Neuropsychological features of mildcognitive impairment and preclinicalAlzheimer’s disease

The concept of the boundary between normalaging and very early or mild Alzheimer’s disease(AD) has become an area of interest for boththeoretical and practical reasons. This is based onthe assumption that mild cognitive deficits, partic-ularly in the area of memory, are the precursors tothe cognitive dysfunction that characterizes AD.Therefore, identification of early clinical AD hasbecome an important public health priority as newtreatments have emerged (1–3).

Mild cognitive impairment (MCI) refers to atransitional state between the cognition of normalaging and very mild AD. Several studies haveindicated that MCI individuals are at an increasedrisk for developing AD, ranging from 1% to 25%per year (4); 24% of MCI patients progressed toAD in 2 years (2) and 20% over 3 years (5),whereas a recent study indicated that the progres-sion of MCI subjects was 55% in 4.5 years (1). Arelatively long preclinical stage of dementia hasbeen demonstrated, corresponding to a stage of the

disease at which the pathology begins to have somerepercussions on cognitive functioning, but whencognitive impairments are still not sufficient for thedementia criteria to be reached (6).

In the past 20 years, several authors haveattempted to find neuropsychological predictorsof progression to AD. Collectively, these studiesemphasize the need for the clinician to detect theearliest signs of cognitive impairment. This practiceparameter is important to determine whetherscreening at-risk subjects in a specific settingleads to the diagnosis of dementia (7). Within thisresearch context, specification of certain neuropsy-chological tests for the identification of MCI willcertainly ensure comparability at this experimentalstage as well as cross-national estimates of preval-ence, incidence, risk, and associated morbidity.

The value of neuropsychological measures inhelping to identify very early cases of dementia hasbeen documented by both cross-sectional andlongitudinal studies. More specifically, deficits in

Arnaiz E, Almkvist O. Neuropsychological features of mild cognitiveimpairment and preclinical Alzheimer’s disease.Acta Neurol Scand 2003: 107 (Suppl. 179): 34–41.� Blackwell Munksgaard 2003.

Recent research has identified a transitional state between the cognitivechanges of normal aging and Alzheimer’s disease (AD), known as mildcognitive impairment (MCI). MCI patients experience memory loss toa greater extent than one would expect for age, yet they do not meetcurrently accepted criteria for clinically probable AD. An issuecurrently under investigation is whether MCI represents the preclinicalstages of AD or a distinct and static cognitive aetiology. In an attemptto address this issue, the present investigations are adopting aconvergent approach to the detection of preclinical AD, where multiplerisk factors are considered when making a diagnosis. Currently, one ofthe most important tools when assessing early cognitive changes isneuropsychological evaluation. MCI subjects typically recordneuropsychological performance between that of healthy olderindividuals and demented patients. Tests assessing new learning,delayed recall and attention ⁄ executive function seem to providevaluable information for screening and diagnosis of MCI and early ADif interpreted properly. Recommendations concerning methodologicalissues and the early management of neuropsychological MCI studieswere made.

Eva Arn�iz, Ove Almkvist1

Karolinska Institutet, Department of ClinicalNeuroscience, Occupational Therapy, and Elderly CareResearch (NEUROTEC), Division of Geriatric Medicine,Huddinge University Hospital, Huddinge, Sweden;1Department of Psychology, Stockholm University,Sweden

Key words: neuropsychological testing; mild cognitiveimpairment; Alzheimer's disease; preclinical; cognition

Eva Arn.iz ⁄ Ove Almkvist, Division of GeriatricMedicine, Huddinge University Hospital, B-84,S-141 86 Huddinge, SwedenTel.: +46 8585 82889Fax: +46 8585 85470e-mail: Ove.Almkvist@neurotec.ki.se

Acta Neurol Scand 2003: 107 (Suppl. 179): 34–41Printed in UK. All rights reserved

Copyright � Blackwell Munksgaard 2003

ACTA NEUROLOGICASCANDINAVICAISSN 0065-1427

34

measures of verbal episodic memory are commonlyreported in these patients, while other cognitivefunctions (e.g. language, praxis, and executivefunctions) seem to be spared. However, it is notclear whether all subjects with memory impairmentwill develop AD, or whether the absence of memoryimpairment excludes subsequent AD (8). In anycase, neuropsychological testing procedures shouldbe as comprehensive as possible in their assessmentof cognitive functioning in elderly people towardsexpectations of greater competence.

The aim of the current paper is to address theissue of the existing knowledge that pertains to thepreclinical cognitive markers in early dementiaand MCI. We will review studies that use neuro-psychological data longitudinally and cross-sectionally, and present the state-of the-art in thisarea of research.

Neuropsychological predictors of preclinical ADand MCI

Neuropsychological measures are routinely used toquantify the degree of cognitive impairment inpatients with dementia and are likely to beparticularly helpful early in the course of adementing illness when functional and behaviouraldisturbances are absent. The majority of longitud-inal studies report deficits in verbal episodicmemory in preclinical AD patients. This might berelatively mild and comparable with what is foundin many normal elderly individuals and memorytasks.

Longitudinal clinical studies

When reviewing the literature, we observed thatneuropsychological measures found to be predic-tors of AD are not completely homogeneous acrossstudies, and some of the most important longitud-inal studies found different cognitive predictors inpreclinical AD.

Using a logistic regression model, Masur et al.(9) found that verbal episodic memory measuredwith delayed recall, visual episodic memory meas-ured with WAIS Digit Symbol (10), and semanticmemory measured by verbal fluency were the bestpredictors in the Bronx cohort. Similarly, in theAging Project (North Manhattan), Jacobs et al.(11) used a Cox regression analysis and only verbalepisodic measured by immediate recall in theSelective Reminding Test and Boston NamingTest (12) and semantic memory (WAIS-R Similar-ities) (10) were significantly and independentlyassociated with increased risk of subsequent ADdiagnosis. In the Framingham Cohort, Linn et al.

(13) used stepwise regression procedures andshowed that only verbal episodic memory couldaccurately predict cognitive progression in preclin-ical AD. Five years later, Elias et al. (14) increasedthe 55 subjects in Linn et al.’s study (13) to 109patients and considerably amplified the surveil-lance period. The pattern of tests predictingpreclinical AD was similar to those reported byLinn et al. With one exception. Elias et al. did notfind that lower Digit Span Test (10) scores wereprotective with regard to the development of AD.This could be due to Linn et al.’s smaller sample ofstudy participants and the difference in follow-uptime in both studies.

In a recent study on MCI subjects, Petersen (16)reported impairments that were as severe as thoseseen in mild AD. However, the same MCI group’sperformance on measures assessing other cognitivedomains (naming, executive functions, etc.) wasequivalent to that of healthy older controls. Thisstudy provides support for the hypothesis thatverbal memory is the initial domain of cognition tobe affected in the AD process, as 48% of Petersenet al.’s subjects developed probable AD within4 years of diagnosis of MCI. Some other MCIstudies reported cognitive deficits similar to thosedescribed by Petersen and colleagues (17, 18).

Grober (19) investigated the estimation of therelative rates of dementia in initially nondementedsubjects defined by baseline free recall from theFree Recall and Cued Selective Reminding (FCSR)test (20, 21). These results showed that free recallpowerfully predicts future dementia and supportsthe general view that the best approach for identifypersons at high risk of having dementia is to use amemory test that controls for attention and cog-nitive processing in order to show the presence of acognitive impairment that is not caused by othercognitive deficits. Other studies suggest that pre-diction of future dementia can be improved bycombining memory indicators with an informant’sperception of the patient’s cognitive and functionalstatus (2). Likewise, in the European Kungsholmenproject (Stockholm, Sweden), using a logisticregression analysis, it was observed that onlythe delayed recall item was a significant predictorof future development of AD (18). In anotherEuropean-community-based study (the PAQUIDcohort), Fabrigoule et al. (22) used a multivariateapproach of principal component analysis andshowed that preclinical deficits in AD are homo-geneous and reflect the deterioration of a generalcognitive factor, which mainly includes verbalepisodic memory and visual episodic memory.

More recently, in a prospective study of com-munity-living elderly people, Morris et al. (23)

Neuropsychological features of MCI and AD

35

Tab

le1

Neu

rops

ycho

logica

lfinding

sin

pros

pective

long

itudina

lstudies

ofprec

linical

ADan

dM

CI

Author

Num

berof

subjec

tsM

ean

age

Crite

riaformild

demen

tiaor

MCI

Follo

w-up

(yea

rs)

Cogn

itive

func

tion

pred

ictors

Neu

rops

ycho

logica

lmea

sures

Mas

uret

al.(

32)

385

80.4

DSM

-III-R

(41)

1–2

Verbal

episod

icmem

oryan

dvisu

alep

isod

icmem

ory

Selective

reminding

test

and

fuld

object

mem

oryev

alua

tion

Tuok

koet

al.(

33)

4571

.5DS

M-III-R

(41)

NIN

CDS-

ADRD

A(42)

1–2

Verbal

episod

icmem

ory

Selective

reminding

test

Flicke

ret

al.(

29)

3271

.3GD

S(43)

¼3,

42

Verbal

episod

icmem

oryan

dvisu

alep

isod

icmem

ory

Shop

ping

listreca

ll,visu

alreca

llob

ject

reco

gnition

and

iden

tification

Mortim

eret

al.(

34)

6563

.8DS

M-III(

41)

4Ve

rbal

neurop

sych

olog

ical

tests

Boston

naming

test,v

erba

lrec

all(

word

list)

and

verbal

fluen

cy(animal

naming)

NIN

CDS-

ADRD

A(42)

Flicke

ret

al.(

30)

8669

.8GD

S(43)

¼3,

42

Verbal

episod

icmem

oryan

dex

ecutive

func

tions

Shop

ping

listreca

ll,remote

mem

oryqu

estio

nnaire

and

digitsy

mbo

l

Mas

uret

al.(

9)31

775

–85

DSM

-III-R

(41)

NIN

CDS-

ADRD

A(42)

4Ve

rbal

episod

icmem

ory,

visu

alep

isod

icmem

ory

and

seman

ticmem

ory

Selective

reminding

test,f

uld

object

mem

oryev

alua

tion,

digitsy

mbo

land

verbal

fluen

cy

HDnn

inen

etal.(

35)

229

71.7

NIM

Hcrite

riaW

orkgrou

p(49)

3.6

Verbal

and

visu

almem

ory

Busc

hke

selective

reminding

(totalr

ecall),

visu

alreprod

uctio

n(im

med

iate

reca

ll),v

erba

lfluen

cy(categ

ory),p

aired

asso

ciated

learning

Jaco

bset

al.(

11)

443

73.3

NIN

CDS-

ADRD

A(42)

4Ve

rbal

episod

icmem

oryan

dse

man

ticmem

ory

Selective

reminding

test

and

Boston

naming

&simila

rities,

verbal

fluen

cyan

ddigitsp

an

Linn

etal.(

13)

1045

65–8

8DS

M-III-R

(41)

13Ve

rbal

episod

icmem

ory

Logica

lmem

ory-retained

,paired

asso

ciate

learning

and

digitsp

an

Tierne

yet

al.(2)

107

71.5

NIN

CDS-

ADRD

A(42)

2Ve

rbal

episod

icmem

oryan

dex

ecutive

func

tions

RAVL

T(52)

and

WM

S-R

(51)

men

talc

ontro

l

Deva

nand

etal.(

28)

7566

.2CD

R(44)

¼3

2.5

Verbal

episod

icmem

ory,

verbal

fluen

cy,v

isuo

spatial

mem

ory,

psyc

homotor

spee

dDe

laye

dreca

llon

the

MM

SE(53),lon

g-term

retri

eval

onthe

SRT,

WAI

S-R

(51)

pictureco

mpletion,

WAI

S-R

(51)

(digit

symbo

l,bloc

kde

sign

)and

catego

ryna

ming

inan

imals

Darti

gues

etal.(

28)

2943

74.5

DSM

-III-R

(41)

1–3

Glob

alco

gnitive

perfo

rman

ce,s

hort-

term

visu

almem

oryan

dve

rbal

fluen

cype

rform

ance

MM

SE(53),B

enton'svisu

alretention

test

(54),W

echs

lerpa

iras

sociated

(51)

NIN

CDS-

ADRD

A(42)

Grob

eret

al.(

20)

537

79.3

NIN

CDS-

ADRD

A(42)

3Le

arning

Free

reca

llan

dcu

edse

lective

reminding

(FCS

R)

BDck

man

etal.(

31)

2483

.7M

MSE

<24

(53)

DSM

-III-R

(41)

NIN

CDS-

ADRD

A(42)

3Ve

rbal

episod

icmem

ory

Free

and

cued

reca

llof

words

Fabrigou

leet

al.(

22)

1159

72.9

DSM

-III-R

(41)

NIN

CDS-

ADRD

A(42)

2Ve

rbal

episod

icmem

ory,

visu

alep

isod

icmem

ory

and

gene

ralc

ognitio

nM

MSE

(53),B

enton

visu

alretention

test

(54),v

erba

lpaired

asso

ciates

,digit

span

,sim

ilarit

ies(51)

Rubin

etal.(

36)

8271

.6CD

R(44)

¼0.5

2Ve

rbal

episod

icmem

ory

WM

S(51):l

ogical

mem

ory

Marra

etal.(

37)

4566

.5NIN

CDS-

ADRD

A(42)

3Ve

rbal

episod

icmem

oryan

dex

ecutive

func

tions

RAVL

T(52)

(immed

iate

reca

ll)an

dDB

task

Arnaiz & Almkvist

36

Petersen

etal.(

1)76

80.9

Petersen

crite

ria(45,

46)

DSM

-III-R

(41)

4Ve

rbal

episod

icmem

ory,

visu

alep

isod

icmem

ory

and

seman

ticmem

ory

WM

S-R

(51):l

ogical

mem

ory&

visu

alreprod

uctio

nsRA

VLT

(52),

Boston

naming

test

(55)

Klug

eret

al.(

38)

213

71.2

GDS

(43)

¼3

3.7

Verbal

episod

icmem

ory

Paragrap

hde

layreca

ll

Grob

eret

al.(

19)

6879

.4DS

M-III-R

(41)

6.28

Verbal

episod

icmem

ory

Free

reca

llan

dcu

edse

lective

reminding

(FCS

R)

Smalle

tal.(

18)

459

79.4

DSM

-III-R

(41)

3–6

Verbal

episod

icmem

ory

Delaye

dmem

oryreca

ll(M

MSE

Swed

ish

version)

(47,

48)

Chen

etal.(

39)

120

78.2

DSM

-III-R

(41)

DSM

-III-R

(41)

NIN

CDS-

ADRD

A(42)

10De

laye

dreca

llan

dex

ecutive

func

tions

Word

listde

laye

dreca

llan

dTM

T-B

(52)

Eliaset

al.(

14)

967

65–9

4DS

M-III-R

(41)

22Ve

rbal

episod

icmem

oryan

dab

stract

reas

oning

WM

S:logica

lmem

ory-retained

and

simila

rities

Ritchie

etal.(

40)

308

<60

DSM

-III-R

(41)

3Simple

reac

tion

time,

reac

tion

time

ona

dual

attention

task

,sem

antic

catego

ryflu

ency,

delaye

dve

rbal

reca

ll,cu

edde

laye

dreca

ll,reca

llof

name-face

pairs

,narrativ

ereca

ll,an

dco

pying

ofa

complex

design

Exam

enCo

gnitifpa

rOr

dine

teur

(ECO

)(40

,50)

Morris

etal.(23

)53

(unc

ertain

AD)

76.4

78.0

Petersen

crite

ria(45,

46)

5Ep

isod

ican

dse

man

ticmem

ory,

exec

utive

func

tions

and

visu

ospa

tiala

bilities

Logica

lmem

ory,

asso

ciate

learning

(WAI

S)(51)

visu

alretention

test

form

C,inform

ation,

Boston

naming

test

(55),T

MTA

(52)

and

digitsy

mbo

l(51

)69

(incipien

tAD

)CD

R(44)

Tab

le2

Cros

s-se

ctiona

lstudies

inthe

detection

ofdisc

riminative

cogn

itive

varia

bles

inM

CIan

dea

rlyAD

Author

and

year

Num

berof

subjec

tsM

ean

age

Diag

nosis

Diag

nosiscrite

riaCo

gnitive

func

tion

Neu

rops

ycho

logica

lmea

sures

Storan

dtet

al.1

989

(59)

6673

.9Ve

rymild

senile

demen

tiaCD

R(44)

¼0.5

Mem

ory,

spee

ded

psyc

homotor

and

lang

uage

WM

S(51):l

ogical

mem

ory

Morris

etal.1

991

(60)

1076

.9Ve

rymild

senile

demen

tiaCD

R(44)

¼0.5

Verbal

episod

icmem

ory

WM

S(51):l

ogical

mem

oryas

sociated

learning

test

Welsh

etal.1

992

(61)

4971

.2M

ildAD

NIN

CDS-

ADRD

A(42)

Verbal

episod

icmem

ory

Delaye

dreca

ll(CER

AD)(

67)

Almkv

istet

al.1

993

(6)

3072

Very

mild

demen

tiaDS

M-III-R

(41)

Intellige

nce,

verbal

episod

ican

dse

man

ticmem

ory,

visu

ospa

tialf

unction,

prim

arymem

ory

and

psyc

homotor

spee

d

WAI

S-R

(15),W

MS-

R(51)

Petersen

etal.1

994

(63)

106

80.7

Prob

able

ADDS

M-III-R

(41)

NIN

CDS-

ADRD

A(42)

Learning

with

seman

ticcu

eing

WAI

S-R(15),A

VLT(52),W

MS-

R(51),W

RAT(68),C

OWAT

(54)

Smith

etal.1

996

(64)

6679

.8M

CIPe

tersen

etal.1

995

(45)

Delaye

dreca

llM

OANS

(69)

Arn.

izet

al.2

000

(58)

9064

.5M

CIHu

ddinge

'scrite

riaVe

rbal

episod

ican

dse

man

ticmem

ory,

visu

ospa

tialf

unction

and

attention

AVLT

(70),W

MS-

R(51),W

AIS-

R(15),t

rail

mak

ing

(52)

Neuropsychological features of MCI and AD

37

found that cognitive impairment in individualswith MCI was not limited to memory but alsoinvolved other cognitive domains. They followed122 MCI patients for 9.5 years and concluded thatMCI subjects progress steadily to greater stages ofdementia severity at rates dependent on the level ofcognitive impairment at entry.

Using a survival analysis, Bozoki et al. (24)concluded that nondemented elderly patients withonly memory loss rarely progress to dementia, butthe risk of dementia was significantly increasedamong patients who had more cognitive areasimpaired than just memory. Similarly, in a colla-borative study from the Mayo Clinic (Rochester,MN) and the Karolinska Institutet (Stockholm,Sweden) (25), the number of impaired cognitivefactors at baseline could predict the progression toAD in a sample of 303 MCI patients. Furthermore,tests assessing learning and retention were the bestpredictors for progression to AD, as shown by alogistic regression model (unpublished manuscript).

Some other longitudinal studies with smallersamples showed that new learning (20), verbalabilities (including category and letter fluency),visuospatial and executive functioning (26), verbalabilities (27), verbal ability, and visuospatial func-tion (28–31) were the strongest predictors ofpreclinical AD. In addition, indices of psycho-motor speed, such as the Digit Symbol Test (2, 27,28), were also considered valuable predictors offuture cognitive decline. However, in light ofobjective episodic memory deficits in those indi-viduals who develop dementia, it is interesting tonote that there is conflicting evidence concerningthe predictive power of subjective memory com-plaints for later development of dementia inotherwise healthy elderly individuals. A summaryof neuropsychological findings in the most import-ant prospective longitudinal studies of preclinicalAD and MCI is shown in Table 1.

However, results from epidemiological longitud-inal studies on incipient AD have also demonstra-ted that a variety of measures of episodic memoryperformance could help to clearly detect earlycognitive changes in those patients who ultimatelymay develop dementia (9, 11, 14, 16, 19, 20, 26, 36,37, 56, 57).

These results showed that consideration ofcognitive domains other than memory can signifi-cantly improve the predictive value of neuropsy-chological testing in nondemented patients with amemory complaint. The majority of these resultsfollow from the hypothesis that subjects with evi-dence of impairments extending beyond memoryare more likely to have AD than those with onlymemory deficits (24, 58).

Cross-sectional clinical studies

As previously mentioned, according to the litera-ture, the most salient predictors of AD appear tobe different measures of episodic memory andlearning. This finding is in concordance with cross-sectional studies that also found episodic memoryto best discriminate between AD, preclinical ADand controls (20, 58–65). However, it is importantto mention that psychometric discrimination ofAD has been shown to be less accurate incommunity-dwelling populations than in clinic-based samples, as shown in cross-validation studies(16, 66). A summary of cross-sectional studies inthe detection of discriminative cognitive variablesin MCI and early AD is presented in Table 2.

Although episodic memory tasks appear to havethe best predictive power for indicating earlydementia development, it is still unclear whichaspect of episodic memory is most vulnerable todementia. For example, it is not known whetherthe deficits in memory performance of preclinicalAD patients result from impairment in encoding,storage or retrieval processes. Moreover, neuro-psychological tests may differ in terms of sensitivityand because of varying task difficulty rather thanspecific processes tapped by the memory task.

Limitation of neuropsychological studies in preclinicalAD and MCI

Methodological limitations

The apparent heterogeneity in some of thesestudies could be partly explained by three meth-odological reasons: 1) the lag time between theevaluation of cognitive performance varies consid-erably between studies; 2) the specific properties ofvarious test commonly used are not fully under-stood; 3) test scores are often strongly collinear,essentially because common cognitive componentsare involved in different test (e.g. attention).Therefore, it is expected that the best approachfor identifying persons at high risk of having futuredementia is to show the presence of a memoryimpairment that is not caused by other cognitivedeficits (i.e. deficits in attention, language). Inaddition, cultural, educational and attention-related factors (i.e. impaired attention as a resultof stress, anxiety or depression) can also have animpact on neuropsychological testing.

The validity of these kinds of study – especiallycomparisons of different age groups – is under-mined by the presence of possible uncontrolledcohort effects, i.e. between group differences. Addi-tionally, neuropsychological measures cannot fully

Arnaiz & Almkvist

38

distinguish between different types of dementia,because there is a substantial overlap in neuropsy-chological profiles. This problem could be partlyavoided through the use of longitudinal studies,in which the decreases in cognitive test scores thatare observed can be more reliably attributed toage-related cognitive deterioration. However, lon-gitudinal studies are more likely to yield negativeresults than cross-sectional studies, as a conse-quence of the smaller age differences usuallyassessed and because of the sampling biases inher-ent in the methodology. For example, it has beenpersistently observed that the persons successfullyfollowed up in longitudinal studies are healthierthan dropouts; a phenomenon referred to as�selective attrition� (29).

There is some debate as to whether cognitive datashould be corrected for age and education, becausethese variables are also predictors of AD (71). It isargued that, if data are not corrected for age andeducation, then the specificity will decrease, becausethere is ample evidence that age, education andgender affect cognitive performance. For thatreason, it would always be necessary to correctcognitive performance for age and education inorder to minimize the effects that the performanceof subjects with preclinical AD have on the predic-tive accuracy of the cognitive tests.

Future recommendations for neuropsychological studiesin MCI patients

In relation to these kinds of study, we can make thefollowing methodological recommendations forfuture research in preclinical AD. The combinationof cross-sectional and longitudinal data might bethe best solution in tracing the sequential develop-ment of cognitive deficits in aging, preclinicaldementia and dementia. Conversely, because lon-gitudinal cognitive deterioration is a definingcharacteristic of AD, follow-up cognitive testresults could be used to validate baseline diagnosesretrospectively and, thus, help to determine opti-mal diagnostic criteria and behavioural predictorsof future cognitive loss.

It is also important to mention that the results ofcognitive investigations of MCI and preclinicaldementia have significant implications for thenormative studies of commonly used neuropsycho-logical measures (63, 72).

Studies that investigate preclinical AD in subjectswith MCI should have a follow-up period of at least5 years, although secondary endpoints, such ascognitive assessment, can be used. Cognitive per-formance and functional impairment should not beused as inclusion or exclusion criteria, because both

are highly variable in subjects with preclinical AD;this could then lead to a circular diagnosis effect.Finally, further studies are needed to determinewhether the group that does not develop dementiarepresents a completely different entity and if it ispossible to characterize its cognitive phenotype.

Conclusion

On the basis of the results of the reviewedliterature, a large proportion of patients withMCI (most frequently manifested as isolatedverbal episodic memory dysfunction) will developearly AD with multiple cognitive deficits. Thedeficits that are apparent at this stage may lastfor several years. However, evidence points tothe fact that preclinical AD is characterized bynumerous impairments affecting multiple cognitivedomains, including episodic memory, verbal abil-ities and learning, visuospatial function, attentionand executive functions. By contrast, primarymemory, as well as sensory and motor abilitiesmay be relatively preserved.

A brief battery, including measures of newlearning, delayed recall and attention ⁄ executivefunction, could provide valuable information forscreening and diagnosis of MCI and early ADif interpreted properly. Despite their importantclinical value, preclinical AD and MCI cannot bediagnosed by neuropsychological tests alone andclinical judgment is always required.

References

1. Petersen RC, Smith GE, Warring SC et al. Mild cognitiveimpairment: clinical characterisation and outcome. ArchNeurol 1999;56:303–8.

2. Tierney MC, Slazai JP, Snow GW et al. The predictionof Alzheimer’s disease: the role of patients and inform-ant perceptions of cognitive deficits. Arch Neurol 1996;53:423–7.

3. Bowen J, Teri L, Kukull W et al. Progression to dementiain patients with isolated memory loss. Lancet 1997;349:763–5.

4. Dawe B, Procter A, Philpot M et al. Concepts of mildmemory impairment in the elderly and their relationship todementia: a review. Int J Geriatr Psychiatry 1992;7:473–9.

5. Wolf H, Grunwald M, Ecke GM et al. The prognosis ofmild cognitive impairment in the elderly. J Neural Transm1998;54:31–50.

6. Almkvist O, Backman L. Progression in Alzheimer’sdisease: sequencing of neuropsychological decline. Int JGeriatr Psychiatr 1993;8:755–63.

7. Petersen RC, Stevens JC, Ganguli M et al. Practiceparameter: early detection of dementia: mild cognitiveimpairment (an evidence-based review). Neurology 2001;56:1133–42.

8. Visser JV. Predictors of Alzheimer’s type dementia insubjects with mild cognitive impairment. Thesis. Maas-tricht University, 2000.

Neuropsychological features of MCI and AD

39

9. Masur DM, Sliwinski M, Lipton RB et al. Neuropsycho-logical prediction of dementia and the absence of dementiain healthy elderly persons. Neurology 1994;44:1427–32.

10. Weschler D. Weschler Adult Intelligence Scale (WAISManual). New York: The Psychological Corporation, 1955.

11. Jacobs DM, Sano M, Dooneief G et al. Neuropsycholog-ical detection and characterization of preclinical Alzhei-mer’s disease. Neurology 1995;45:957–62.

12. Goodglass H, Wingfield A, Hyde MR et al. Categoryspecific dissociations in naming and recognition by aphasicpatients. Cortex 1986;22:87–102.

13. Linn RT, Wolf PA, Bachman DL et al. The �preclinicalphase� of probable Alzheimer’s disease. Arch Neurol1995;52:485–90.

14. Elias MF, Beiseries A, Wolf PA et al. The preclinicalphase of Alzheimer’s disease. Arch Neurol 2000;57:808–13.

15. Wechsler D. Wechsler Adult Intelligence Scale Revised:Manual. New York: The Psychological Corporation, 1981.

16. Petersen RC. Mild cognitive impairment or questionabledementia? Arch Neurol 2000;57:643–4.

17. Blesa R, Adroer R, Santacruz P et al. High Apolipopro-tein e epsilon 4 allele frequency in age-related memorydecline. Ann Neurol 1996;39:548–51.

18. Small BJ, Fratiglioni L, Viitanen M et al. The course ofcognitive impairment in pre-clinical Alzheimer’s disease.Arch Neurol 2000;57:839–44.

19. Grober E. Memory impairment on free and cued recallselective reminding predicts dementia. Neurology 2000;54:827–31.

20. Grober E, Kawas C. Learning and retention in preclinicaland early Alzheimer’s disease. Psychol Aging 1997;12:183–8.

21. Buschke H. Cued recall in amnesia. J Clin Exp Neuro-psychol 1984;6:433–40.

22. Fabrigoule C, Rouch I, Taberly A et al. Cognitive processin preclinical phase of dementia. Brain 1998;121:135–41.

23. Morris JC, Storandt M, Miller JP et al. Mild cognitiveimpairment represents early stage Alzheimer disease. ArchNeurol 2001;58:397–405.

24. Bozoki A, Giordani B, Heidebrink JL et al. Mild CognitiveImpairment predicts dementia in nondemented elderlypatients with memory loss. Arch Neurol 2001;58:411–6.

25. Arnaiz E, Almkvist O, Ivnik RK et al. Mild cognitiveimpairment diagnosis: a cross national comparison of MCIsamples. Submitted for publication.

26. Small BJ, Herlitz L, Backman L et al. Cognitive devel-opment in Alzheimer’s disease: charting the decline pro-cess. Oxford: Elservier, 1997.

27. Howieson DB, Dame A, Camicioli R et al. Cognitivemarkers preceding Alzheimer’s disease in the healthy oldestold. J Am Geriatr Soc 1997;45:584–9.

28. Devanand DP, Folz M, Gorlyn M et al. Questionabledementia: clinical course and predictors outcome. J AmGeriatr Soc 1997;45:321–8.

29. Flicker C, Ferris SG, Reisberg B et al. Mild cognitiveimpairment in the elderly: predictors of dementia. Neur-ology 1991;41:1006–9.

30. Flicker C, Ferris S, Reisberg B et al. A two-year longi-tudinal study of cognitive function in normal ageing andAlzheimer’s disease. J Geriatr Psychiatry Neurol1993;6:84–96.

31. Backman L, Small B. Influences of cognitive support onepisodic remembering: tracing the process of loss fromnormal ageing to Alzheimer’s disease. Psychol Ageing1998;12:183–8.

32. Masur DM, Sliwinski M, Lipton RB et al. Predictingdevelopment of dementia in the elderly with selectivereminding test. J Clin Exp Neuropsychol 1990;12:528–38.

33. Tuokko H, Vernon-Wilkinson R, Weir J et al. Cued recalland early identification of dementia. J Clin Exp Neuro-psychol 1991;13:871–9.

34. Mortimer JA, Ebbit B, June SP et al. Predictors of cog-nitive and functional progression in patients with probableAlzheimer’s disease. Neurology 1992;42:1689–96.

35. Hanninen T, Hallikainen M, Koivisto K et al. A follow-upstudy of age-associated memory impairment: neuropsy-chological predictors of dementia. J Am Geriatr Soc1995;43:1007–15.

36. Rubin EH, Storandt M, Miller JP et al. A prospectivestudy of cognitive function and onset of dementia in cog-nitively healthy elders. Arch Neurol 1998;55:395–401.

37. Marra C, Silveri M, Gainotti G. Predictors of cognitivedecline in the early stage of probable Alzheimer’s disease.Dementia 1999;11:212–8.

38. Kluger A, Gianutsos J, Golomb J et al. Motor ⁄ psycho-motor dysfunction in normal aging, mild cognitive decline,and early Alzheimer’s disease: diagnostic and differentialdiagnostic features. Int Psychogeriatr 1997 9(Suppl.):307–16.

39. Chen P, Ratcliff G, Belle SG et al. Cognitive tests thatbest discriminate between presymptomatic AD and thosewho remain nondemented. Neurology 2000;55:1847–53.

40. Ritchie K, Artero S. Touchon. Classification criteria formild cognitive impairment. A population-based validationstudy. Neurology 2001;56:37–42.

41. American Psychiatric Association. Diagnostic and StatisticalManual of Mental Disorders (DSM-III-R), rev, 3rd edn.Washington, DC: American Psychiatric Association, 1987.

42. McKhann G, Drachman D, Folstein M et al. Clinicaldiagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Departmentof Health and Human Services Task Forces on Alzheimer’sDisease. Neurology 1984;34:939–44.

43. Reisberg B, de Ferris SH, Leon et al. The global deteri-oration scale for assessment of primary degenerativedementia. Am J Psychiatry 1982;139:1136–9.

44. Hughes CP, Berg L, Danziger WL et al. A new clinicalscale for the staging of dementia. Br J Psychiatry1982;140:566–72.

45. Petersen RC, Smith G, Ivnik RJ et al. Apolipoprotein Estatus as a predictor of the development of Alzheimer’sdisease in memory impaired individuals. J Med Am Assoc1997;273:1274–8.

46. Petersen RC, Smith G, Tangalos EC et al. Predictive valueof APOE genotype in incipient Alzheimer’s disease. AnnNY Acad Sci 1996;802:58–69.

47. Fratiglioni L, Grut M, Forsell Y et al. Clinical diagnosisof Alzheimer’s disease and other dementias in a populationsurveys: agreement and causes of disagreement in applyingDSM-III-R. Arch Neurol 1992;49:927–32.

48. Fratiglioni L, Viitanen M, von Strauss E et al. Very oldwomen at highest risk of dementia and Alzheimer’s dis-ease: incidence data from the Kungsholmen project,Stockholm. Neurology 1997;48:132–8.

49. Crook TH, Bartus RT, Ferris SH et al. Age-associatedmemory impairment: proposed diagnostic criteria andmeasures of clinical range. Report of a National Instituteof Mental Health work group. Dev Neuropsychol1986;2:261–76.

50. Ritchie K, Allard M, Huppert FA et al. Computerisedcognitive examination of the elderly (ECO): the develop-ment of a neuropsychological examination for clinic andpopulation use. Int J Geriatr Psychiatry 1993;8:899–914.

51. Weshcler D, Stone C. Weshler Memory Scale Manual.New York: The Psychological Corporation, 1973.

Arnaiz & Almkvist

40

52. Rey A. L’examen clinique en psychologie. Paris: PressesUniversitaire de France, 1959.

53. Folstein MF, Folstein SE, McHugh PR. Mini-MentalState: a practical method for grading the cognitive state ofpatients for the clinician. J Psychiatr Res 1975;12:189–98.

54. Benton A, Hamsher K. Multilingual aphasia examination.Iowa City: University of Iowa, 1976.

55. Kaplan EF, Goodglass H, Weibtraub S. The Boston NamingTest, 2nd edn. Philadelphia, PA: Lea and Febriger, 1983.

56. Herlitz A, Small B, Fratiglioni L et al. Detection of milddementia in community surveys: is it possible to increasethe accuracy of our diagnostic instruments? Arch Neurol1997;54:319–24.

57. Johansson B, Zarit S. Early cognitive markers of the inci-dence of dementia and mortality: a longitudinal popula-tion-based study of the oldest old. Int J Geriatr Psychiatr1997;12:53–9.

58. Arnaiz E, Blomberg M, Fernaeus S-E et al. Psychometricdiscrimination of Alzheimer’s disease and mild cognitiveimpairment. Alzheimer’s Reports 2000;3:97–103.

59. Storandt M, Hill RD. Very mild senile dementia of theAlzheimer type. II. Psychometric test performance. ArchNeurol 1989;46:383–6.

60. Morris JC, McKeel D, Storandt M et al. Very mildAlzheimer’s disease: informant -based clinical, psycho-metric and pathological distinction from normal aging.Neurology 1991;41:469–78.

61. Welsh KA, Butterns N, Hughes JP et al. Detection andstaging of dementia in Alzheimer’s disease: use of theneuropsychological measures developed for the Consor-tium to Establish a Registry for Alzheimer’s Disease. ArchNeurol 1992;49:448–52.

62. Bondi MW, Monsch AU, Galasko D et al. Preclinicalmarkers of dementia of the Alzheimer type. Neuropsychol1994;8:374–84.

63. Petersen RC, Smith G, Ivnik RJ et al. Memory functionin very early Alzheimer’s disease. Neurology 1994;44:867–72.

64. Smith GE, Petersen RC, Parisi JE et al. Definition, course,and outcome of mild cognitive impairment. Aging Neu-ropsychol Cognition 1996;3:141–7.

65. Amkvist O, Basun H, Backman L et al. Mild cognitiveimpairment – an early stage of Alzheimer’s disease?J Neural Transm 1998;54:21–9.

66. Cahn DA, Salmon DP, Butters N et al. Detection ofdementia of the Alzheimer type in a population-basedsample: neuropsychological test performance. J Int Neuro-psychol Soc 1995;1:252–60.

67. Morris JC, Mohns R, Rogers H et al. Consortium toestablish a registry of Alzheimer’s disease (CERAD) clin-ical and neuropsychological assessment of Alzheimer’sdisease. Psyhopharmacol Bull 1988;24:641–52.

68. Jastak S, Wilkinson GS. The Wide Range AchievementTest Revised. Administration Manual. Wilmington, DE:Jastak Associates, 1984.

69. Ivnik RJ, Malec JF, Smith GR et al. Mayo’s olderAmerican normative studies: WAIS-R, WMS-R andAVLT norms for ages 56 through 97. Clin Neuropsy-chologist 1992;6:1–104.

70. Lezak M. Neuropsychological Assessment. New York:Oxford University Press, 1995.

71. Sliwinski M, Buschke H, Stewart W et al. The effectof dementia risk factors on comparative and diagnosticselective reminding norms. J Int Neuropsychol Soc1997;3:317–26.

72. Sliwinski M, Lipton RB, Buschke H et al. The effect ofpreclinical dementia on estimates of normal cognitivefunctioning in ageing. J Gerontol B Psychol Sci Soc Sci1996;51:217–25.

Neuropsychological features of MCI and AD

41