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Aims The 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations. Methods and results Individuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options. Conclusion The SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk. Key objective To improve upon prediction of 10-year residual atherosclerotic cardiovascular disease (ASCVD) event risk in individuals with established ASCVD, by taking into account competing risks and geographical differences in ASCVD incidence. Key findings Derivation in 8355 individuals with established ASCVD from the Utrecht Cardiovascular Cohort-Secondary Manifestations of ARTerial disease (SMART) cohort. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] to 0.772 (95% CI 0.659-0.886). Clinical utility was demonstrated across a range of treatment thresholds relevant to therapy intensification. Take-home messages The SMART2 risk score can be used to estimate 10-year residual risk of fatal and non-fatal ASCVD in individuals with established ASCVD. Adapted to the CVD incidence in several global regions. Facilitates shared decision-making on Step 2 prevention goals as recommended by the 2021 ESC Guidelines on cardiovascular prevention.

BACKGROUND AND PURPOSE: The clinical relevance of cortical microinfarcts has recently been established; however, studies on microinfarcts in the deep gray matter are lacking. We examined the risk factors and MR imaging correlates of microinfarcts in the deep gray matter on 7T MR imaging and their relation to cognitive functioning.\MATERIALS AND METHODS: Within the Second Manifestations of ARTerial disease?Magnetic Resonance (SMART-MR) study, 213 patients (mean age, 68 [SD, 8]?years) had a risk-factor assessment, 7T and 1.5T brain MR imaging, and a cognitive examination. Microinfarcts on 7T MR imaging were defined as lesions of < 5 mm. Regression models were used to examine the age-adjusted associations among risk factors, MR imaging markers, and microinfarcts. Cognitive function was summarized as composite and domain-specific z scores. RESULTS: A total of 47 microinfarcts were found in 28 patients (13%), most commonly in the thalamus. Older age, history of stroke, hypertension, and intima-media thickness were associated with microinfarcts. On 1.5T MR imaging, cerebellar infarcts (relative risk = 2.75; 95% CI, 1.4?5.33) and lacunes in the white (relative risk = 3.28; 95% CI, 3.28?6.04) and deep gray matter (relative risk?= 3.06; 95% CI, 1.75?5.35) were associated with microinfarcts, and on 7T MR imaging cortical microinfarcts (relative risk = 2.33; 95% CI, 1.32?4.13). Microinfarcts were also associated with poorer global cognitive functioning (mean difference in the global z score between patients with multiple microinfarcts versus none = ?0.97; 95% CI, ?1.66 to ?0.28, P = .006) and across all cognitive domains. CONCLUSIONS: Microinfarcts in the deep gray matter on 7T MR imaging were associated with worse cognitive functioning and risk factors and MR imaging markers of small-vessel and large-vessel disease. Our findings suggest that microinfarcts in the deep gray matter may represent a novel imaging marker of vascular brain injury.

Objectives. DISH has been associated with increased coronary artery calcifications and incident ischaemic stroke. The formation of bone along the spine may share pathways with calcium deposition in the aorta. We hypothesized that patients with DISH have increased vascular calcifications. Therefore we aimed to investigate the presence and extent of DISH in relation to thoracic aortic calcification (TAC) severity. Methods. This cross-sectional study included 4703 patients from the Second Manifestation of ARTerial disease cohort, consisting of patients with cardiovascular events or risk factors for cardiovascular disease. Chest radiographs were scored for DISH using the Resnick criteria. Different severities of TAC were scored arbitrarily from no TAC to mild, moderate or severe TAC. Using multivariate logistic regression, the associations between DISH and TAC were analysed with adjustments for age, sex, BMI, diabetes, smoking status, non-high-density lipoprotein cholesterol, cholesterol lowering drug usage, renal function and blood pressure. Results. A total of 442 patients (9.4%) had evidence of DISH and 1789 (38%) patients had TAC. The prevalence of DISH increased from 6.6% in the no TAC group to 10.8% in the mild, 14.3% in the moderate and 17.1% in the severe TAC group. After adjustments, DISH was significantly associated with the presence of TAC [odds ratio (OR) 1.46 [95% CI 1.17, 1.82)]. In multinomial analyses, DISH was associated with moderate TAC [OR 1.43 (95% CI 1.06, 1.93)] and severe TAC [OR 1.67 (95% CI 1.19, 2.36)]. Conclusions. Subjects with DISH have increased TACs, providing further evidence that patients with DISH have an increased burden of vascular calcifications.

Background Up to 60% of breast cancer patients treated with chemotherapy is confronted with cognitive problems, which can have a significant impact on daily activities and quality of life (QoL). We investigated whether exercise training improves cognition in chemotherapy-exposed breast cancer patients 2–4 years after diagnosis. Methods Chemotherapy-exposed breast cancer patients, with both self-reported cognitive problems and lower than expected performance on neuropsychological tests, were randomized to an exercise or control group. The 6-month exercise intervention consisted of supervised aerobic and strength training (2 h/week), and Nordic/power walking (2 h/week). Our primary outcome was memory functioning (Hopkins Verbal Learning Test-Revised; HVLT-R). Secondary outcomes included online neuropsychological tests (Amsterdam Cognition Scan; ACS), self-reported cognition (MD Anderson Symptom Inventory for multiple myeloma; MDASI-MM), physical fitness (relative maximum oxygen uptake; VO2peak), fatigue (Multidimensional Fatigue Inventory), QoL (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire; EORTC QLQ C-30), depression (Patient Health Questionnaire-9, Hospital Anxiety and Depression Scale; HADS), and anxiety (HADS). HVLT-R total recall was analyzed with a Fisher exact test for clinically relevant improvement (≥ 5 words). Other outcomes were analyzed using multiple regression analyses adjusted for baseline and stratification factors. Results We randomized 181 patients to the exercise (n = 91) or control group (n = 90). Two-third of the patients attended ≥ 80% of the exercise sessions, and physical fitness significantly improved compared to control patients (B VO2peak 1.4 ml/min/kg, 95%CI:0.6;2.2). No difference in favor of the intervention group was seen on the primary outcome. Significant beneficial intervention effects were found for self-reported cognitive functioning [MDASI-MM severity (B-0.7, 95% CI − 1.2; − 0.1)], fatigue, QoL, and depression. A hypothesis-driven analysis in highly fatigued patients showed positive exercise effects on tested cognitive functioning [ACS Reaction Time (B-26.8, 95% CI − 52.9; − 0.6) and ACS Wordlist Learning (B4.4, 95% CI 0.5; 8.3)]. Conclusions A 6-month exercise intervention improved self-reported cognitive functioning, physical fitness, fatigue, QoL, and depression in chemotherapy-exposed breast cancer patients with cognitive problems. Tested cognitive functioning was not affected. However, subgroup analysis indicated a positive effect of exercise on tested cognitive functioning in highly fatigued patients. Trial Registration Netherlands Trial Registry: Trial NL5924 (NTR6104). Registered 24 October 2016, https://www.trialregister.nl/trial/5924.

Additional file 1. Table S1. Intervention effects on cognitive functioning. Table S2. Intervention effects on cognitive functioning, per protocol. Table S3. Intervention effects, separately for patients with and without endocrine therapy. Table S4. Intervention effects, separately for patients of different age categories (30-44, 45-59, 60-75 years). Table S5. Intervention effects, separately for patients of with pre- and peri- menopausal status and patients with postmenopausal status. Table S6. Intervention effects on cognitive functioning, stratified for low versus high levels of fatigue measured with the EORTC QLQ C-30 fatigue scale. Table S7. Intervention effects on patient-reported outcomes.

Contains fulltext : 291410.pdf (Publisher’s version ) (Open Access) BACKGROUND: Physical exercise in cancer patients is a promising intervention to improve cognition and increase brain volume, including hippocampal volume. We investigated whether a 6-month exercise intervention primarily impacts total hippocampal volume and additionally hippocampal subfield volumes, cortical thickness and grey matter volume in previously physically inactive breast cancer patients. Furthermore, we evaluated associations with verbal memory. METHODS: Chemotherapy-exposed breast cancer patients (stage I-III, 2-4 years post diagnosis) with cognitive problems were included and randomized in an exercise intervention (n = 70, age = 52.5 ± 9.0 years) or control group (n = 72, age = 53.2 ± 8.6 years). The intervention consisted of 2x1 hours/week of supervised aerobic and strength training and 2x1 hours/week Nordic or power walking. At baseline and at 6-month follow-up, volumetric brain measures were derived from 3D T1-weighted 3T magnetic resonance imaging scans, including hippocampal (subfield) volume (FreeSurfer), cortical thickness (CAT12), and grey matter volume (voxel-based morphometry CAT12). Physical fitness was measured with a cardiopulmonary exercise test. Memory functioning was measured with the Hopkins Verbal Learning Test-Revised (HVLT-R total recall) and Wordlist Learning of an online cognitive test battery, the Amsterdam Cognition Scan (ACS Wordlist Learning). An explorative analysis was conducted in highly fatigued patients (score of ≥ 39 on the symptom scale 'fatigue' of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire), as previous research in this dataset has shown that the intervention improved cognition only in these patients. RESULTS: Multiple regression analyses and voxel-based morphometry revealed no significant intervention effects on brain volume, although at baseline increased physical fitness was significantly related to larger brain volume (e.g., total hippocampal volume: R = 0.32, B = 21.7 mm(3), 95 % CI = 3.0 - 40.4). Subgroup analyses showed an intervention effect in highly fatigued patients. Unexpectedly, these patients had significant reductions in hippocampal volume, compared to the control group (e.g., total hippocampal volume: B = -52.3 mm(3), 95 % CI = -100.3 - -4.4)), which was related to improved memory functioning (HVLT-R total recall: B = -0.022, 95 % CI = -0.039 - -0.005; ACS Wordlist Learning: B = -0.039, 95 % CI = -0.062 - -0.015). CONCLUSIONS: No exercise intervention effects were found on hippocampal volume, hippocampal subfield volumes, cortical thickness or grey matter volume for the entire intervention group. Contrary to what we expected, in highly fatigued patients a reduction in hippocampal volume was found after the intervention, which was related to improved memory functioning. These results suggest that physical fitness may benefit cognition in specific groups and stress the importance of further research into the biological basis of this finding.

BACKGROUND AND PURPOSE: Intracranial atherosclerosis, a major risk factor for ischemic stroke, is thought to have different atherogenic mechanisms than extracranial atherosclerosis. Studies investigating their relationship in vivo are sparse and report inconsistent results. We studied the relationship between intracranial atherosclerosis and extracranial atherosclerosis in a cohort of patients with a history of vascular disease. MATERIALS AND METHODS: Within the Second Manifestations of ARTerial disease-Magnetic Resonance (SMART) study, cross-sectional analyses were performed in 130 patients (mean age, 68 ± 9 years) with a history of vascular disease and with assessable 7T intracranial vessel wall MR imaging data. Intracranial atherosclerosis burden was defined as the number of intracranial vessel wall lesions in the circle of Willis and its major branches. Age- and sex-adjusted unstandardized regression coefficients (b-value) were calculated with intracranial atherosclerosis burden as the dependent variable and extracranial atherosclerosis markers as independent variables. RESULTS: Ninety-six percent of patients had ≥1 vessel wall lesion, with a mean intracranial atherosclerosis burden of 8.5 ± 5.7 lesions. Significant associations were observed between higher intracranial atherosclerosis burden and carotid intima-media thickness (b = 0.53 lesions per +0.1 mm; 95% CI, 0.1-1.0 lesions), 50%-100% carotid stenosis versus no stenosis (b = 6.6 lesions; 95% CI, 2.3-10.9 lesions), ankle-brachial index ≤ 0.9 versus >0.9 (b = 4.9 lesions; 95% CI, 1.7-8.0 lesions), and estimated glomerular filtration rate (b = -0.77 lesions per +10 mL/min; 95% CI, -1.50 to -0.03 lesions). No significant differences in intracranial atherosclerosis burden were found among different categories of vascular disease. CONCLUSIONS: Intracranial atherosclerosis was associated with various extracranial markers of atherosclerosis, not supporting a different etiology.

Background Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies. The effect on cardiovascular risk factor management is yet to be confirmed. Methods We performed a systematic review and meta-analysis evaluating the effects of CDSS on CVRM, defined as the change in absolute values and attainment of treatment goals of systolic blood pressure (SBP), low density lipoprotein cholesterol (LDL-c) and HbA1c. Also, CDSS characteristics related to more effective CVRM were identified. Eligible articles were methodologically appraised using the Cochrane risk of bias tool. We calculated mean differences, relative risks, and if appropriate (I2

Background: Smoking is a well-known risk factor for stroke. However, the relationship between smoking trajectories during the life course and stroke is not known. Aims: We aimed to study the association of smoking trajectories and smoked pack-years with risk of ischemic and haemorrhagic strokes in a population-based birth cohort followed up to 50 years of age. Methods: Within the Northern Finland Birth Cohort 1966, 11,999 persons were followed from antenatal period to age 50 years. The smoking behaviour was assessed with postal questionnaires at ages 14, 31 and 46 years. Stroke diagnoses were collected from nationwide registers using unique study number linkage. The associations between smoking behaviour and stroke risk were estimated using Cox regression models. Results: Six different patterns in smoking habits throughout the life course were found in trajectory modelling. During 542,140 person-years of follow-up, 352 (2.9%) persons had a stroke. Continuous smoking during the life course was associated with increased stroke risk (HR = 1.69; 95% CI 1.10–2.60) after adjusting for sex, educational level, family history of strokes, leisure-time physical activity, body mass index, alcohol consumption, hypertension, hypercholesterolemia, and diabetes. Per every smoked pack-year the stroke risk increased 1.04-fold (95% CI 1.03–1.06). Other smoking trajectories were not significantly associated with stroke risk, nor were starting or ending age of smoking. Conclusion: Accumulation of smoking history is associated with increased risk of stroke until age of 50 years. The increased stroke risk does not depend on the age at which smoking started. Given that the majority starts smoking at young age, primary prevention of strokes should focus on adolescent smoking.

OBJECTIVE: To estimate the association between hippocampal and total brain volume and the course of depressive symptoms over eight years of follow-up in patients with a history of vascular disease. METHOD: Within the SMART-Medea study, 636 participants (62 ± 10 years) had a 1.5-tesla brain MRI obtaining hippocampal and total brain volumes. Depressive symptoms were assessed with the Patient Health Questionnaire-9 biannually during eight-year follow-up. Generalized estimating equation models with robust standard errors were used to assess the associations of hippocampal and total brain volumes with depressive symptoms during follow-up adjusting for age, sex, education, and intracranial volume. An interaction term between volume and time (6-month intervals) was included to examine whether the course of depressive symptoms differed according to hippocampal and total brain volume. RESULTS: The mean PHQ-9 score was 2.8 ± 3.5. Smaller hippocampal volumes were associated with an increasing course of depressive symptom levels, while larger volumes were associated with decreasing levels (P-value interaction = 0.07). Smaller total brain volume was associated with consistently higher levels of depressive symptoms, but not with change in course of depressive symptoms (P-value interaction = 0.45). CONCLUSION: Smaller hippocampal volume but not total brain volume is associated with poorer course of depressive symptoms over eight years of follow-up.

Background Depressive symptoms and cognitive impairment often co-occur, but their interactive relationship is complex and the direction of causation is still a topic of research. We examined the influence of cognitive performance on the course of depressive symptoms during 7 years of follow-up in patients with vascular disease. Method Within the SMART-MR study, 736 patients (mean age 62 ± 10 years) had neuropsychological assessment on four cognitive domains at baseline [memory (MEM), working memory (WMEM), executive functioning (EXEC), and information processing speed (SPEED)]. Depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9) at baseline and every 6 months during 7 years of follow-up. Generalized Estimating Equation (GEE) models were used to assess the association between cognitive performance with depressive symptoms at multiple time points during follow-up. Interaction terms between the respective cognitive domains and time was included to examine if the course of depressive symptoms differed according to baseline cognitive performance. Results The GEE analyses showed no significant interactions between the respective cognitive domains and time indicating no different course of depressive symptoms according to baseline cognitive performance. Lower MEM, EXEC or SPEED, but not WMEM performance, was significantly associated with more depressive symptoms during follow-up per z score decrease: MEM [B = 0.70, 95% confidence interval (CI) 0.35-1.05]; EXEC (B = 0.88, 95% CI 0.41-1.36), and SPEED (B = 0.57, 95% CI 0.21-0.92). Conclusions Poorer cognitive performance on the domains MEM, EXEC and SPEED, but not WMEM, was associated with higher levels of depressive symptoms over 7 years of follow-up, but not with a different course of depressive symptoms over time.

Background: The reduction of major depression incidence is a public health challenge. Aim: To develop an algorithm to estimate the risk of occurrence of major depression in patients attending primary health centers (PHC). Material and Methods: Prospective cohort study of a random sample of 2832 patients attending PHC centers in Concepción, Chile, with evaluations at baseline, six and twelve months. Thirty nine known risk factors for depression were measured to build a model, using a logistic regression. The algorithm was developed in 2,133 patients not depressed at baseline and compared with risk algorithms developed in a sample of 5,216 European primary care attenders. The main outcome was the incidence of major depression in the follow-up period. Results: The cumulative incidence of depression during the 12 months follow up in Chile was 12%. Eight variables were identified. Four corresponded to the patient (gender, age, depression background and educational level) and four to patients' current situation (physical and mental health, satisfaction with their situation at home and satisfaction with the relationship with their partner). The C-Index, used to assess the discriminating power of the final model, was 0.746 (95% confidence intervals (CI = 0,707-0,785), slightly lower than the equation obtained in European (0.790 95% CI = 0.767-0.813) and Spanish attenders (0.82; 95% CI = 0.79-0.84). Conclusions: Four of the factors identified in the risk algorithm are not modifiable. The other two factors are directly associated with the primary support network (family and partner). This risk algorithm for the incidence of major depression provides a tool that can guide efforts towards design, implementation and evaluation of effectiveness of interventions to prevent major depression.

Background: There is a need for brief instruments to ascertain the diagnosis of major depressive disorder. In this study, we present the reliability, construct validity and accuracy of the PHQ-9 and PHQ-2 to detect major depressive disorder in primary care.Methods: Cross-sectional analyses within a large prospective cohort study (PREDICT-NL). Data was collected in seven large general practices in the centre of the Netherlands. 1338 subjects were recruited in the general practice waiting room, irrespective of their presenting complaint. The diagnostic accuracy (the area under the ROC curve and sensitivities and specificities for various thresholds) was calculated against a diagnosis of major depressive disorder determined with the Composite International Diagnostic Interview (CIDI).Results: The PHQ-9 showed a high degree of internal consistency (ICC = 0.88) and test-retest reliability (correlation = 0.94). With respect to construct validity, it showed a clear association with functional status measurements, sick days and number of consultations. The discriminative ability was good for the PHQ-9 (area under the ROC curve = 0.87, 95% CI: 0.84-0.90) and the PHQ-2 (ROC area = 0.83, 95% CI 0.80-0.87). Sensitivities at the recommended thresholds were 0.49 for the PHQ-9 at a score of 10 and 0.28 for a categorical algorithm. Adjustment of the threshold and the algorithm improved sensitivities to 0.82 and 0.84 respectively but the specificity decreased from 0.95 to 0.82 (threshold) and from 0.98 to 0.81 (algorithm). Similar results were found for the PHQ-2: the recommended threshold of 3 had a sensitivity of 0.42 and lowering the threshold resulted in an improved sensitivity of 0.81.Conclusion: The PHQ-9 and the PHQ-2 are useful instruments to detect major depressive disorder in primary care, provided a high score is followed by an additional diagnostic work-up. However, often recommended thresholds for the PHQ-9 and the PHQ-2 resulted in many undetected major depressive disorders.

BACKGROUND: The links between depression and increased mortality risk in older persons may depend on the severity of the depressive disorder and on gender. AIM: To investigate the links between severe and 'mild' depressive syndromes and excess mortality in elderly men and women, living in their own homes. METHOD: Depression (GMS-AGECAT) was assessed in 4051 older persons. After a period of six years we checked the official death registers to find out how many of theses persons had died. The mortality risk for neurotic and psychotic depression was calculated after adjustment for demographic variables, physical illness, cognitive decline and functional disabilities. RESULTS: At the six-year follow-up 75% of the men and 41% of the women with psychotic (severe) depression were found to have died. In both men and women psychotic depression was associated with significantly higher-than-normal mortality. Neurotic (mild) depression was associated with a 1.67-fold higher mortality risk in men only. CONCLUSIONS: In the elderly, severe depressive syndromes increase the risk of death in both men and women, whereas mild depression increases the risk of death only in men.

OBJECTIVE: To investigate whether the association between APOE-epsilon4 and memory decline is modified by baseline cognition and age in a population-based elderly sample.METHODS: The study sample consisted of 1,243 subjects, 62 to 85 years old, with a Mini-Mental State Examination (MMSE) score between 21 and 30 and known APOE phenotypes. Memory performance was measured with an abbreviated Auditory Verbal Learning Test (AVLT) at baseline and repeated after 3 years (n = 854). Memory decline was defined as a decrease of at least 1 SD from the mean change score on immediate recall (IR), delayed recall (DR), and retention, based on the AVLT.RESULTS: Multivariate logistic regression analyses showed that APOE-epsilon4 is associated with memory decline in cognitively impaired subjects (MMSE score, 21 to 26) (OR for decline on IR adjusted for age, sex, education, and baseline recall score, 3.8; 95% CI, 1.4 to 10.0; adjusted OR for decline on DR, 2.9; 95% CI, 1.2 to 7.0; adjusted OR for decline on retention, 3.3; 95% CI, 1.1 to 10. 1), but not in cognitively normal subjects (MMSE score, 27 to 30) (adjusted OR for decline on IR, 1.1; 95% CI, 0.6 to 2.0; adjusted OR for decline on DR, 1.0; 95% CI, 0.6 to 1.8; adjusted OR for decline on retention, 1.5; 95% CI, 0.7 to 3.0). In particular, cognitively impaired epsilon4 carriers older than 75 years were at high risk of memory decline (adjusted OR for decline on IR, 4.5; 95% CI, 1.4 to 13.8; adjusted OR for decline on DR, 3.6; 95% CI, 1.2 to 10.8; adjusted OR for decline on retention, 6.6; 95% CI, 1.5 to 29.7).CONCLUSIONS: APOE-epsilon4 was associated with memory decline in subjects with cognitive impairment, but not in normally functioning subjects. Contrary to AD studies, our study suggests that the risk of APOE-epsilon4 on memory decline does not decrease at higher ages.