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. Author manuscript; available in PMC: 2012 Apr 1.
Published in final edited form as: Int J Geriatr Psychiatry. 2010 Sep 15;26(4):364–372. doi: 10.1002/gps.2535

Neuropsychiatric symptoms in MCI subtypes: the importance of executive dysfunction

Paul B Rosenberg 1,4,*, Michelle M Mielke 1,2,4, Brian Appleby 1, Esther Oh 3, Jeannie-Marie Leoutsakos 1,2,4, Constantine G Lyketsos 1,2,4
PMCID: PMC3204866  NIHMSID: NIHMS315307  PMID: 20845402

Abstract

Objective

Mild cognitive impairment (MCI) is a syndrome thought to be a prodrome of dementia for some patients. One subtype, amnestic MCI, may be specifically predispose patients to develop Alzheimer’s Dementia (AD). Since dementia has been associated with a range of neuropsychiatric symptoms (NPS), we sought to examine the prevalence of NPS in MCI and its subtypes.

Methods

1779 participants in the National Alzheimer Coordinating Center (NACC) with MCI were included in this study. All participants were evaluated systematically with a thorough cognitive battery, clinical interview, and consensus diagnoses, and subtyped as: 1) amnestic (aMCI) (single- or multiple-domain) vs. non-amnestic (non-aMCI); 2) executive dysfunction-MCI (exMCI) (single- or multiple-domain) vs. no executive dysfunction-MCI (non-exMCI); 3) both aMCI and exMCI; 4) and neither aMCI nor exMCI. Additionally , aMCI vs. nonaMCI and exMCI vs. non-exMCI dichotomies were explored. NPS were assessed with the Neuropsychiatric Inventory (NPI-Q) and Geriatric Depression Scale (GDS).

Results

1379 participants (77.5%) met criteria for aMCI and 616 (34.6%) for exMCI. No differences were observed in the prevalence of NPS between aMCI vs. non-aMCI. However, exMCI was associated with greater severity of depression, anxiety, agitation, disinhibition, irritability, and sleep problems, although these differences do not persist after adjustment for several variables. .

Conclusions

While there were few associations between aMCI and NPS, the presence of executive dysfunction in MCI was associated with greater severity of symptoms and specifically with depression (evidenced by GDS score) and anxiety. These findings may have implications for MCI prognosis and need to be explored in longitudinal studies.

Keywords: Mild Cognitive Impairment, Depression, Executive Dysfunction, Neuropsychiatric symptoms

Introduction

There is growing evidence that dementia is preceded by a prodrome in which persons at risk can be identified by clinical characteristics, especially the emergence of mild cognitive deficits (Petersen et al., 2001; Winblad et al., 2004). The syndrome “mild cognitive impairment” (MCI) has been proposed as one way to identify this prodrome and is used to describe individuals who are neither cognitively normal nor demented, but who are exhibiting cognitive impairment in the absence of functional impairment (Winblad et al., 2004). MCI has been subtyped by the number and characteristics of the affected cognitive domains: single- vs. multiple-domain, and amnestic (affecting episodic recall) vs. non-amnestic. (Petersen et al., 2001; Winblad et al., 2004). Persons with amnestic MCI (aMCI) are at particularly high risk of developing Alzheimer’s Dementia (AD) in the near term, with annual rates of progression from aMCI to AD estimated at 10-18%; up to 80% develop AD at 6 year follow-up (Petersen, 2004; Gauthier et al., 2006; Tschanz et al., 2006). Several longitudinal studies report that persons with aMCI progress to AD faster than persons with non-aMCI (Busse et al., 2006; Ravaglia et al., 2006b; Tschanz et al., 2006; Fischer et al., 2007).

In addition to cognitive deficits, AD is characterized by neuropsychiatric symptoms (NPS) including depression, apathy, agitation, irritability, delusions, and hallucinations (Lyketsos et al., 2000; Lyketsos et al., 2001; Lyketsos et al., 2002b; Steinberg et al., 2003; Steinberg et al., 2007). NPS are near-universal in dementia with 97% of participants in one study experiencing at least one NPS (Steinberg et al., 2007). It is possible that the prodrome of dementia may have both cognitive and non-cognitive symptoms. As a prodrome of AD, NPS may be associated with increased risk for MCI progression to dementia and the prevalence of NPS in MCI would be expected to be greater than in cognitively healthy persons but less than in dementia; the latter finding has been reported in epidemiologic studies of population-based samples (Lyketsos et al., 2002b; Geda et al., 2008). A corollary is that if different MCI subtypes have different NPS profiles, these differences might be reflected in different prognoses. Differences in NPS between MCI subtypes have not been clearly established, with the Cardiovascular Health Study (CHS) reporting no difference in NPS profile between participants with amnestic single-domain MCI compared to other MCI subtypes (Lopez, Becker, Sweet, 2005) while the Mayo Clinic Study of Aging reporting differences that were small in magnitude (Geda et al., 2008).

We consequently examined NPS profiles in several MCI subtypes in a large multi-center cohort from the National Alzheimer Coordinating Center (NACC) database, (Beekly et al., 2004; Beekly et al., 2007). Since depression in older adults is characterized by deficits in executive function (Alexopoulos et al., 1997), that persist even when depressive symptoms resolve (Murphy and Alexopoulos, 2004), we included the presence or absence of executive dysfunction as well as memory dysfunction to subtype MCI. We hypothesized that the presence of executive dysfunction (regardless of memory dysfunction) in MCI would be associated with greater severity of NPS, particularly depressive symptoms.

Methods

The National Alzheimer’s Coordinating Center (NACC) is responsible for developing and maintaining a database combining the data collected at the 29 Alzheimer’s Disease Centers (ADCs) funded by the National Institute of Aging (Beekly et al., 2004). The NACC database has been operational since 2000 and since 2002 has expanded its efforts into a fully integrated data system, the Uniform Data Set (UDS) (Beekly et al., 2007), which is available to investigators in the field for analytic projects. Methods for the administration of the UDS in the ADCs have been previously published (Morris et al., 2006).

Standard Protocol Approvals, Registrations, and Patient Consents

All participants or their legally authorized representatives signed informed consent prior to participation, and the procedures were approved by the Institutional Review Board overseeing each ADC.

MCI and dementia diagnoses

NACC participants receive a diagnosis adjudicated by an experienced clinician or an interdisciplinary team as previously described (Morris et al., 2006). Diagnosticians considered history and test performance in several cognitive domains (episodic recall, language, attention, executive function, and visuospatial function) as well as psychosocial functioning in making diagnoses. The UDS neuropsychological battery was used to inform the diagnostic process, but diagnoses were made clinically and not on the basis of strict cutoffs on neuropsychologic tests. The battery included Mini-Mental State Exam (Folstein, Folstein, McHugh, 1975), Wechsler Memory Scale-Revised Logical Memory IA (Wechsler and Stone, 1973), Digit Span Forward and Backward (Wechsler and Stone, 1973), Category Fluency (animals and vegetables) (Morris et al., 1989), Boston Naming Test (Goodglass and Kaplan, 1983), WAIS-R Digit Symbol (Wechsler, 1955), Trailmaking Test Parts A and (Armitage, 1946), and Wechsler Memory Scale (Revised) Logical Memory IIA (Wechsler and Stone, 1973). Participants were assigned diagnoses of 1) “cognitively normal” if they lacked significant cognitive or functional impairment; 2) “MCI” if they had objective or subjective evidence of cognitive impairment but no significant functional impairment to meet criteria for dementia; 3) “demented” if they had significant cognitive and functional impairment.

MCI was further subtyped into 1) aMCI if they had significant impairment in memory; 2) non-aMCI if they had normal performance in memory but impairment in another cognitive domain; 3) single-domain MCI if they had impairment in one cognitive domain only; 4) multiple-domain MCI if they had impairment in more than one cognitive domain. Thus, a participant with MCI might have been diagnosed with single- or multiple-domain aMCI, or single- or multiple-domain non-aMCI (Winblad et al., 2004). In addition, non-aMCI and multiple-domain aMCI were further subtyped according to the cognitive domains affected including memory, visuospatial, attention, language, and executive function. We used these clinical consensus diagnoses available in the UDS to define two dichotomies of MCI subtypes (below).

Definition of MCI subtypes

aMCI vs. non-aMCI

We first dichotomized MCI by distinguishing all amnestic subtypes (single- or multiple-domain) vs. all non-amnestic subtypes (single- or multiple-domain). We chose to combine single- and multiple-domain subtypes because a) neither of our hypotheses was affected conceptually by the distinction between single- and multiple-domain subtypes of MCI; and b) comparing two (instead of multiple) categories improves statistical power. This dichotomy is similar though not identical to the approach used in the Cardiovascular Health study (CHS) (Lopez, Becker, Sweet, 2005) and in the Olmsted County Study (Geda et al., 2008).In the CHS, the investigators compared single-domain aMCI vs. all other types of MCI including multiple-domain; we chose to combine multiple-domain aMCI with single-domain because the clinical presentations are similar and the prognoses not yet known.

MCI with executive dysfunction (exMCI) vs. MCI without executive dysfunction (non-exMCI)

we similarly dichotomized MCI according to the presence or absence of executive dysfunction as defined by the clinician or interdisciplinary team at each ADC, combining together single/multiple-domain and aMCI/non-aMCI subtypes. We examined differences in NPS between the setwo dichotomies.

Since the categories of aMCI and exMCI were not mutually exclusive, we additionally subtyped MCI into four mutually exclusive categories:

  1. neither aMCI nor exMCI

  2. aMCI only

  3. exMCI only

  4. both aMCI and exMCI

Outcomes

Clinical Dementia Rating (CDR) (Morris, 1993)

The CDR is the most widely used rating of global function in dementia and MCI. The CDR is performed via a semi-structured interview and it has been demonstrated to have excellent reliability and validity. The CDR uses a 4 to 5-point ordinal scale to characterize six domains of cognitive and functional performance: memory, orientation, judgment, community, hobbies, and personal care. Each domain is rated (0=no impairment, 0.5=questionable impairment, 1=mild impairment, 2=moderate impairment, 3=severe impairment), with the exception of personal care which omits the questionable impairment category. A global score (CDR-composite) is created using a predefined algorithm. The CDR-Sum of Boxes (CDR-Sum) score is the sum of individual ratings in each of the six domains, with a range of 0 (no impairment) to 30 (maximum impairment in all domains). Both CDR-composite and CDR-Sum scores were examined as outcome measures in this study. The CDR-Sum score has demonstrated sensitivity in changes within MCI and AD as demonstrated by epidemiological (Pavlik et al., 2006) and functional magnetic resonance imaging studies (Dickerson et al., 2004).

Neuropsychiatric Inventory Questionnaire (NPI-Q) (Cummings et al., 1994; Kaufer et al., 2000)

The NPI is the most widely used measure of NPS in dementia research that assesses the type and severity of behavioral disturbances in dementia. It evaluates 12 domains: agitation, delusions, hallucinations, depression, euphoria, aberrant motor behavior, apathy, irritability, disinhibition, anxiety, sleep, and eating. The NPI is administered as a structured interview with a knowledgeable informant who can report the patient’s NPS. The NPI-Q is a simplified clinical form of the NPI, with two scores reported for each domain: a) presence of symptoms; and b) severity on a 0-3 scale (0= none, 1=mild, 2=moderate, 3=severe). We report severity for each individual NPI domain, and further calculated the sum (NPI-total, range 0-36). The frequency of symptoms is not assessed on NPI-Q,(Kaufer et al., 2000) unlike the NPI(Cummings et al., 1994).

Geriatric Depression Scale (GDS), short-form (Yesavage et al., 1982)

The GDS(short-form) is a 15-item scale in which each item is endorsed “yes” or “no” by the participant. The GDS is widely used in the geriatric population and its reliability and validity compared to other depression measures are well established (Lichtenberg et al., 1992). The GDS (short-form) has also been validated in cognitively impaired persons (Burke, Roccaforte, Wengel, 1991).

Hachinski Ischemia Scale (Hachinski, 1975)

The Hachinski Ischemia Scale was devised to differentiate vascular dementia from degenerative dementia (largely AD). The scale rates eight items associated with vascular dementia including abrupt onset, stepwise progression, emotional incontinence, history of stroke or hypertension, and focal neurologic signs and symptoms. The range is 0-12; scores of 4 or less are consistent with primary degenerative dementias, scores of >=7 with vascular dementias, while scores of 5-6 are considered equivocal (Swanwick et al., 1996).

Analyses

Two approaches to dichotomizing the MCI group were examined: aMCI vs. non-aMCI and exMCI vs. non-exMCI. These dichotomies constituted the independent variables. The dependent variables were CDR-Sum, NPI-Q total severity scores and individual NPS scores (score> 0 or frequency X severity), and GDS total and item scores. The occurrence of categorical variables (choosing the “depressed” response to a GDS item) was compared between diagnoses using the χ2(df=1) statistic. For dichotomous comparisons (aMCI vs. nonaMCI, and exMCI vs. nonexMCI) the statistic used was χ2 (df=1). For comparison of continuous variables (including CDR Sum of Boxes, NPI-Q sum of frequency X severity for all domains, and NPI-Q scores (prevalence and frequency X severity) for individual domains), multivariate analysis of variance (ANOVA) was performed, with Tukey’s HSD used to correct for multiple comparisons where appropriate. We also assessed the prevalence of vascular conditions causing atherosclerotic disease (myocardial infarction, atrial fibrillation, stroke, hypertension, hypercholesterolemia, diabetes, and congestive heart failure), since they have been reported as impacting the incidence of both AD and non-AD dementias (Forti et al., 2006; Ravaglia et al., 2006a). P<.05 was used as the cutoff for statistical significance, and Holms’ procedure (Aickin and Gensler, 1996) was used to adjust for multiple comparisons. The unadjusted p values are presented in each table, with significance after adjustment marked with *. Analyses were run using Stata, version 10 (Statacorp, College TX, 2009).

Results

MCI participants grouped by mutually exclusive subtypes

We initially subtyped MCI by the presence or absence of amnestic and executive function, categorizing all participants into mutually exclusive subtypes: 1) neither amnestic nor executive dysfunction; 2) amnestic only; 3) executive dysfunction only; or 4) both amnestic and executive dysfunction. Of the 1779 NACC participants with MCI, 1379 (77.5%) met criteria for aMCI and 400 (22.5%) for non-aMCI. Of the aMCI participants, 783 were impaired only in memory (i.e., aMCI single-domain) and 596 in multiple cognitive domains. 1163 (64.4%) met criteria for non-exMCI and 616 (34.6%) for exMCI. Demographic variables and vascular conditions in these groups are in Table 1. Participants with executive dysfunction tended to be younger; aMCI participants were less likely to be African-American or Hispanic. Of the vascular conditions, only stroke varied by subtype such that persons with both amnestic and executive dysfunction had the highest prevalence of stroke.

Table 1. Demographic variables and prevalence of vascular conditions stratified by mutually exclusive MCI subtypes.

Demographics and prevalence of vascular risk factors for NACC participants with MCI, stratified by mutually exclusive MCI subtypes. Categorical variables reported as %, with statistical test Pearson’s χ2(3). Continuous variables reported as mean(SD), using analysis of variance with calculated using (F 3,1775) statistic. Post-hoc comparisons were performed using Tukey’s HSD using p<.05 for threshold of statistic significance.

Variable All
MCI		 Neither
aMCI nor
exMCI		 aMCI
only		 exMCI
only		 Both aMCI
and exMCI		 Statistic p Post-hoc
comparisons
Age (years) 75.4
(9.6)		 75.1(8.3) 76.2(9.6) 72.9(9.8) 75.1(9.5) F 3,1775 = 8.38 <.001 Neither, aMCI,
both>exMCI
Education (years) 15.2
(7.8)		 15.2 (7.7) 15.6
(7.8)		 15.0 (8.6) 14.4 (7.2) F 3,1775 = 2.04 .10
Female (%) 52.3 59.5 51.1 56.2 51.6 χ2(3) =5.3 .15
African-American (%) 15.4 20.3 10.6 21.5 22.2 χ2(3) =63.6 <.001
Hispanic (%) 7.4 6.3 5.4 11.2 11.0 χ2(3) =42.0 <.001
Myocardial infarction
(%)		 7.8 5.1 8.6 7.9 7.0 χ2(3) =6.1 .73
Atrial fibrillation (%) 8.0 6.3 7.6 9.5 9.1 χ2(3) =2.9 .97
Stroke (%) 6.24 3.17 5.2 7.0 9.6 χ2(3) =20.1 .017
Hypertension(%) 54.7 54.4 52.8 57.9 58.0 χ2(3) =9.4 .40
Hypercholesterolemia
(%)		 51.9 53.8 51.0 48.8 55.6 χ2(3) =13.5 .14
Diabetes (%) 12.9 12.7 11.5 14.9 15.5 χ2(3) =8.4 .49
Congestive heart failure
(%)		 4.0 3.2 3.9 7.0 2.6 χ2(3) =12.7 .17
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Functional impairment and neuropsychiatric severity scores are presented in table 2. The presence of executive dysfunction (with or without amnestic deficits) was associated with lower MMSE and higher Hachinski scores. A trend toward greater GDS scores in persons with executive dysfunction was no longer significant after adjustment for multiple comparisons. Amnestic and “both” participants were more functionally impaired on the CDR-Global, while executive dysfunction and “both” participants had greater total severity on the NPI-Q compared to those with “neither” or with amnestic deficits only.

Table 2. Functional and neuropsychiatric summary scores stratified by mutually exclusive MCI subtypes.

Mean (standard deviation) presented for CDR-Global, CDR-Sum, NPI-Q Total Severity (sum of severity for all NPI-Q domains), GDS total, and Hachinski Ischemia Scale scores, stratified by mutually exclusive MCI subtypes. Covariates include MCI subtype, age, education, and sex. The statistic used was ANOVA with post-hoc Tukey’s HSD adjustment for 4-way comparison within each ANOVA. P-values <.05 after adjustment for multiple comparisons within 12 NPI domains using Holms’ procedure are marked with *.

Variable
[Mean(SD)]		 All MCI
(N=1779)		 Neither aMCI
nor exMCI
(N=158)		 aMCI only
(N=1005)		 exMCI
only
(N=242)		 Both aMCI
and exMCI
(N=374)		 F3,1772 p
(unadjusted)		 Post-hoc
comparisons
MMSE 27.8 (7.5) 28.8 (9.8) 28.1 (8.6) 27.2 (3.2) 26.5 (4.7) 5.84 .0006* aMCI,
neither>both
aMCI>exMCI
CDR-Global .46 (.59) .30 (.28) .50 (.69) .38 (.24) .49 (.52) 7.52 .0001* aMCI,
Both>neither
CDR-Sum 1.6 (5.8) .72 (1.01) 1.72 (7.0) 1.26 (1.3) 1.86 (5.2) 1.95 .12
NPI-Q (total
severity)		 2.0 (2.9) 1.5 (2.6) 1.8 (2.8) 2.4 (3.2) 2.4 (3.1) 5.29 .0002* Both,
exMCI>neither
GDS Total 2.5 (3.9) 2.1 (2.3) 2.3 (2.6) 3.0 (6.2) 2.8 (5.3) 2.97 .03 exMCI>neither
Hachinski
Ischemic Scale		 1.1 (1.5) 1.1 (1.5) .92 (1.2) 1.5 (1.8) 1.4 (1.8) 19.19 <.0001* Both,
exMCI>neither,
aMCI
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The prevalence of NPI-Q symptoms by domain is presented in table 3A and the severity of NPI-Q symptoms by domain in table 3B. The severity of anxiety varied by MCI subtype such that participants with both amnestic and executive dysfunction had higher anxiety scores compared to those with neither. Executive dysfunction was associated with greater prevalence and severity of agitation, disinhibition, and irritability as well as greater severity of sleep problems, but these associations were no longer significant after adjustment for multiple comparisons.

Table 3. Prevalence and severity of NPI-Q domains stratified by mutually exclusive MCI subtypes.

The prevalence (3A) and severity (3B) of individual NPI-Q domains are presented stratified by mutually exclusive MCI subtypes.. Prevalence (%) was reported according to NPI-Q responses (“present” or “absent”). The statistic used was χ2 (df=3). Severity mean (SD) scores ranged from 1 (mild) to 3 (severe). The statistic used was ANOVA with post-hoc Tukey’s HSD adjustment for 4-way comparison within each ANOVA. Covariates include MCI subtype, age, education, sex, and MMSE. P-values <.05 after adjustment for multiple comparisons within 12 NPI domains using Holms’ procedure are marked with *.

Table 3A Prevalence (%)
Variable All MCI
(N=1648)		 Neither aMCI nor
exMCI (N=144)		 aMCI only
(N=922)		 exMCI only
(N=227)		 Both aMCI and
exMCI (N=355)		 χ2(3) p
(unadjusted)
Delusions 4.25 2.08 4.23 3.52 5.63 3.63 .30
Hallucinations 1.82 2.08 1.30 3.08 2.25 3.84 .28
Agitation 15.8 13.2 14.5 15.9 20.3 7.19 .06
Depression 27.3 22.9 27.1 29.1 28.2 1.91 .59
Anxiety 18.5 15.3 16.8 17.6 24.5 11.3 .01
Elation 1.64 .69 1.63 1.32 2.25 1.77 .62
Apathy 16.1 11.1 15.5 18.1 18.6 5.16 .16
Disinhibition 7.65 4.17 6.83 12.3 8.17 10.53 .015
Irritability 24.9 14.6 24.4 26.9 29.0 12.0 .007
Aberrant motor 5.46 6.25 4.66 8.81 5.07 6.35 .096
Sleep 18.8 18.1 17.1 22.5 21.1 4.98 .17
Appetite 10.7 9.03 9.98 11.0 12.2 3.32 .34
Table 3B Severity (range 0-3)
Variable
[Mean(SD)]		 All MCI
(N=1779)		 Neither aMCI
nor exMCI
(N=158)		 aMCI only
(N=1005)		 exMCI
only
(N=242)		 Both aMCI
and exMCI
(N=374)		 F3,1771 p
(unadjusted)		 Post-hoc
comparisons
Delusions .056 (.31) .019 (.14) .058 (.32) .041 (.24) .075 (.35) 1.24 .14
Hallucinations .022 (.19) .044 (.35) .014 (.15) .037 (.23) .021 (.14) 1.84 .14
Agitation .19 (.52) .15 (.42) .18 (.50) .18 (.46) .27 (.62) 5.82 .04 Both > neither
Depression .34 (.65) .30 (.63) .32 (.61) .42 (.77) .37 (.65) 1.20 .31
Anxiety .25 (.61) .19 (.51) .22 (.56) .28 (.71) .33 (.68) 4.16 .0002* Both > neither
Elation .020 (.18) .0063 (.080) .018 (.15) .012 (.11) .037 (.28) 1.70 .16
Apathy .21 (.54) .13 (.44) .19 (.52) .26 (.60) .24 (.58) 1.76 .15 exMCI>neither
Disinhibition .091 (.36) .044 (.24) .82 (.35) .14 (.42) .099 (.37) 2.74 .04 exMCI>neither
Irritability .31 (.64) .19 (.53) .30 (.62) .37 (.70) .37 (.68) 3.02 .03 Both,
exMCI>neither
Aberrant motor
behavior		 .064 (.30) .088 (.40) .054 (.28) .099 (.35 ) .053 (.25) 1.81 .14
Sleep .26 (.64) .23 (.56) .23 (.60) .37 (.78) .30 (.67) 2.75 .04 exMCI>aMCI,
neither
Appetite .15 (.50) .13 (.48) .13 (.46) .15 (.48) .20 (.60) 1.53 .20
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MCI subtyped dichotomously (amnestic vs. nonamnestic, executive dysfunction vs. no executive dysfunction)

The association of executive dysfunction with greater severity of neuropsychiatric symptoms led us to examine two dichotomies for MCI subtyping: amnestic vs. nonamnestic and executive dysfunction vs. no executive dysfunction.

Functional impairment and neuropsychiatric severity scores are presented in table 4. Amnestic deficits were associated with greater functional impairment on CDR-Global and with lower Hachinski scores. Executive dysfunction was associated with lower MMSE scores and with greater NPI-Q total severity, GDS, and Hachinski scores.

Table 4. Functional and neuropsychiatric summary scores stratified by amnestic and executive dysfunction.

Mean (standard deviation) presented for CDR-Global, CDR-Sum, NPI-Q Total Severity (sum of severity for all NPI-Q domains), GDS total, and Hachinski Ischemia Scale scores, stratified by the presence or absence of amnestic and executive dysfunction. Covariates include presence or absence of amnestic or executive dysfunction, age, education, and sex. The statistical method was ANOVA. P-values <.05 after adjustment for multiple comparisons using Holms’ procedure are marked with *.

Variable
[Mean(SD)]		 aMCI
(N=1379)		 Non-aMCI
(N=400)		 F 1,1771 p exMCI
(N=616)		 Non-exMCI
(N=1163)		 F 1,1771 p
(unadjusted)
MMSE 27.7 (7.8) 27.9 (6.7) .05 .82 26.8 (4.19) 28.3 (8.77) 15.5 .0001*
CDR-Global .50 (.65) .25 (.26) 20.92 <.0001* .45 (.44) .47 (.66) .60 .44
CDR-Sum 1.76 (6.60) 1.04 (1.21) 5.00 .026 1.62 4.15 .00 .96
NPI-Q (total
severity)		 1.95 (2.91) 2.02 (2.98) .07 .80 2.37 (3.15) 1.75 (2.78) 14.6 .0001*
GDS Total 2.41 (3.55) 2.63 (5.03) .37 .54 2.87 (5.65) 2.25 (2.58) 7.95 .005*
Hachinski Ischemic
Scale		 1.05 (1.40) 1.33 (1.72) 14.6 .0001* 1.44 (1.80) .94 (1.24) 47.55 <.0001*
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The prevalence of NPI-Q symptoms by domain is presented in table 5A and the severity of NPI-Q symptoms by domain in table 5B. Amnestic deficits were associated with greater prevalence and severity of aberrant motor behavior and greater severity of hallucinations, while executive deficits were associated with greater prevalence and severity of agitation, anxiety, disinhibition, irritability, and sleep problems. However, none of the associations in table 6 were statistically significant after adjustment for multiple comparisons.

Table 5. Prevalence and severity of NPI-Q domains stratified by amnestic and executive dysfunction.

The prevalence (6A) and severity (6B) of individual NPI-Q domains are presented, stratified by presence or absence of amnestic or executive dysfunction. Prevalence (%) was reported according to NPI-Q responses (“present” or “absent”). The statistic used was χ2 (df=1). Severity mean (SD) scores ranged from 1 (mild) to 3 (severe). The statistic used was ANOVA with post-hoc Tukey’s HSD adjustment for 4-way comparisons within each ANOVA. Covariates included presence of amnestic or executive dysfunction, age, education, sex, and MMSE. P-values <.05 after adjustment for multiple comparisons within 12 NPI domains using Holms’ procedure are marked with *.

Table 5A Prevalence (%)
Variable aMCI
(N=1379)		 Non-aMCI
(N=400)		 χ2(1) p exMCI
(N=616)		 Non-exMCI
(N=1163)		 χ2(1) p
(unadjusted)
Delusions 4.62 2.96 1.94 .16 4.81 3.94 .70 .40
Hallucinations 1.57 2.70 2.05 .15 2.58 1.41 2.99 .089
Agitation 16.1 14.8 .37 .54 18.6 14.4 4.99 .03
Depression 27.4 26.7 .076 .78 28.5 26.6 .74 .39
Anxiety 19.0 16.7 .96 .33 21.8 16.6 6.81 .009
Elation 1.80 1.08 .93 .33 1.89 1.50 .35 .55
Apathy 16.4 15.4 .21 .64 18.4 14.9 3.35 .067
Disinhibition 7.20 9.16 1.56 .21 9.79 6.57 5.88 .015
Irritability 25.7 22.1 1.97 .16 28.2 23.1 5.24 .022
Aberrant motor
behavior		 4.78 7.82 5.15 .02 6.53 4.88 1.99 .16
Sleep 18.3 20.8 1.18 .28 21.7 17.3 4.75 .029
Appetite 10.9 10.2 .12 .73 12.4 9.85 2.50 .11
Table 5B Severity (range 0-3)
Variable
[Mean(SD)]		 aMCI
(N=1379)		 Non-aMCI
(N=400)		 F1,1773 p exMCI
(N=616)		 Non-exMCI
(N=1163)		 F1,1773 p
(unadjusted)
Delusions .062 (.33) .033 (.20) 2.81 .094 .061 (.31) .052 (.30) .17 .67
Hallucinations .016 (.15) .04 (.28) 5.17 .023 .028 (.18) .019 (.019) .62 .43
Agitation .20 (.54) .17 (.45) 1.22 .27 .24 (.57) .17 (.49) 4.35 .037
Depression .33 (.63) .37 (.72) .45 .50 .39 (.33) .32 (.61) 2.88 .090
Anxiety .25 (.60) .25 (.64) .20 .65 .31 (.69) .21 (.55) 7.73 .0055
Elation .023 (.20) .01 (.10) 2.57 .11 .027 (.23) .016 (.15) .80 .37
Apathy .21 (.54) .21 (.55) .00 .98 .25 (.59) .18 (.51) 3.62 .057
Disinhibition .086 (.35) .11 (.37) .85 .36 .12 (.39) .077 (.33) 4.45 .035
Irritability .32 (.64) .3 (.65) .26 .61 .37 (.69) .28 (.61) 5.86 .016
Aberrant motor
behavior		 .054 (.27) .095 (.37) 5.28 .022 .071 (.29) .059 (.30) .20 .65
Sleep .25 (.62) .32 (.71) 2.76 .097 .33 (.72) .23 (.59) 6.27 .012
Appetite .15 (.50) .14 (.48) .11 .74 .18 (.56) .13 (.46) 3.12 .077
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Discussion

We present data comparing NPS in several subtypes of MCI. The prevalence of NPS in the overall cohort was similar to other published reports. For example, using the NPI-Q we report a depression prevalence of 27.3% compared to the CHS, which reported a prevalence of 20% (Lyketsos et al., 2002a). Comparable figures for apathy are 16% in this cohort and 15% in the CHS; for irritability, the prevalence here (25%) was higher than in the CHS (15%).

The overall severity of NPS was not high (table 2), nor were prevalences and severities in individual NPI domains (table 3). Nonetheless we were able to observe associations between MCI subtypes and NPS: executive dysfunction (with or without associated amnestic deficits) was associated with greater NPI-Q total severity and GDS, and with worse anxiety specifically. Thus our hypoe=thesis waqs supported by these data. Although the associations were not significant after adjustment for multiple comparisons, executive dysfunction was associated with several other NPI domains including agitation, disinhibition, irritability, and sleep problems. While these associations may be due to chance, it is notable that for each of these domains the presence of executive dysfunction predicted greater severity and/or prevalence of certain NPS, suggesting a characteristic pattern of NPS associated with executive dysfunction in MCI.

We observed relatively minor differences in NPS between participants with amnestic vs. non-amnestic MCI, similar to reports from CHS (Lopez, Becker, Sweet, 2005) and the Mayo Clinic Study of Aging (Geda et al., 2008). These symptoms are similar to those recently proposed as characteristic of MCI (Geda et al., 2008), of “Depression of AD” (Lyketsos et al., 2001; Lyketsos and Olin, 2002; Olin et al., 2002a; Olin et al., 2002b; Rosenberg et al., 2005; Appleby et al., 2007) and the syndrome of late life depression with executive dysfunction (Alexopoulos, 2002).

These data suggest that the pattern of NPS in exMCI is similar to depression in AD and to the late life depression executive dysfunction syndrome. It is possible that this NPS profile is prodromal to a similar profile in AD, and its presence may signal a greater likelihood of dementia development in MCI participants. If borne out in longitudinal studies this finding would be important since NPS and particularly depression add significantly to the burden of AD for both patients and caregivers (Teri, 1997). Identifying these symptoms at an earlier stage of disease such as MCI offers opportunities for earlier intervention. While the overall severity of symptoms is relatively low and well within the range of “subsyndromal” symptoms, it is possible that this relatively mild degree of symptom severity will predict prognosis of cognitive, functional, and neuropsychiatric symptoms. These results shed new light on the nosology and subtyping of MCI. It is possible that executive dysfunction and a characteristic NPS profile are associated with prodromal AD, and conceivably this profile might constitute a subtype of prodromal AD with implications for prognosis and treatment.

The study has several limitations including 1) limited number of neuropsychiatric measures; 2) cross-sectional design, preventing prognostic inferences; 3) and study of a referral population which may skew these results towards a more “ill” population. However, the prevalence of NPS we report is close to that found in the CHS which is a population-based sample (Lopez, Becker, Sweet, 2005); 4) low levels of symptom severity limit generalizability of these findings, which may not be applicable to persons suffering from a primary diagnosis of major depression with co-morbid cognitive deficits. The study has several strengths including 1) very large multi-center cohort of MCI participants characterized with standardized methods; 2) clinical diagnoses of MCI and its subtypes by experienced interdisciplinary teams and current consensus-criteria.

In conclusion, we report that in a large well-characterized MCI cohort, executive dysfunction is associated with greater severity of NPS, specifically depression, anxiety, agitation, apathy, disinhibition, irritability, and sleep disturbance. These results may have implications for the treatment of MCI and its nosology, and merit follow-up longitudinal studies.

Key Points.

- Few differences in neuropsychiatric symptoms were found between participants with amnestic and those with non-amnestic MCI.

-Participants with MCI and executive dysfunction had more neuropsychiatric symptoms and depression, including a symptom constellation similar to depression of Alzheimer’s disease, including depression, agitation, anxiety, apathy, disinhibition, irritability, appetite and sleep disturbances.

Acknowledgments

Sponsors: National Institute of Aging 1 K08 AG029157-01A1 (to PBR) ,U01 AG016976 (to the National Alzheimer’s Coordinating Center), National Institute of Mental Health 1U01MH066136 (to CGL)

Footnotes

Previously presented at the 4th International Congress on Vascular, Cognitive, and Behavioral Disorders, Singapore, January 16, 2009.

References

  1. Aickin M, Gensler H. Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods. Am. J. Public Health. 1996;86:726–728. doi: 10.2105/ajph.86.5.726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Alexopoulos GS. Frontostriatal and limbic dysfunction in late-life depression. Am. J. Geriatr. Psychiatry. 2002;10:687–695. [PubMed] [Google Scholar]
  3. Alexopoulos GS, Meyers BS, Young RC, Campbell S, Silbersweig D, Charlson M. ‘Vascular depression’ hypothesis. Arch. Gen. Psychiatry. 1997;54:915–922. doi: 10.1001/archpsyc.1997.01830220033006. [DOI] [PubMed] [Google Scholar]
  4. Appleby BS, Roy P, Valenti A, Lee HB. Diagnosis and treatment of depression in Alzheimer’s disease: impact on mood and cognition. Panminerva Med. 2007;49:139–149. [PubMed] [Google Scholar]
  5. Armitage SG. An analysis of certain psychological tests used in the evaluation of brain injury. Psych Mono. 1946;60:1–48. [Google Scholar]
  6. Beekly DL, Ramos EM, van Belle G, Deitrich W, Clark AD, Jacka ME, Kukull WA, NIA-Alzheimer’s Disease Centers The National Alzheimer’s Coordinating Center (NACC) Database: an Alzheimer disease database. Alzheimer Dis. Assoc. Disord. 2004;18:270–277. [PubMed] [Google Scholar]
  7. Beekly DL, Ramos EM, Lee WW, Deitrich WD, Jacka ME, Wu J, Hubbard JL, Koepsell TD, Morris JC, Kukull WA, NIA Alzheimer’s Disease Centers The National Alzheimer’s Coordinating Center (NACC) database: the Uniform Data Set. Alzheimer Dis. Assoc. Disord. 2007;21:249–258. doi: 10.1097/WAD.0b013e318142774e. 10.1097/WAD.0b013e318142774e. [DOI] [PubMed] [Google Scholar]
  8. Burke WJ, Roccaforte WH, Wengel SP. The short form of the Geriatric Depression Scale: a comparison with the 30-item form. J. Geriatr. Psychiatry Neurol. 1991;4:173–178. doi: 10.1177/089198879100400310. [DOI] [PubMed] [Google Scholar]
  9. Busse A, Hensel A, Guhne U, Angermeyer MC, Riedel-Heller SG. Mild cognitive impairment: long-term course of four clinical subtypes. Neurology. 2006;67:2176–2185. doi: 10.1212/01.wnl.0000249117.23318.e1. 10.1212/01.wnl.0000249117.23318.e1. [DOI] [PubMed] [Google Scholar]
  10. Cummings JL, Mega M, Gray K, Rosenberg-Thompson S, Carusi DA, Gornbein J. The Neuropsychiatric Inventory: comprehensive assessment of psychopathology in dementia. Neurology. 1994;44:2308–2314. doi: 10.1212/wnl.44.12.2308. [DOI] [PubMed] [Google Scholar]
  11. Dickerson BC, Salat DH, Bates JF, Atiya M, Killiany RJ, Greve DN, Dale AM, Stern CE, Blacker D, Albert MS, Sperling RA. Medial temporal lobe function and structure in mild cognitive impairment. Ann. Neurol. 2004;56:27–35. doi: 10.1002/ana.20163. 10.1002/ana.20163 [doi] [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fischer P, Jungwirth S, Zehetmayer S, Weissgram S, Hoenigschnabl S, Gelpi E, Krampla W, Tragl KH. Conversion from subtypes of mild cognitive impairment to Alzheimer dementia. Neurology. 2007;68:288–291. doi: 10.1212/01.wnl.0000252358.03285.9d. 10.1212/01.wnl.0000252358.03285.9d. [DOI] [PubMed] [Google Scholar]
  13. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 1975;12:189–198. doi: 10.1016/0022-3956(75)90026-6. 0022-3956(75)90026-6 [pii] [DOI] [PubMed] [Google Scholar]
  14. Forti P, Maioli F, Pisacane N, Rietti E, Montesi F, Ravaglia G. Atrial fibrillation and risk of dementia in non-demented elderly subjects with and without mild cognitive impairment. Neurol. Res. 2006;28:625–629. doi: 10.1179/016164106X130461. 10.1179/016164106X130461 [doi] [DOI] [PubMed] [Google Scholar]
  15. Gauthier S, Reisberg B, Zaudig M, Petersen RC, Ritchie K, Broich K, Belleville S, Brodaty H, Bennett D, Chertkow H, Cummings JL, de Leon M, Feldman H, Ganguli M, Hampel H, Scheltens P, Tierney MC, Whitehouse P, Winblad B, International Psychogeriatric Association Expert Conference on mild cognitive impairment Mild cognitive impairment. Lancet. 2006;367:1262–1270. doi: 10.1016/S0140-6736(06)68542-5. 10.1016/S0140-6736(06)68542-5. [DOI] [PubMed] [Google Scholar]
  16. Geda YE, Roberts RO, Knopman DS, Petersen RC, Christianson TJ, Pankratz VS, Smith GE, Boeve BF, Ivnik RJ, Tangalos EG, Rocca WA. Prevalence of neuropsychiatric symptoms in mild cognitive impairment and normal cognitive aging: population-based study. Arch. Gen. Psychiatry. 2008;65:1193–1198. doi: 10.1001/archpsyc.65.10.1193. 10.1001/archpsyc.65.10.1193. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Goodglass H, Kaplan E. The Assessment of Aphasia and Related Disorders. 1983.
  18. Kaufer DI, Cummings JL, Ketchel P, Smith V, MacMillan A, Shelley T, Lopez OL, DeKosky ST. Validation of the NPI-Q, a brief clinical form of the Neuropsychiatric Inventory. J. Neuropsychiatry Clin. Neurosci. 2000;12:233–239. doi: 10.1176/jnp.12.2.233. [DOI] [PubMed] [Google Scholar]
  19. Lichtenberg PA, Marcopulos BA, Steiner DA, Tabscott JA. Comparison of the Hamilton Depression Rating Scale and the Geriatric Depression Scale: detection of depression in dementia patients. Psychol. Rep. 1992;70:515–521. doi: 10.2466/pr0.1992.70.2.515. [DOI] [PubMed] [Google Scholar]
  20. Lopez OL, Becker JT, Sweet RA. Non-cognitive symptoms in mild cognitive impairment subjects. Neurocase. 2005;11:65–71. doi: 10.1080/13554790490896893. P565W45M84V5Q107 [pii];10.1080/13554790490896893 [doi] [DOI] [PubMed] [Google Scholar]
  21. Lyketsos CG, Olin J. Depression in Alzheimer’s disease: overview and treatment. Biol. Psychiatry. 2002;52:243–252. doi: 10.1016/s0006-3223(02)01348-3. [DOI] [PubMed] [Google Scholar]
  22. Lyketsos CG, Lopez O, Jones B, Fitzpatrick AL, Breitner J, DeKosky S. Prevalence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study. JAMA. 2002a;288:1475–1483. doi: 10.1001/jama.288.12.1475. joc20689 [pii] [DOI] [PubMed] [Google Scholar]
  23. Lyketsos CG, Lopez O, Jones B, Fitzpatrick AL, Breitner J, DeKosky S. Prevalence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study. JAMA. 2002b;288:1475–1483. doi: 10.1001/jama.288.12.1475. [DOI] [PubMed] [Google Scholar]
  24. Lyketsos CG, Steinberg M, Tschanz JT, Norton MC, Steffens DC, Breitner JC. Mental and behavioral disturbances in dementia: findings from the Cache County Study on Memory in Aging. Am. J. Psychiatry. 2000;157:708–714. doi: 10.1176/appi.ajp.157.5.708. [DOI] [PubMed] [Google Scholar]
  25. Lyketsos CG, Sheppard JM, Steinberg M, Tschanz JA, Norton MC, Steffens DC, Breitner JC. Neuropsychiatric disturbance in Alzheimer’s disease clusters into three groups: the Cache County study. Int. J. Geriatr. Psychiatry. 2001;16:1043–1053. doi: 10.1002/gps.448. 10.1002/gps.448 [pii] [DOI] [PubMed] [Google Scholar]
  26. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993;43:2412–2414. doi: 10.1212/wnl.43.11.2412-a. [DOI] [PubMed] [Google Scholar]
  27. Morris JC, Heyman A, Mohs RC, Hughes JP, van Belle G, Fillenbaum G, Mellits ED, Clark C. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology. 1989;39:1159–1165. doi: 10.1212/wnl.39.9.1159. [DOI] [PubMed] [Google Scholar]
  28. Morris JC, Weintraub S, Chui HC, Cummings J, Decarli C, Ferris S, Foster NL, Galasko D, Graff-Radford N, Peskind ER, Beekly D, Ramos EM, Kukull WA. The Uniform Data Set (UDS): clinical and cognitive variables and descriptive data from Alzheimer Disease Centers. Alzheimer Dis. Assoc. Disord. 2006;20:210–216. doi: 10.1097/01.wad.0000213865.09806.92. 10.1097/01.wad.0000213865.09806.92. [DOI] [PubMed] [Google Scholar]
  29. Murphy CF, Alexopoulos GS. Longitudinal association of initiation/perseveration and severity of geriatric depression. Am. J. Geriatr. Psychiatry. 2004;12:50–56. [PubMed] [Google Scholar]
  30. Olin JT, Katz IR, Meyers BS, Schneider LS, Lebowitz BD. Provisional diagnostic criteria for depression of Alzheimer disease: rationale and background. Am. J. Geriatr. Psychiatry. 2002a;10:129–141. [PubMed] [Google Scholar]
  31. Olin JT, Schneider LS, Katz IR, Meyers BS, Alexopoulos GS, Breitner JC, Bruce ML, Caine ED, Cummings JL, Devanand DP, Krishnan KR, Lyketsos CG, Lyness JM, Rabins PV, Reynolds CF, 3rd, Rovner BW, Steffens DC, Tariot PN, Lebowitz BD. Provisional diagnostic criteria for depression of Alzheimer disease. Am. J. Geriatr. Psychiatry. 2002b;10:125–128. [PubMed] [Google Scholar]
  32. Pavlik VN, Doody RS, Massman PJ, Chan W. Influence of premorbid IQ and education on progression of Alzheimer’s disease. Dement. Geriatr. Cogn. Disord. 2006;22:367–377. doi: 10.1159/000095640. DEM2006022004367 [pii]; 10.1159/000095640 [doi] [DOI] [PubMed] [Google Scholar]
  33. Petersen RC. Mild cognitive impairment as a diagnostic entity. J. Intern. Med. 2004;256:183–194. doi: 10.1111/j.1365-2796.2004.01388.x. 10.1111/j.1365-2796.2004.01388.x. [DOI] [PubMed] [Google Scholar]
  34. Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, Ritchie K, Rossor M, Thal L, Winblad B. Current concepts in mild cognitive impairment. Arch. Neurol. 2001;58:1985–1992. doi: 10.1001/archneur.58.12.1985. nsa10002 [pii] [DOI] [PubMed] [Google Scholar]
  35. Ravaglia G, Forti P, Maioli F, Martelli M, Servadei L, Brunetti N, Pantieri G, Mariani E. Conversion of mild cognitive impairment to dementia: predictive role of mild cognitive impairment subtypes and vascular risk factors. Dement. Geriatr. Cogn. Disord. 2006a;21:51–58. doi: 10.1159/000089515. 10.1159/000089515. [DOI] [PubMed] [Google Scholar]
  36. Ravaglia G, Forti P, Maioli F, Martelli M, Servadei L, Brunetti N, Pantieri G, Mariani E. Conversion of mild cognitive impairment to dementia: predictive role of mild cognitive impairment subtypes and vascular risk factors. Dement. Geriatr. Cogn. Disord. 2006b;21:51–58. doi: 10.1159/000089515. 10.1159/000089515. [DOI] [PubMed] [Google Scholar]
  37. Rosenberg PB, Onyike CU, Katz IR, Porsteinsson AP, Mintzer JE, Schneider LS, Rabins PV, Meinert CL, Martin BK, Lyketsos CG, Depression of Alzheimer’s Disease Study Clinical application of operationalized criteria for ’Depression of Alzheimer’s Disease’. Int. J. Geriatr. Psychiatry. 2005;20:119–127. doi: 10.1002/gps.1261. 10.1002/gps.1261 [doi] [DOI] [PubMed] [Google Scholar]
  38. Steinberg M, Sheppard JM, Tschanz JT, Norton MC, Steffens DC, Breitner JC, Lyketsos CG. The incidence of mental and behavioral disturbances in dementia: the cache county study. J. Neuropsychiatry Clin. Neurosci. 2003;15:340–345. doi: 10.1176/jnp.15.3.340. [DOI] [PubMed] [Google Scholar]
  39. Steinberg M, Shao H, Zandi P, Lyketsos CG, Welsh-Bohmer KA, Norton MC, Breitner JC, Steffens DC, Tschanz JT, Cache County Investigators Point and 5-year period prevalence of neuropsychiatric symptoms in dementia: the Cache County Study. Int. J. Geriatr. Psychiatry. 2007 doi: 10.1002/gps.1567. 10.1002/gps.1858. [DOI] [PubMed] [Google Scholar]
  40. Swanwick GR, Coen RF, Lawlor BA, O’Mahony D, Walsh JB, Coakley D. Utility of ischemic scores in the differential diagnosis of Alzheimer’s disease and ischemic vascular dementia. Int. Psychogeriatr. 1996;8:413–424. doi: 10.1017/s1041610296002773. [DOI] [PubMed] [Google Scholar]
  41. Teri L. Behavior and caregiver burden: behavioral problems in patients with Alzheimer disease and its association with caregiver distress. Alzheimer Dis. Assoc. Disord. 1997;11(Suppl 4):S35–8. [PubMed] [Google Scholar]
  42. Tschanz JT, Welsh-Bohmer KA, Lyketsos CG, Corcoran C, Green RC, Hayden K, Norton MC, Zandi PP, Toone L, West NA, Breitner JC, Cache County Investigators Conversion to dementia from mild cognitive disorder: the Cache County Study. Neurology. 2006;67:229–234. doi: 10.1212/01.wnl.0000224748.48011.84. 67/2/229 [pii]; 10.1212/01.wnl.0000224748.48011.84 [doi] [DOI] [PubMed] [Google Scholar]
  43. Wechsler D. Manual: Wechsler Adult Intelligence Scale. 1955.
  44. Wechsler D, Stone CP. Manual: Wechsler Memory Scale. 1973.
  45. Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, Nordberg A, Backman L, Albert M, Almkvist O, Arai H, Basun H, Blennow K, de Leon M, DeCarli C, Erkinjuntti T, Giacobini E, Graff C, Hardy J, Jack C, Jorm A, Ritchie K, van Duijn C, Visser P, Petersen RC. Mild cognitive impairment--beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J. Intern. Med. 2004;256:240–246. doi: 10.1111/j.1365-2796.2004.01380.x. 10.1111/j.1365-2796.2004.01380.x. [DOI] [PubMed] [Google Scholar]
  46. Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, Leirer VO. Development and validation of a geriatric depression screening scale: a preliminary report. J. Psychiatr. Res. 1982;17:37–49. doi: 10.1016/0022-3956(82)90033-4. [DOI] [PubMed] [Google Scholar]

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