WMH as compared to a low cfPWV; high cSBP was associated with a 28% (95% CI: 14, 45) greater volume of WMH compared to a low cSBP. In AAs, high cfPWV was associated with a 32% (95% CI: 7, 62) greater volume of WMH as compared to low cfPWV. Cerebral microvascular imaging markers did not differ quantitatively with measures of PPA and cPP. Conclusions: Central arterial stiffening and pressure amplification are plausible microvascular contributors to cognitive aging, providing new information on modifiable pathways for previously observed associations between cardiovascular disease risk factors and the rates of cognitive decline and dementia among older adults.

Background: Brain infarcts, white matter hyperintensities (WMH), and brain atrophy appear to contribute to the development of mild cognitive impairment (MCI) and dementia in selected populations, but few prospective studies are available in general populations. Methods: The study included 732 black and white participants, sampled from the original ARIC cohort, who had 3T brain Magnetic Resonance Imaging (MRI) scans, were free of MCI and dementia during 2011-13 (Visit 5), and were evaluated for cognitive impairment during 2016-17 (Visit 6, about 90% complete). We assessed the associations of brain infarcts, WMH, and brain volumes measured on MRI from 2011-2013 with incident MCI and dementia (combined), diagnosed using a computer algorithm based on specified criteria and comprehensive assessment at Visit 6. We used logistic regression, incorporating sampling weights, to evaluate the risk for incident MCI/dementia with adjustment for demographic covariates, major dementia risk factors, and history of cardiovascular diseases. Results: Participants had a median age of 75 (IQR: 71, 79) at Visit 5 (baseline); 62% (453) were female and 33% (242) were African American. There were 156 newly identified cases of MCI or dementia during a median follow-up time of 4.9 (IQR: 3.4, 5.2) years. The presence of any brain infarct was associated with a nonsignificantly higher risk of MCI/dementia (OR: 1.50; 95%CI: 0.87 to 2.58), but the only significant individual association was with cortical infarcts (OR: 1.99; 95%CI: 1.03 to 3.85). WMH volume above the median value was nonsignificantly associated with conversion to MCI/dementia. Smaller Alzheimer’s disease (AD) signature region was an independent predictor for greater risk of MCI/dementia (OR: 1.49; 95%CI: 1.00 to 2.22). A similar but nonsignificant association was observed for total brain volume. Conclusions: Brain infarcts (cortical infarcts) and lower brain volume (AD signature region), measured in community-based older residents, are risk factors for MCI and dementia incidence.

AbstractBackgroundHearing impairment is associated with cognitive decline but whether it is a cause or marker is unknown. We investigated the association of hearing impairment with brain volumes and 8‐year cognitive decline. Because the superior temporal gyrus (STG) is the location of the primary auditory cortex, we stratified results by STG volume to investigate if the association of hearing and cognition differed among participants with and without evidence of possible hearing‐related brain atrophy.MethodWe used data from 1195 community‐dwelling adults (72‐94 years, 61% female, 36% black) from the Atherosclerosis Risk in Communities Study. A composite cognitive score was created from 10 neuropsychological tests administered at 3 study visits spanning 8 years (2011‐13 to 2018‐19). Brain volumes were calculated from structural magnetic resonance imaging scans for 6 regions of interest. Pure tone air conduction hearing thresholds (frequencies 0.5‐4 kHz) were obtained in 2016‐17 and averaged, with better‐ear hearing impairment defined as an average >25 dB. Multivariable‐adjusted linear regression was used to estimate cross‐sectional differences in standardized brain volumes, adjusting for intracranial volume, demographic and clinical covariates. We estimated differences in annual rates of cognitive change by hearing impairment status adjusting for demographic and clinical covariates using linear mixed models; results were stratified by intracranial volume‐adjusted STG volume (below vs. equal to or greater than the median value).ResultThe mean STG volume difference comparing hearing impairment to normal hearing was ‐0.121 standard deviations (SD) (95% CI: ‐0.213, ‐0.028). Overall, the difference in the rate of cognitive decline associated with hearing impairment was ‐0.014 SD (‐0.023, ‐0.005). Hearing was more strongly associated with cognitive decline among participants with smaller STG volumes; rate difference, ‐0.014 SD (‐0.027, ‐0.002) compared to ‐0.008 (‐0.022, 0.006) for participants with larger STG volumes.ConclusionHearing impairment was associated with smaller brain volumes in the primary auditory region, but not with other regions. Our stratified analysis suggests that hearing treatment might be an important possible strategy to delay cognitive decline, even among participants with hearing‐related brain atrophy. Furthermore, the adverse cognitive effects of hearing impairment could potentially be mitigated if early hearing treatment can prevent STG atrophy.