Low Prevalence of Mixed Dementia in a Cohort of 2,000 Elderly Patients in a Memory Clinic Setting

Abstract

Background:

It is generally assumed that with increasing age, pathology in clinically diagnosed Alzheimer’s disease (AD) becomes more mixed, i.e., co-existence of amyloid plaques and cerebrovascular pathology.

Objective:

To test the hypothesis of increasing prevalence of mixed dementia in late-onset clinically diagnosed Alzheimer’s disease (AD) in a single-center memory clinic population.

Methods:

Patients included had diagnoses of AD (n = 832), subjective cognitive impairment (SCI, n = 333), mild cognitive impairment (MCI, n = 492), vascular dementia (VaD, n = 57), other dementia (n = 53), or other diagnosis (n = 233). Prevalence of severe white matter lesions (WML) was defined as a score of 2 or higher on the Fazekas-scale on brain computed tomography to classify AD patients as having mixed dementia. We examined the effect of age on WML using multiple linear regression analysis, and AD patients were compared to SCI to determine the effect of disease on WML.

Results:

Prevalence of severe WML was 33.6% in AD patients (mixed dementia), 11.4% in SCI, 22.7% in MCI, 75.4% in VaD, 3.8% in other dementia, and 15.5% in other diagnosis. With increasing age there was a significant and similar increase of WML scores in SCI, MCI, AD, other dementia, and other diagnosis, indicating no effect modification by AD. The difference between AD patients and SCI averaged 0.16 on the WML score and difference in percentage severe WML between AD and SCI patients was 15% across all ages.

Conclusion:

We found a low prevalence of mixed dementia. Furthermore, severe WML in AD was largely explained by age rather than effect of disease.

Keywords

Alzheimer’s disease computed tomography Fazekas score memory clinic white matter lesions

INTRODUCTION

White matter lesions (WML) on brain imaging are considered indicators of cerebral small vessel disease [1]. In healthy elderly individuals, WML increase with advancing age and play a role in cognitive function and dementia [2]. Alzheimer’s disease (AD) has been associated with presence of cerebrovasculardisease (CVD) [3]. Accordingly, prevalence of WML is higher in AD patients than in normal controls and may have prognostic value in terms of cognitive decline and mortality [4]. The frequent finding of combined Alzheimer-type and cerebrovascular pathologies in older demented individuals suggests a heterogeneous etiology in the contribution of dementia as a clinical syndrome [5]. This suggestion comes from autopsy studies in very elderly patients reporting multiple brain pathologies in patients with dementia compared to non-demented subjects [6, 7]. In a large unselected community-based neuropathology study, cerebrovascular and Alzheimer–type pathology were common, 78% and 70% , respectively, and small vessel disease was found in 69% of individuals, being the most common cerebrovascular feature [8]. However, subjects in these population-based or community autopsy studiesdo not represent regular clinical practice, thereby limiting the interpretation of results for clinicians and memory clinic populations.

The vascular hypothesis of AD [9, 10] is based on the notion that vascular risk factors play a role in the etiology of AD and that vascular disease and Alzheimer-type pathology are interrelated. Reciprocally synergistic mechanisms could promote both pathologies and thus enhance risk of dementia [11]. Since both pathologies increase with age, based on this vascular hypothesis, one might expect that prevalence of WML and mixed dementia, defined as presence of both neuro degenerative and vascular pathology on neuro imaging, will be high in older populations from regular clinical practice. To date, few studies are available to test this hypothesis. In fact, no studies have been reported investigating the presence of cerebrovascular disease, including WML, and cerebral or lacunar infarcts in large groups of unselected very late-onset dementia patients presenting in a memory clinic. Insight in these possible vascular mechanisms in AD is of great importance as they may lead to treatment strategies in the prevention of vascular abnormalities.

To test the hypothesis of increasing prevalence of clinically defined mixed dementia in old age, we investigated the prevalence of CVD in a large group of elderly patients from a single-center memory clinic population. With focus on clinically diagnosed AD, we determined prevalence of moderate to severe WML in relation to age and we investigated both the effect of age on WML and the effect of disease on presence of WML relative to patients with SCI. We compared the effect of age on WML in AD patients to other diagnostic groups in this population and we hypothesized that the age effect is modulated by AD as diagnosis. With respect to the disease effect of AD in relation to the vascular hypothesis, we expected the prevalence of CVD to be higher in AD than in SCI, but also that this difference would increase in very late-onset AD (patients over 80 years old).

METHODS

Subjects

Patients included in this study were referred with cognitive complaints to the memory clinic at Tergooi Hospital, a general hospital in Blaricum, TheNetherlands. Since April 2009, we use a standard protocol for diagnostic assessment, modified from [5]. For this study all patients evaluated from April 2009 to April 2015 were included, resulting in a consecutive series of 2, 000 patients. Each patient received the same diagnostic work-up in one day, resulting in a total of close to 350 patients per year. All patients underwent a clinical examination by both a neurologist and a geriatrician. The local Medical Ethics Committee approved the protocol of this study.

Clinical diagnostic procedures

The following diagnostic evaluation was completed by all subjects: 1) full medical and neurological examination including history taking by neurologist or geriatrician, 2) assessment of vital functions, 3) cognitive screening with CAMCOG test part of the CAMDEX [12] and Visual Association Test (VAT [13], 4) standard ECG, 5) laboratory tests, 6) informant based history and assessment of needs by specialized nurse including admission of the Geriatric Depression Scale (GDS) [14], assessments of the IADL scale [15]. The clinical diagnosis was made in a consensus meeting attended by the neurologist, geriatrician, neuropsychologist, and a specialized nurse. We employed standard clinical diagnostic criteria for MCI [16] and AD [17]. Mixed dementia was defined as a clinical diagnosis of AD combined with vascular abnormalities on imaging including a Fazekas score [18] of 2 or higher (see CT imaging protocol). The diagnosis of VaD was made in accordance with current criteria when vascular abnormalities on CT were thought to be primary responsible for the cognitive decline such as stepwise progression or acute onset of symptoms in relation to cerebral infarcts, or a subcortical clinical picture combined with severe WML [19]. Other types of dementia, including dementia with Lewy bodies (DLB, [20]) frontotemporal dementia (FTD, [21]) and cognitive deficits associated with Parkinson’s disease or Parkinson’s disease dementia [22], were diagnosed according to current criteria and clustered in one group as “other dementia”. Patients received the diagnosis of psychiatric disorder when psychiatric disease was considered the most likely cause of their memory complaints or cognitive function abnormalities, including depression. Psychiatric disease was combined with other neurological diagnoses (including cognitive abnormalities in relation to alcoholism) in one group as “other diagnosis”. If patients scored normal on all tests and none of the previous mentioned diagnoses could be made, patients were considered as subjective cognitive impairment (SCI).

Vascular risk factors

Presence of vascular risk factors was recorded and defined as history of hypertension (yes/no), diabetes mellitus (yes/no), hyperlipidemia (yes/no), transient ischemic attack (TIA) or stroke (yes/no), atrial fibrillation (yes/no), and smoking (current smoker yes/no).

Computed tomography protocol

CT scanning of the brain was performed using a 64-detector row CT with Siemens Somatom definition AS 64 slice scanner according to a CT brain protocol for the memory clinic (260 mAs, 120 kV, 64 * 0.6 mm collimation, pitch of 0.55, WC / WW = 40 / 80, CARE kV = on (dose optimation slider on non-contrast)). Oblique coronal, sagittal, and transversal reconstructions were made with bonewindow 1.5 mm slices, axial slices of 5.0 mm, and oblique coronal slices of 3.0 mm, modified from the protocol described by Wattjes et al. [23].

All CT scans were reviewed by a radiologist. CT scans were visually assessed for WML by applying the 4 point rating scale from 0 to 3 described by Fazekas et al. [18] in a consensus meeting by a neurologist and geriatrician (JJC, DH, MS, WvM, LS). Presence of lacunar infarcts and large vessel infarcts was determined.

Statistical analysis

We used SPSS version 22.0. Baseline demographics were compared with one-way analysis of variance (ANOVA) with post-hoc tests or Chi-square tests where appropriate. Analyses were divided in three parts.

First, we determined the prevalence of mixed dementia and we compared vascular abnormalities on CT between diagnostic groups. Prevalence ofmoderate to severe WML or lacunar and hemispheric infarcts were compared using Chi-square tests, and WML scores were compared using one-way ANOVA. As previously described, we dichotomized WML scores into “no or mild” with scores ranging from 0 to 1, versus “moderate to severe” with scores including 2 or 3 on the Fazekas scale.

Second, we determined the effect of age on WML and whether this relation was modified by AD asdisease. This disease modification was considered as a parameter of neurodegenerative versus vascular interaction. We used linear regression analysis to determine the relationship between age and WML scores in separate diagnostic categories, with age entered as independent variable, with adjustment for gender, education, and global dementia severity with CAMCOG total score, and WML score entered as continuous dependent variable. Additional regression analysis was performed with adjustment for vascular risk factors including presence of hypertension, diabetes, smoking, and hyperlipidemia.

Third, we used the SCI patients as reference group for AD to quantify the disease effect on WML. Comparison of SCI and AD patients with regard to WML scores was conducted with analysis of covariance with adjustment for age. Then, the difference between AD and SCI patients was expressed in years of aging in SCI patients using the following analysis. Multiple linear regression was performed for combined groups of AD and SCI, entering age and diagnosis as independent variables, adjusted for gender, education as covariates, and WML scores as continuous variable. This allows assessment of the independent effects of age and diagnosis on WML. The disease effect of AD on the WML scale relative to SCI was expressed in years of aging in SCI patients and calculated by the ratio of the regression coefficients. Finally, to further investigate the disease effect of AD, we calculated the difference in percentage of moderate to severe WML between AD and SCI. To determine if this difference between AD and SCI changed with age, we stratified this by age, in those under 80 years, and those of 80 years and above.

RESULTS

Patients

The distribution of diagnoses is shown in Fig. 1; n = 333 (16.7%) had SCI, n = 492 (24.6%) MCI, n = 832 (41.6%) were diagnosed as AD of which n = 278 (33.6% of the AD patients) were classified as mixed dementia. Only 2.9% received the diagnosis of VaD, 2.8% other dementia (1.1% DLB, 0.7% FTD, and 1.0% cognitive deficits associated with PD), and 11.7% other diagnosis (2.0% alcohol, 5.6% psychiatric diagnosis, 4.1% ‘another neurological diagnosis’). Of all patients diagnosed with dementia, 88.3% was diagnosed as AD, and this percentage was dependent on age rising to 93.4% after 80 years.

Mean age of the total population was 78.2 years (range 45–96 years) (see Table 1). Except for VaD, AD patients were significantly older (mean age 81.8 years) and had significantly lower MMSE scores than any of the other diagnoses (all at p < 0.001). AD patients had significantly lower education than SCI (p < 0.05).

With regard to vascular risk factors and AD (Table 1), percentage of presence of hypertensionwas significantly higher compared to SCI (p < 0.001), percentage of history of TIA lower than VaD (p < 0.01), and percentage of smoking lower than other dementia (p < 0.001).

Imaging: prevalence of vascular abnormalities (Table 2)

AD patients showed significantly different WML scores and percentage of presence of WML score of 2 or higher than any of the other diagnostic categories (all at p < 0.001). Looking at prevalence of moderate to severe WML, values are reported for each diagnostic category with overall prevalence values stratified for age below and above 80 years of age. Patients with VaD showed more moderate to severe WML than any of the diagnoses (all at p < 0.001).

For AD, prevalence was 33.6% , indicating that 33.6% of the AD patients were classified as mixed dementia and that the vast majority of AD, namely 66.4% , had no or mild WML. This prevalence was strongly dependent on age: a prevalence of 78.8% of noor mild WML was demonstrated in AD under 80 years compared to 60.6% for AD patients aged over 80 years. Women showed higher prevalence of moderate to severe WML than men in all diagnostic categories, but none of these differences were statistically significant.

Presence of other vascular abnormalities on CT was significantly higher in VaD than any of the other diagnoses for both lacunar infarcts (p < 0.001) and hemispheric infarcts (p < 0.001). Prevalence values of lacunar (5.8%) and hemispheric infarcts (13.2%) were low in AD and did not increase with advancing age. For comparison of AD versus other diagnostic groups and significance values, see Table 2.

WML: effect of age

Multiple linear regression analysis was used to determine the relation between age and WML scores in the different patient groups. A significant increase with advancing age in WML score was shown for SCI (regression coefficient 0.032±0.004, p < 0.001), MCI (0.023±0.006, p < 0.001), AD (0.032±0.004, p < 0.001), other dementia (0.028±0.01, p < 0.01), and other diagnosis (0.034±0.005, p < 0.01), but not for VaD. Figure 2 shows regression lines for patients with SCI, MCI, and AD. Regression coefficients were very similar among the diagnostic groups, and indicated that with increase of 10 years there is an increase of 0.3 in WML score. The effect of age on the WML score was thus not modified by AD. Regression coefficients did not alter with additional adjustments for presence of hypertension, diabetes, smoking and hyperlipidemia. There were no statistically significant differences between men and women in either of these analyses.

WML: effect of disease

To determine the relative disease effect of AD versus SCI as reference group, the difference was calculated with regression analysis adjusted for age. AD patients showed only a 0.16 higher score on the WML scale than SCI patients. The analysis to express the AD disease effect in years of aging in SCI patients showed regression coefficients of 0.032 (p < 0.001) for age and 0.147 for diagnosis (p < 0.001) (SCI versus AD), indicating that the effect of AD diagnosis on the WML score expressed in years of aging in the SCI patients is 4.8 years (0.147/0.032).

Subsequently, AD patients were compared to SCI patients as reference group calculating the difference in percentage of moderate to severe WML, stratified for age. A similar difference in prevalence of moderate to severe WML for those under 80 years (21.2% versus 7.5%) and above 80 years (39.4% versus 24.1%) of 13.7% and 15.3% was shown (Fig. 3 shows WML scores from 0 to 3 per age category for AD and SCI patients). In other words, considering the prevalence in SCI as an age effect in an elderly memory clinic population, around 15% of moderate to severe WML prevalence is demonstrated to be attributableto AD.

DISCUSSION

We found a prevalence of mixed dementia of 33.6% , defined as presence of moderate to severe WML in clinically diagnosed AD patients, in a large memory clinic population. In addition, we found a strong relation between age and WML severity, comparable over all diagnostic categories. AD patients showed more severe WML than all other diagnostic subgroups in this population, except for VaD by definition. However, the disease effect of AD relative to SCI appeared to be rather small, expressed as difference in WML score or in prevalence of moderate to severe WML. Furthermore, prevalence of cerebral and lacunar infarcts was low and did not increase with age.

We tested the vascular hypothesis of AD [11 , 25] and expected a high prevalence of mixed dementia in our old aged memory clinic population based on previous neuropathology studies [26 –28]. On the contrary, we found a low prevalence of mixed dementia in our AD patients. Although the prevalence was strongly dependent on age, the vast majority of AD patients, even above 80 years, demonstrated limited vascular abnormalities on CT, illustrated by no or only mild WML in 80% of AD patients aged under 80 years versus 61% in patients above 80 years. Presence of large vessel cerebral infarcts and lacunar infarcts was also low in AD and did not increase with age, in agreement with earlier studies [7]. Differences between our prevalence figures and prevalence of mixed dementia in some autopsy population-based studies, reasonably estimated at 6–12% [29], are likely explained bydefinitions of diagnostic criteria and study population. Comparison of our findings to other clinical studies is difficult since few data are available of WML prevalence in other memory clinic populations with specifications of data according to different diagnoses. One memory clinic study showed a relation between vascular risk factors and WML severity but diagnosis was not specified [30].

Prevalence of moderate to severe WML in older AD patients in our study was largely explained by an age effect rather than an effect of AD as a disease. Indeed, the age effect on WML scores in AD was comparable to other diagnostic groups and thus not modified by AD. Using the SCI patients as reference group, AD patients had higher WMC scores with stable differences across age, but this difference adjusted for age was very small being only 0.16 on the WML score. In addition, the AD disease effect had an equivalent of only 4.8 years of aging in SCI patients. A similar picture emerged when prevalence of moderate to severe WML in AD was compared to SCI patients. In absolute values, this difference was statistically significant, in agreement with earlier studies [31, 32], but was around 15% before and after 80 years old. Relative to SCI, the percentage of AD attributed prevalence in WML not explained by aging was thus only 15% , even at high age.

To our knowledge this is the first and largest study reporting prevalence of WML in a memory clinic sample of late-onset AD patients from one single center. Few studies investigated the relation between vascular disease on imaging in a memory clinic testing the vascular hypothesis of AD at clinical level. We are aware of only one memory clinic study testing the hypothesis of increased prevalence and severity of CVD in AD compared to non-AD patients, and in line with our findings the authors could not find a relation between AD biomarkers and CVD, the vascular hypothesis could not be confirmed [33].

Pathogenic mechanisms suggest that there is not a synergistic effect of CVD and AD pathology, but that these factors are additive [34, 35]. The issue is still under debate, as other reports suggest that AD and CVD are interrelated [11, 24]. Our results lend support for the absence of interaction of neurodegenerative and vascular mechanisms from a clinical perspective. We emphasize that our study does not disprove a vascular contribution to AD, since presence of WML may lower the threshold for diagnosing AD as a clinical diagnosis in memory clinic patients. Further, no AD biomarkers were available in our study to show that the patients diagnosed with AD, were in fact cases of subcortical vascular dementia. However, misclassifying patients with clinical AD and moderate to severe WML but AD biomarker negative would result inoverestimation of the prevalence of mixed dementia rather than underestimating it.

One of the main strengths of the present study consists of the very large group of consecutively referred and therefore unselected population of a single-center memory clinic in a general hospital. Many reports describe tertiary or academic based cohorts and therefore are less representative for general clinical practice. In addition, our population is old in comparison to many other memory clinic investigations (for example The Amsterdam Dementia Cohort [36]), which offersa unique opportunity to study prevalence of cerebrovascular abnormalities in very late onset AD. Furthermore, our elderly unselected patients appeared to be mildly to moderately demented and probably in a relatively early disease stage, indicated by a mean MMSE of 22 with a mean age of 78 years. In agreement with earlier findings, even at high age, a reasonable amount of patients was considered as SCI [37]. Of the 2, 000 consecutively patients included in this study, 53% did not receive a dementia diagnosis. One explanation for the low prevalence of vascular disease in our cohort might be selection bias, as possibly patients with high vascular burden are less able to visit the hospital or are directly admitted to nursing homes without prior visit to a memory clinic.

Given the superior sensitivity of MRI in the detection of WML, it is possible that we underestimate WML prevalence in our AD patients. However, visual ratings of the WML scale have been shown to be comparable between a 64 slice CT scanner and MRI [23]. In addition, specificity of CT may be higher for WML detection than MRI, indicating that WML seen on CT are more likely to be vascular in origin [38]. When discordant results between CT and MRI were observed, MRI scores were higher but almost always discrepancy was between a score of 0 on CT versus a score of 1 on MRI on the Fazekas scale [23] resulting in a low risk of underestimating moderate to severe WML using our CT scan protocol, defined as a score of 2 or higher on the Fazekas scale. Smaller vascular lesions will be undetected by the present CT study and WML may be associated with these smaller lesions [39]. Although smaller vascular lesions including microinfarcts and small punctuate WML may have little clinical relevance [4], presence of lobar and nonlobar microbleeds in AD are associated with mortality [40], but microbleeds and lacunes are not associated with clinical progression in subjects with SCI [41]. The definitive clinical importance of these smaller vascular lesions and their role in the definition of mixed dementia has yet to be established.

Another possible issue of concern is the use of SCI as reference group. The SCI group may contain patients with increased risk for cognitive or functional decline [42, 43], with special reference to presence of WML [40]. Indeed, WML prevalence may be lower in a ‘real’ control group and the possibility that we underestimate the difference in WML prevalence between AD and SCI patients cannot be excluded. However, the mean age of the patients from the Benedictus study [41] is 10 years younger and age related prevalence of moderate to severe WML is 7.5% (patients under 80, Table 2) in our cohort versus 13.4% in the Amsterdam Dementia Cohort. Our SCI patients probably represent a relatively unselected population, likely explained by differences in referral, and the problem of underestimating WML prevalence may less play a role. In addition, Benedictus et al. are the first to report a link between severity of WML and clinical progression in subjective cognitive decline subjects from a memory clinic and these results need to be confirmed in other populations.

Our study may have several clinical implications. First, the strong relation between age and WML suggests that prevention of cerebrovascular disease manifested by vascular abnormalities on CT is an important therapeutic target, especially to prevent these abnormalities in individuals above 80 years. Indeed, when prevalence of all WML is considered in our study, most individuals above 80 years have a score of 1 or higher on the WML scale (see Fig. 3) and could therefore benefit from preventive treatment at younger age. A recent review [4] emphasized that WML in the elderly are most likely due to ischemia, supported by recent serial MRI studies suggesting that WML are due to “silent” stroke [44], which add on to previous studies from LADIS [45]. Thus, these findings do not disprove the vascular contribution to AD and should encourage re-evaluation of the contribution of cerebrovascular (especially small vessel) disease and hence its treatment and prevention. Second, when clinicians observe moderate to severe WML on CT imaging in AD patients, our study suggests that this mostly reflects the effect of age rather than a specific correlate of the vascular hypothesis of AD. The specific effects of WML on cognitive function were not investigated in this report and need further study, especially in relation to specific contributions of cerebrovascular diseaseand neurodegeneration and possible interaction on memory and non-memory functions.

DISCLOSURE STATEMENT

Authors’ disclosures available online (http://j-alz.com/manuscript-disclosures/15-0796r1).

References

Schmidt

, Schmidt

, Haybaeck

, Loitfelder

, Weis

, Cavalieri

, Seiler

, Enzinger

, Ropele

, Erkinjuntti

, Pantoni

, Scheltens

, Fazekas

, Jellinger

(2011) Heterogeneity in age-related white matter changes. ActaNeuropathol 122, 171–185.

Enzinger

, Fazekas

, Ropele

, Schmidt

(2007) Progression of cerebral white matter lesions - Clinical and radiological considerations. J Neurol Sci 257, 5–10.

de Leeuw

, de Groot

, Achten

, Oudkerk

, Ramos

, Heijboer

, Hofman

, Jolles

, van Gijn

, Breteler

(2001) Prevalence of cerebral white matter lesions in elderly people: A population based magnetic resonance imaging study. The Rotterdam Scan Study.. J Neurol Neurosurg Psychiatry 70, 9–14.

Prins

, Scheltens

(2015) White matter hyperintensities, cognitive impairment and dementia: An update. Nat Rev Neurol 11, 1557–165.

Jellinger

(2013) Pathology and pathogenesis of vascular cognitive impairment-a critical update. Front Aging Neurosci 5, 17.

Schneider

, Arvanitakis

, Bang

, Bennett

(2007) Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology 69, 2197–2204.

Chui

, Ramirez-Gomez

(2015) Clinical and imaging features of mixed Alzheimer and vascular pathologies. Alzheimers Res Ther 7, 21.

Neuropathology Group of the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS NeuropathologyGroup (2001) Pathological correlates of late-onset dementia in a multicentre, community-based population in England and Wales. Lancet 357, 169–175.

Knopman

, Roberts

(2010) Vascular risk factors: Imaging and neuropathologic correlates. J Alzheimers Dis 20, 699–709.

10.

Zlokovic

(2011) Neurovascular pathways to neurodegeneration in Alzheimer’s disease and other disorders. Nat Rev Neurosci 12, 723–738.

11.

Yarchoan

, Xie

, Kling

, Toledo

, Wolk

, Lee

, Van Deerlin

, Lee

VMY

, Trojanowski

, Arnold

(2012) Cerebrovascular atherosclerosis correlates with Alzheimer pathology in neurodegenerative dementias. Brain 135, 3749–3756.

12.

Derix

, Hofstede

, Teunisse

, Hijdra

, Walstra

, Weinstein

, van Gool

(1991) CAMDEX-N: The Dutch version of the Cambridge Examination for Mental Disorders of the Elderly with automatic data processing. Tijdschr Gerontol Geriatr 22, 143–150.

13.

Lindeboom

, Schmand

, Tulner

, Walstra

, Jonker

(2002) Visual association test to detect early dementia of the Alzheimer type. J Neurol Neurosurg Psychiatry 73, 126–133.

14.

Sheikh

, Yesavage

(1986) Geriatric Depression Scale (GDS). Recent evidence and development of a shorter version. Clin Gerontol 5, 165–173.

15.

Gélinas

, Gauthier

, McIntyre

, Gauthier

(1999) Development of a functional measure for persons with Alzheimer’s disease: The disability assessment for dementia. Am J Occup Ther 53, 471–481.

16.

Petersen

, Smith

, Waring

, Ivnik

, Tangalos

, Kokmen

(1999) Mild cognitive impairment: Clinical characterization and outcome. Arch Neurol 56, 303–308.

17.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

, Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 263–269.

18.

Fazekas

, Chawluk

, Alavi

(1987) MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. Am J Neuroradiol 8, 421–426.

19.

Román

, Tatemichi

, Erkinjuntti

, Cummings

, Masdeu

, Garcia

, Amaducci

, Orgogozo

, Brun

, Hofman

(1993) Vascular dementia: Diagnostic criteria for research studies: Report of the NINDS-AIREN International Workshop. Neurology 43, 250–260.

20.

McKeith

, Dickson

, Lowe

, Emre

, O’Brien

, Feldman

, Cummings

, Duda

, Lippa

, Perry

, Aarsland

, Arai

, Ballard

, Boeve

, Burn

, Costa

, Del Ser

, Dubois

, Galasko

, Gauthier

, Goetz

, Gomez-Tortosa

, Halliday

, Hansen

, Hardy

, Iwatsubo

, Kalaria

, Kaufer

, Kenny

, Korczyn

, Kosaka

, Lee

VMY

, Lees

, Litvan

, Londos

, Lopez

, Minoshima

, Mizuno

, Molina

, Mukaetova-Ladinska

, Pasquier

, Perry

, Schulz

, Trojanowski

, Yamada

(2005) Diagnosis and management of dementia with Lewy bodies: Third report of the DLB consortium. Neurology 65, 1863–1872.

21.

Rascovsky

, Hodges

, Knopman

, Mendez

, Kramer

, Neuhaus

, Van Swieten

, Seelaar

, Dopper

EGP

, Onyike

, Hillis

, Josephs

, Boeve

, Kertesz

, Seeley

, Rankin

, Johnson

, Gorno-Tempini

, Rosen

, Prioleau-Latham

, Lee

, Kipps

, Lillo

, Piguet

, Rohrer

, Rossor

, Warren

, Fox

, Galasko

, Salmon

, Black

, Mesulam

, Weintraub

, Dickerson

, Diehl-Schmid

, Pasquier

, Deramecourt

, Lebert

, Pijnenburg

, Chow

, Manes

, Grafman

, Cappa

, Freedman

, Grossman

, Miller

(2011) Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 134, 2456–2477.

22.

Emre

, Aarsland

, Brown

, Burn

, Duyckaerts

, Mizuno

, Broe

, Cummings

, Dickson

, Gauthier

, Goldman

, Goetz

, Korczyn

, Lees

, Levy

, Litvan

, McKeith

, Olanow

, Poewe

, Quinn

, Sampaio

, Tolosa

, Dubois

(2007) Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Mov Disord 22, 1689–1707.

23.

Wattjes

, Henneman

WJP

, van der Flier

, de Vries

, Träber

, Geurts

JJG

, Scheltens

, Vrenken

, Barkhof

(2009) Diagnostic imaging of patients in a memory clinic: Comparison of MR imaging and 64-detector row CT. Radiology 253, 174–183.

24.

Erten-Lyons

, Woltjer

, Kaye

, Mattek

, Dodge

, Green

, Tran

, Howieson

, Wild

, Silbert

(2013) Neuropathologic basis of white matter hyperintensity accumulation with advanced age. Neurology 81, 977–983.

25.

Honig

, Kukull

, Mayeux

(2005) Atherosclerosis and AD: Analysis of data from the US National Alzheimer’s Coordinating Center. Neurology 64, 494–500.

26.

Stephan

BCM

, Matthews

, Ma

, Muniz

, Hunter

, Davis

, McKeith

, Foster

, Ince

, Brayne

(2012) Alzheimer and vascular neuropathological changes associated with different cognitive states in a non-demented sample. J Alzheimers Dis 29, 309–318.

27.

Kövari

, Gold

, Herrmann

, Canuto

, Hof

, Michel

, Bouras

, Giannakopoulos

(2004) Cortical microinfarcts and demyelination significantly affect cognition in brain aging. Stroke 35, 410–414.

28.

Sonnen

, Larson

, Haneuse

, Woltjer

, Li

, Crane

, Craft

, Montine

(2009) Neuropathology in the adult changes in thought study: A review. J Alzheimers Dis 18, 703–711.

29.

Jellinger

(2007) The enigma of mixed dementia. Alzheimers Dement 3, 40–53.

30.

Lazarus

, Prettyman

, Cherryman

(2005) White matter lesions on magnetic resonance imaging and their relationship with vascular risk factors in memory clinic attenders. Int J Geriatr Psychiatry 20, 274–279.

31.

Barber

, Scheltens

, Gholkar

, Ballard

, McKeith

, Ince

, Perry

, O’Brien

(1999) White matter lesions on magnetic resonance imaging in dementia with Lewy bodies, Alzheimer’s disease, vascular dementia, and normal aging. J Neurol Neurosurg Psychiatry 67, 66–72.

32.

de Leeuw

, Barkhof

, Scheltens

(2004) White matter lesions and hippocampal atrophy in Alzheimer’s disease. Neurology 62, 310–312.

33.

Spies

, Verbeek

, Sjogren

MJC

, Claassen

JAHR

(2014) Alzheimer Biomarkers and Clinical Alzheimer disease were not associated with increased cerebrovascular disease in a memory clinic population. Curr Alzheimer Res 11, 40–46.

34.

Launer

, Hughes

, White

(2011) Microinfarcts, brain atrophy, and cognitive function: The Honolulu Asia Aging Study Autopsy Study. Ann Neurol 70, 774–780.

35.

Chui

, Zheng

, Reed

, Vinters

(2012) Vascular risk factors and Alzheimer’s disease: Are these risk factors for plaques and tangles or for concomitant vascular pathology that increases the likelihood of dementia? An evidence-based review. Alzheimers Res Ther 4, 1.

36.

van der Flier

, Pijnenburg

YAL

, Prins

, Lemstra

, Bouwman

, Teunissen

, van Berckel

BNM

, Stam

, Barkhof

, Visser

, van Egmond

, Scheltens

(2014) Optimizing patient care and research: The Amsterdam Dementia Cohort. J Alzheimers Dis 41, 313–327.

37.

Lehrner

, Moser

, Klug

, Gleiß

, Auff

, Dal-Bianco

, Pusswald

(2014) Subjective memory complaints, depressive symptoms and cognition in patients attending a memory outpatient clinic. Int Psychogeriatr 26, 463–473.

38.

Scheltens

, Erkinjunti

, Leys

, Wahlund

, Inzitari

, del Ser

, Pasquier

, Barkhof

, Mäntylä

, Bowler

, Wallin

, Ghika

, Fazekas

, Pantoni

(1998) White matter changes on CT and MRI: An overview of visual rating scales. European Task Force on Age-Related White Matter Changes. Eur Neurol 39, 80–89.

39.

Longstreth

Jr , Sonnen

, Koepsell

, Kukull

, Larson

, Montine

(2009) Associations between microinfarcts and other macroscopic vascular findings on neuropathologic examination in 2 databases. Alzheimer Dis Assoc Disord 23, 291–294.

40.

Benedictus

, Prins

, Goos

, Scheltens

, Barkhof

, van der Flier

(2015) Microbleeds, mortality, and stroke in Alzheimer’s disease: The Mistral Study. JAMA Neurol 72, 539–545.

41.

Benedictus

, van Harten

, Leeuwis

, Koene

, Scheltens

, Barkhof

, Prins

, van der Flier

(2015) White matter hyperintensities relate to clinical progression in subjective cognitive decline. Stroke 46, 2661–2664.

42.

Schmand

, Jonker

, Hooijer

, Lindeboom

(1996) Subjective memory complaints may announce dementia. Neurology 46, 121–125.

43.

Slavin

, Sachdev

, Kochan

, Woolf

, Crawford

, Giskes

, Reppermund

, Trollor

, Draper

, Delbaere

, Brodaty

(2015) Predicting cognitive, functional, and diagnostic change over 4 years using baseline subjective cognitive complaints in the Sydney Memory and Ageing Study. Am J Geriatr Psychiatry 23, 906–914.

44.

Conklin

, Silver

, Mikulis

, Mandell

(2014) Are acute infarcts the cause of leukoaraiosis? Brain mapping for 16 weeks consecutive weeks. Ann Neurol 76, 899–904.

45.

Gouw

, van der Flier

, Pantoni

, Inzitari

, Erkinjuntti

, Wahlund

, Waldemar

, Schmidt

, Fazekas

, Scheltens

, Barkhof

, Study LADIS, Group (2008) On the etiology of incident brain lacunes: Longitudinal observations from the LADIS study. Stroke 39, 3083–3085.