Participants

Sixty-three people with a DSM–IV diagnosis of bipolar affective disorder (American Psychiatric Association, 1994) were recruited from out-patient clinics in secondary and tertiary care in the north-east of England; 54 had bipolar type I disorder, 9 had type II and 5 were rapid-cycling. Diagnoses were confirmed using the Structured Clinical Interview for DSM–IV (SCID; Reference First, Spitzer and GibbonFirst et al, 1997). Illness characteristics were derived from retrospective life charts constructed from patient interview and hospital medical records (Reference Leverich and PostLeverich & Post, 1996). Patients were excluded if they were taking corticosteroids or antihypertensive medication, had any other current Axis I diagnosis or had a neurological or medical condition. A history of substance or alcohol misuse in the past 6 months (6 patients met DSM–IV criteria for a previous history of alcohol dependence, 4 met criteria for a previous history of substance dependence and 1 patient met criteria for previous substance and alcohol dependence) or electro-convulsive therapy (ECT) in the past year also led to exclusion.

Euthymia was prospectively defined as scores of 7 or below on both the Hamilton Rating Scale for Depression (HRSD; Reference HamiltonHamilton, 1960) and the Young Mania Rating Scale (YMRS; Reference Young, Biggs and ZieglerYoung et al, 1978) at initial assessment and after 1 month. Patients also completed the Beck Depression Inventory (BDI; Reference Beck, Ward and MendelsonBeck et al, 1961) and the Altman Mania Rating Scale (AMRS; Reference Altman, Hedeker and PetersonAltman et al, 1997) each week during the euthymia verification month. Saliva samples collected at 08.00 h, 12.00 h, 16.00 h and 20.00 h on the day before testing confirmed that patients were eucortisolaemic (i.e. exhibited normal rhythm and secretion of cortisol), as measured by directed disequilibrium radioimmunoassay. With the exception of 3 patients who were taking no medication, all patients were stabilised on prophylactic medication at test; 40 were receiving combination treatment. Demographic and clinical characteristics of the sample are presented in Table 1.

Table 1 Demographic and clinical characteristics

Variable	Control group (n=63)	Patient group (n=63)	Inferential test statistic	P
Demographic characteristics
Gender (female:male), n:n	26:37	26:37
Age, years: mean (s.d.)	45.4 (9.1)	44.4 (8.6)	0.61	0.540
Education, years: mean (s.d.)	14.2 (3.1)	14.24 (3.0)	-0.12	0.906
Pre-morbid IQ: mean (s.d.)	110.0 (9.2)	109.6 (10.2)	0.22	0.824
MMSE score: mean (s.d.)	29.8 (0.6)	29.6 (0.7)	3236.5	0.013
Handedness (right:left:mixed), n:n:n	58:5:0	56:4:3
Mood rating scores: mean (s.d.)
HRSD initial assessment		2.1 (1.7)
YMRS initial assessment		1.4 (2.0)
BDI
Week 1		6.1 (5.8)
Week 2		5.1 (5.4)
Week 3		4.6 (5.6)
Week 4	1.9 (2.3)	4.8 (5.4)	1396.0	0.003
AMRS
Week 1		3.2 (3.3)
Week 2		2.3 (2.4)
Week 3		2.1 (2.6)
Week 4	1.6 (2.0)	2.2 (2.6)	1788.5	0.313
HRSD post-month assessment	0.7 (1.1)	1.4 (1.6)	1336.0	0.001
YMRS post-month assessment	0.3 (0.8)	0.8 (1.5)	1654.0	0.031
BDI post-month assessment	1.8 (2.2)	4.0 (4.9)	1384.0	0.003
AMRS post-month assessment	1.6 (1.9)	1.9 (2.5)	1912.5	0.713
Clinical characteristics
Age at illness onset, years
Mean (s.d.)		25.3 (7.2)
Range		12-42
Duration of illness, years
Mean (s.d.)		19.5 (10.0)
Range		0.58-39
No. of hospital admissions
Mean (s.d.)		5.0 (6.1)
Range		0-40
No. of depressed episodes
Mean (s.d.)		12.0 (16.4)
Range		0-88
Lifetime months of depression
Mean (s.d.)		29.5 (40.3)
Range		0-242
No. of manic episodes
Mean (s.d.)		10.3 (17.4)
Range		1-98
Lifetime months of mania
Mean (s.d.)		9.8 (16.4)
Range		0.5-121
Duration since last episode, months
Mean (s.d.)		27.3 (40.9)
Range		1-192
Medication
Mood stabilisers, n		56
Antidepressants, n		18
Anticholinergics, n		3
Benzodiazepines, n		4
Antipsychotics (typical:atypical), n:n		11.6
Dosage (CPZeq per day), mg1
Mean (s.d.)		181.6 (146.0)
Range		50-533
No. of previous ECT treatments (n=30)2
Mean (s.d.)		18.1 (26.4)
Range		2-120
Time since last ECT treatment, years2
Mean (s.d.)		17.2 (10.3)
Range		2-37

For the control group, 63 healthy volunteers were recruited from the community by local advertisement. Controls were matched on an individual basis with patients for age (±5 years), gender, race, handedness (Reference Briggs and NebesBriggs & Nebes, 1975), years of education (±3 years), and premorbid IQ (±5 IQ points; Reference NelsonNelson, 1982). Controls were screened for significant medical conditions and were excluded if they had a current or past psychiatric illness (confirmed by SCID) or a family history of affective disorders in a first-degree relative, or were taking any medication other than the oral contraceptive pill. Control participants completed the same clinical ratings as patients on the study day, 1 week after completing a pre-screen AMRS and BDI.

For all participants, historic and current substance use was assessed using DSM–IV criteria and a detailed inventory was derived from the major DSM–IV substance classifications. To exclude people with current alcohol misuse, participants had to have a current alcohol intake of less than 28 units per week for men and 21 units per week for women. The Modified Mini-Mental State Examination (Reference Teng and ChuiTeng & Chui, 1987) was administered on the study day to screen for dementia. The local ethics committee approved the investigation.

Neuropsychological measures

Participants completed a comprehensive battery of neurocognitive tests spanning four broad cognitive domains. To control for the possible effects of diurnal variation on performance, cognitive testing commenced at 14.00 h. Tests were administered according to standard instructions and took about 2 h to complete. The tasks were given in the same order to the whole sample. The instruments administered for each domain were as follows:

1. (a) Psychomotor performance: the Vigil test (response latency) (Reference Cegalis and BowlinCegalis & Bowlin, 1991), Digit Symbol Substitution Test from the Wechsler Adult Intelligence Scale – Revised (WAIS–R; Reference WechslerWechsler, 1981) and the Trail Making Test part A (Reference ReitenReiten, 1958).

2. (b) Attention and executive function: Trail Making Test part B, Vigil (errors of omission and commission), Stroop Neuropsychological Screening Test (Reference Trenerry, Crosson and DeboeTrenerry et al, 1989), the Tower of London task from the Cambridge Neuropsychological Test Automated Battery (CANTAB, Cambridge Cognition Ltd, Cambridge, UK), the Controlled Oral Word Association Test (Reference Benton and HamsherBenton & Hamsher, 1976), the Digits Backward sub-test from the WAIS–R, a computerised version of the Abstract Designs Self-Ordered Pointing Task (SOPT; Reference Petrides and MilnerPetrides & Milner, 1982) and the CANTAB Spatial Working Memory test.

3. (c) Immediate memory: the Digits Forward sub-test from the WAIS–R and the CANTAB Spatial Span.

4. (d) Declarative memory (visual and verbal): the CANTAB Pattern Recognition Memory and Spatial Recognition Memory tasks, CANTAB Simultaneous and Delayed Matching to Sample, CANTAB Paired Associates Learning test and the Rey Auditory Verbal Learning Test (RAVLT; Reference ReyRey, 1964).

The SOPT and CANTAB tasks were presented on a 486 microcomputer fitted with a high-resolution 38 cm touch-screen monitor. Detailed descriptions of the CANTAB tasks are provided in Robbins et al (Reference Robbins, James, Owen and Rabbit1997) and further details regarding the pen-and-paper measures in Lezak (Reference Lezak1995).

Statistical analyses

Analyses were conducted using the Statistical Package for the Social Sciences, version 9 (SPSS, 1998). Data were first examined to see whether they fulfilled the assumptions for parametric analyses. Variables fulfilling these assumptions were analysed by independent samples t-test or analysis of variance (ANOVA), with group (patient or control) as the between-subject factor. For tests with more than one level and the cortisol data, an additional within-subject factor of ‘time’ or ‘problem level’ was added. Where sphericity was violated, within-subject degrees of freedom were adjusted using Greenhouse–Geisser or Huynh–Feldt corrections as appropriate. Adjusted P values are reported, although the original degrees of freedom are also reported for clarity. Data not fulfilling the assumptions of parametric analyses were either subjected to an appropriate transformation or analysed non-parametrically (Reference HowellHowell, 1997).

To calculate clinically significant performance impairments, the proportion of patients scoring on or below the fifth percentile was determined (i.e. – 1.64 standard deviations from the mean of the control sample). Estimates of effect size were calculated for untransformed data using the formula (μ_patients–μ_controls)/σ_pooled (Reference HowellHowell, 1999); the first part of this equation was reversed for tasks where a high score indicates poorer performance (i.e. μ_controls–μ_patients) to standardise the scoring schemes across tasks. All reported P values are two-tailed. To examine the impact of illness severity on neurocognitive performance, correlations between illness characteristics and neurocognitive test variables were calculated using Spearman's method.

Demographic and mood data

There was no significant between-group difference across the demographic variables. On the clinical rating scales patients exhibited few symptoms during the euthymia verification period, although their scores were still significantly higher than the controls on most of the measures completed by both groups (Table 1).

Basal salivary cortisol measures

Basal salivary cortisol samples were collected from 54 people in the control group and 56 patients. Comparison between patients and controls illustrated the expected main effect of time (F _(3,324)=99.18, P<0.0001) but no main effect of group (F _(1,108)=1.13, P=0.29) or group×time interaction (F _(3,324)=0.54, P=0.56). Overall cortisol output did not differ between the groups (P>0.2).

Cognitive measures

Group mean performance and statistical comparisons for all cognitive measures are summarised in Table 2. In tests comprising a delay or difficulty level variable, only main effects and interactions involving group variables are reported below: main effects of delay or difficulty level were significant in all cases (excluding Vigil latency and omissions) but are not presented here. In Table 3, outcome measures from each test are sorted by effect size, with Cohen's conventions used to indicate small, medium and large effects (Reference CohenCohen, 1988). The proportion of patients scoring at or below the fifth percentile of the control group is also presented.

Table 2 Cognitive performance comparisons (untransformed means are reported for clarity)

Measure	Control group (n=63) Mean (s.d.)	Patient group (n=63) Mean (s.d.)	Inferential test statistic	P
Psychomotor performance
Vigil latency, ms	371.6 (55.1)	402.8 (67.3)	9.42	0.003
Digit Symbol Substitution Test	61.2 (10.0)	50.5 (13.2)	5.15	0.000
Trail Making Test part A, s	32.1 (8.8)	37.4 (13.1)	-2.67	0.009
Attention and executive function
Trail Making Test part B, s	65.6 (24.5)	71.4 (26.3)	-1.27	0.206
Vigil total omissions	1.7 (2.3)	5.4 (8.0)	13.72	0.000
Vigil total commissions	1.7 (2.2)	2.6 (3.1)	2.44	0.120
Stroop colour-word trial correct, ms	100.2 (12.0)	90.8 (19.4)	3.23	0.002
Tower of London task1
Minimum move solutions	8.8 (1.6)	7.9 (1.9)	2.88	0.005
Number of excess moves	3.1 (1.8)	4.2 (2.5)	7.50	0.007
Motor initiation time, ms	1535.3 (497.8)	2074.5 (997.5)	14.17	0.000
Motor execution time, average ms per move	1350.4 (488.2)	1566.1 (580.2)	8.90	0.003
Initial thinking time, ms	8888.5 (3175.1)	1023.2 (4499.6)	4.03	0.047
Subsequent thinking time, average ms per move	2346.6 (1172.4)	2929.4 (1361.6)	7.10	0.009
Initial planning time, ms	7353.2 (2963.0)	8157.9 (4330.8)	1.51	0.222
Subsequent planning time, average ms per move	1100.3 (960.37)	1457.8	3.82	0.053
Controlled Oral Word Association Test
Total correct	44.8 (10.7)	40.9 (11.1)	1.98	0.050
Perseverations	1.4 (2.0)	1.4 (1.5)	0.03	0.975
Digits Backward span	5.2 (1.3)	4.7 (1.4)	2.23	0.027
SOPT total errors	10.2 (4.1)	14.3 (5.6)	14.29	0.000
Spatial Working Memory
Total between-search errors1,2	29.1 (17.7)	40.6 (24.2)	6.88	0.010
Strategy score2	34.2 (5.6)	35.4 (5.9)	-1.11	0.267
Immediate memory
Digits Forward span	7.0 (1.2)	6.94 (1.4)	0.29	0.775
Spatial Span	5.9 (1.2)	5.30 (1.3)	2.80	0.006
Declarative memory (LTM)
Pattern Recognition, total % correct	90.1 (9.3)	85.2 (12.9)	1.79	0.076
Spatial Recognition, total % correct	82.0 (10.3)	74.4 (13.1)	3.67	0.000
Matching to Sample
SMTS % correct	96.2 (6.4)	96.2 (6.1)	0.00	1.00
DMTS average % correct1	87.8 (7.2)	81.0 (12.5)	13.94	0.000
Paired Associates Learning
Sets successfully completed	7.9 (0.3)	7.8 (0.5)	2.52	0.014
Completed sets first trials memory score	19.4 (3.7)	17.3 (4.0)	3.05	0.003
Trials to success	14.1 (5.0)	16.6 (6.1)	2.57	0.011
RAVLT
Trial A1	6.5 (1.6)	6.1 (1.5)	1.21	0.229
Learning (Trials A1 to A5)	51.7 (7.9)	46.7 (9.1)	3.23	0.002
List B	6.4 (1.8)	5.6 (1.5)	2.80	0.006
A6	10.7 (2.2)	9.3 (3.0)	2.96	0.004
A7	10.6 (2.7)	9.1 (3.0)	2.94	0.004
Retention % (A5-A7)3	94.3 (11.0)	92.1 (12.2)	1.05	0.300
Recognition correct	13.3 (1.6)	12.1 (2.6)	3.23	0.002
Recognition commissions	1.6 (2.3)	2.2 (2.9)	-1.33	0.187

Table 3 Cognitive performance: effect sizes and percentage of patients scoring below the fifth percentile of the control group

Measure	Domain1	Effect size2	Patients below 5th percentile (%)
Digit symbol substitution	PsychM	0.84	35.5
Mean		0.84	35.5
SOPT total errors	Att/Exec	0.78	34.0
ToL motor initiation time, ms	Att/Exec	0.65	24.6
DMTS average % correct	DeclarM	0.64	23.0
Spatial recognition total % correct	DeclarM	0.62	27.0
Vigil total omissions	Att/Exec	0.58	30.7
Stroop colour-word trial correct, ms	Att/Exec	0.56	26.2
RAVLT learning (trials A1 to A5)	DeclarM	0.56	19.4
RAVLT recognition correct	DeclarM	0.55	22.6
SWM total between-search errors	Att/Exec	0.53	31.8
PAL completed sets 1st trials memory score	DeclarM	0.53	19.7
ToL number of excess moves	Att/Exec	0.52	23.0
ToL minimum move solutions	Att/Exec	0.51	26.2
RAVLT A6	DeclarM	0.51	25.8
RAVLT A7	DeclarM	0.51	21.0
Mean (range)		0.58	25.4 (19.4-34.0)
Vigil latency, ms	PsychM	0.49	19.4
Spatial span	ImmedM	0.49	11.5
RAVLT List B	DeclarM	0.49	4.8
Trail Making Test part A, s	PsychM	0.47	41.9
ToL subsequent thinking time (average ms per move)	Att/Exec	0.45	16.4
PAL sets successfully completed	DeclarM	0.44	21.0
Pattern recognition total % correct	DeclarM	0.43	15.9
ToL motor execution time (average ms per move)	ATT/Exec	0.40	11.5
Backward digit span	Att/Exec	0.39	25.8
ToL subsequent planning time (average ms per move)	Att/Exec	0.35	13.1
FAS total correct	Att/Exec	0.35	11.3
ToL initial thinking time, ms	Att/Exec	0.34	11.5
Vigil total commissions	Att/Exec	0.32	16.1
RAVLT recognition commissions	DeclarM	0.24	11.3
Trail Making Test part B, s	Att/Exec	0.23	11.3
ToL initial planning time, ms	Att/Exec	0.22	8.2
RAVLT trial A1	DeclarM	0.22	3.2
SWM strategy score	Att/Exec	0.20	3.2
Mean (range)		0.36	14.3 (3.2-41.9)
RAVLT % retention (A5-A7)	DeclarM	0.19	11.3
Digits Forward span	ImmedM	0.05	16.1
PAL trials to success	DeclarM	0.05	22.6
SMTS % correct	DeclarM	0.00	6.6
FAS perseverations	Att/Exec	-0.01	3.2
Mean (range)		0.06	12.0 (3.2-22.6)

Post hoc multivariate analysis by neurocognitive domain

Studies of neurocognitive function are frequently at risk of type I error because of the number of comparisons conducted in the analysis. Multiple comparisons are a product of the need to use several tasks to profile the range of different neurocognitive processes. One approach that has been suggested to overcome this problem is to group together tests and outcome measures that have some degree of theoretical overlap (Reference StevensStevens, 2002), i.e. apply to a specific neurocognitive domain. This method was therefore adopted and it confirmed that a significant multivariate statistic (Hotelling's trace) was present in each of the four domains (from Table 2): psychomotor performance (MANOVA=0.244, F=9.86, P<0.001), attention and executive function (MANOVA=0.492, F=3.33, P<0.001), immediate memory (MANOVA=0.061, F=3.63, P=0.029) and declarative memory (MANOVA=0.2389, F=2.17, P=0.014).

Effects of residual mood symptoms

Residual mood symptoms have been found to impair cognition in affective disorders (Reference Ferrier, Stanton and KellyFerrier et al, 1999; Reference Clark, Iversen and GoodwinClark et al, 2002). As patients’ mood scores on many of the clinical rating scales used in this study were significantly higher than those of controls, a series of analyses were performed to rule out this potential confound on the observed deficits. Correlations between the clinical rating scales and neurocognitive tests illustrating between-group differences were first calculated, to establish which deficits might have been influenced by mood. Partial correlations were subsequently performed on any cognitive index that significantly correlated with the mood ratings, to examine whether the previously observed between-group differences on these indices remained when the effect of mood on performance was partialled out. These analyses illustrated that 11 cognitive indices correlated significantly with the rating scales. However, when the effects of mood on these variables were controlled, all between-group effects remained significant (apart from subsequent thinking time on the Tower of London task) when the BDI scores on the day of test and at week 4 were partialled out (P=0.066).

Relationship between illness characteristics and neurocognitive function

To restrict the number of correlations computed between the illness characteristics and the neurocognitive test variables, only those indices illustrating between-group differences were examined. In addition, only the most representative variable from each of the cognitive tasks was included. The results of these analyses are presented in Table 4.

Table 4 Correlations between illness characteristics and impaired neurocognitive performance in patients with bipolar disorder

Measure	Months clinically euthymic	Duration of illness (years)	No. of hospital admissions	No. of depressed episodes	Lifetime months of depression	No. of manic episodes	Lifetime months of mania	No. of previous ECT treatments1	Time since last ECT treatment1	Age at onset (years)
Vigil omissions	0.060	0.283*	0.482***	0.121	0.126	0.168	0.107	-0.013	0.041	-0.035
Trail Making Test part A	-0.061	0.283*	0.201	0.073	0.056	0.000	-0.091	0.258	0.197	0.001
Stroop CW trial	0.022	0.009	0.114	0.010	-0.110	-0.084	-0.001	0.208	0.004	0.016
ToL excess moves	0.036	0.135	-0.058	-0.053	-0.118	-0.061	-0.067	-0.066	0.083	-0.034
FAS total correct	0.231	-0.090	-0.320*	0.008	-0.070	0.050	0.095	0.149	0.033	0.034
Digits Backward span	0.057	-0.156	-0.165	0.145	0.096	0.349**	0.294*	0.054	0.245	-0.081
Spatial Span	-0.062	0.050	0.100	-0.089	-0.077	0.114	0.104	0.046	0.064	-0.167
SWM errors	-0.037	0.217	0.278*	0.197	0.161	0.091	-0.018	0.386*	-0.102	0.008
SOPT total errors	-0.181	0.381**	0.430**	0.298*	0.293*	0.024	-0.034	0.136	-0.247	-0.148
Vigil latency	0.003	0.135	0.030	-0.171	-0.133	-0.033	0.033	-0.058	0.366	0.075
DSST	-0.004	-0.306*	-0.479***	-0.189	-0.230	-0.174	-0.121	-0.153	-0.199	-0.020
Spatial Recognition	0.017	-0.140	-0.023	-0.157	-0.154	0.005	0.089	-0.147	-0.006	-0.120
DMTS	0.085	-0.224	-0.324*	-0.221	-0.261*	0.016	0.157	-0.136	0.130	-0.027
PAL sets completed	0.061	-0.299*	-0.240	-0.124	-0.236	-0.042	0.094	-0.480**	0.257	-0.074
RAVLT (A1-5)	-0.206	-0.231	-0.167	0.025	-0.063	0.045	-0.097	-0.262	0.090	-0.084

Relationship between basal cortisol levels and neurocognitive function

Correlations between cortisol area under the curve and neurocognitive indices were also examined for patients and controls separately. In patients, the only significant correlations observed were for the Stroop colour–word latency (r_s =-0.330, P=0.015), Tower of London excess moves (r_s =-0.312, P=0.022) and verbal fluency on the Controlled Oral Word Association Test (r_s =0.303, P=0.025). In controls, no significant correlation was observed (data not shown).

Previous neuropsychological findings in bipolar disorder

Our findings are consistent with a growing body of evidence that people with bipolar disorder experience a range of cognitive deficits during disease remission (Reference van Gorp, Altshuler and Thebergevan Gorp et al, 1998; Reference Ferrier, Stanton and KellyFerrier et al, 1999; Reference Rubinsztein, Michael and PaykelRubinsztein et al, 2000; Reference Clark, Iversen and GoodwinClark et al, 2002; Reference Martinez-Aran, Vieta and ColomMartinez-Aran et al, 2004). Many studies have used structured interviews and standardised rating scales to demonstrate the euthymic status of patients, but generally their sample sizes were smaller than ours and prospective follow-up or cortisol measurements were not recorded. The majority of studies to date have typically defined patients as impaired on the basis of a between-group difference (from controls) on an arbitrarily selected significance level. However, although a result might be statistically significant, this says nothing about the size of the effect, nor does it guarantee that it is clinically important. Few studies have provided data on the number of patients falling within the clinically impaired range on particular tasks, despite normative data being readily available to do so (but see Reference Rubinsztein, Michael and PaykelRubinsztein et al, 2000). We sought to address this by providing effect sizes alongside statistical significance tests and by calculating the percentage of patients falling below the fifth percentile on the measures employed.

Magnitude of the impairment: statistical v. clinical significance

Previous studies have reported deficits in up to 32% of people with bipolar disorder (Reference Astrup, Fossum and HolmboeAstrup et al, 1959; Reference Bratfos and HaugBratfos & Haug, 1968; Reference Dhingra and RabinsDhingra & Rabins, 1991; Reference Martinez-Aran, Vieta and ColomMartinez-Aran et al, 2000). Our results demonstrate that the proportion affected is extremely variable and is dependent upon the particular task employed. For example, for tasks within a medium to large effect size, on average 25% of patients scored at or below the fifth percentile, although on some tasks (such as the Digit Symbol Substitution Test) the proportion was over 33%. This figure averaged almost 15% for tasks falling in the small to medium effect size range. Even for tasks with little or no between-group difference (i.e. d<0.2), clinically significant deficits were still evident in some individuals. This is of particular clinical importance because these deficits were observed in a cohort of patients who had been euthymic for an average of 27.3 months (median 14 months), suggesting that neurocognitive impairment persists long beyond the point of symptomatic recovery. The enduring nature of this impairment is also highlighted by the absence of association between the length of time patients had been in remission and the extent of neurocognitive impairment.

Factors affecting neurocognitive impairment in bipolar disorder

All but three of the patients in this study were receiving medication at the time of testing, therefore the effects of psychotropic drugs on neurocognitive functioning cannot be excluded. Lithium use, for example, has been shown to have subtle but definite effects on several domains, including psychomotor speed and possibly verbal memory. Similarly, antidepressants have been shown to have cognitive effects, particularly those with anticholinergic properties (Reference Amado-Boccara, Gougoulis and LittreAmado-Boccara et al, 1995). However, in their review, Bearden et al (Reference Bearden, Hoffman and Cannon2001) suggest that the cognitive impairments in bipolar illness are unlikely to be a primary effect of medication. In a comparison study of euthymic patients with bipolar disorder and controls, neurocognitive impairment was observed not only in patients receiving mood-stabiliser monotherapy but also in those who were drug-free (Reference Goswami, Gulrajani and MooreGoswami et al, 2002). None the less, many patients with this disorder take several psychotropic medications at varying doses, and it is unknown what the effects of combined therapy might be, particularly over time. Similarly, although ECT may affect neurocognitive function in some patients, only half the patients in our study had ever received ECT and a negative effect of the number of previous treatments on performance was observed on a small number of tests.

Different rates of neurobiological abnormalities among patients with bipolar disorder may also affect the pattern and magnitude of neurocognitive impairment. Elevated cortisol levels have been shown to impair specific domains of neurocognitive functioning, both in studies in which synthetic glucocorticoids were administered exogenously and in patient groups with chronically elevated endogenous cortisol levels (e.g. Cushing's disease). As hypothalamic–pituitary–adrenal axis dysfunction in bipolar disorder may also persist in a proportion of euthymic patients (Reference Watson, Gallagher and RitchieWatson et al, 2004), in our study saliva samples were collected on the day prior to testing to provide a simple, non-invasive assessment of basal cortisol secretion. No difference between patients and controls was observed, potentially excluding this confound. However, basal cortisol profiling is relatively insensitive compared with ‘activating’ challenges such as the dexamethasone/corticotrophin releasing hormone test, which might be more informative in future studies (Reference Watson, Gallagher and RitchieWatson et al, 2004).

Several studies have reported that residual mood symptoms may affect the degree of neurocognitive dysfunction observed in euthymic patients with bipolar disorder (Reference Ferrier, Stanton and KellyFerrier et al, 1999; Reference Clark, Iversen and GoodwinClark et al, 2002). When residual mood symptoms were statistically controlled in our study, all between-group differences remained with the exception of one. As we recruited a larger cohort than in the earlier studies, residual symptoms may exert only subtle effects on performance and are less problematic when the statistical power of the study is increased. The observed impairment is therefore unlikely to be an epiphenomenon of mood.

Clinico-cognitive correlations: disease process or trait deficit?

Several studies have reported that patients with a more severe course of prior illness and greater number of episodes suffer greater neurocognitive decline (Reference KessingKessing, 1998; Reference van Gorp, Altshuler and Thebergevan Gorp et al, 1998; Reference Denicoff, Ali and MirskyDenicoff et al, 1999). In our study, examination of the correlation between illness history characteristics and neurocognitive functioning revealed an effect of several factors, particularly lifetime duration of illness and number of hospitalisations, consistent with several previous reports (Reference Tham, Engelbrektson and MatheTham et al, 1997; Reference Denicoff, Ali and MirskyDenicoff et al, 1999; Reference Rubinsztein, Michael and PaykelRubinsztein et al, 2000). Such associations have typically been interpreted as indicating a progressive disease process. However, the direction of causality cannot be determined from correlational analyses. These results may equally indicate that patients with neurocognitive impairments are more vulnerable to developing a severe and recurrent bipolar disorder. Preliminary evidence indicates subtle neurocognitive impairments in ‘high-risk’ groups, i.e. first-degree relatives of patients with bipolar disorder (Reference Keri, Kelemen and BenedekKeri et al, 2001; Reference Chowdhury, Thompson and WatsonChowdhury et al, 2002; Reference Sobczak, Riedel and BooijSobczak et al, 2002). Therefore, although some deficits might be the result of disease progression, evidence that impairments occur both in euthymic patients with bipolar disorder and their healthy first-degree relatives may represent an endophenotypic marker of genetic vulnerability.

Implications and future research

Neurocognitive deficits are evident in euthymic patients with bipolar disorder. These deficits are often a cause of considerable distress and can lead to impairment of psychosocial and occupational functioning (e.g. Reference Martinez-Aran, Vieta and ColomMartinez-Aran et al, 2004). Our study confirms that these deficits are of both statistical and clinical significance, and persist independently of mood symptoms. Early intervention may be particularly important in order to ameliorate such impairments, as several studies – including this one – indicate that the degree of dysfunction may increase with disease progression. One of the most important aims of future research should therefore be the identification of the underlying neurobiology of neurocognitive impairment in euthymic patients, thereby providing a target for therapeutic intervention. Cognitive and psychoeducational rehabilitation programmes may be warranted to improve the long-term outcome for some patients.

CLINICAL IMPLICATIONS

1. ▪ Patients with bipolar disorder are impaired across a range of neurocognitive domains. This is evident in terms of both statistical and clinical significance.

2. ▪ These deficits persist in the euthymic state and suggest that neurocognitive impairment persists long beyond the point of symptomatic recovery.

3. ▪ These deficits are not simply related to basal hypercortisolaemia.

LIMITATIONS

1. ▪ The patients in the study were stable on medication, but were not drug-free.

2. ▪ The study design was cross-sectional and the longitudinal course of these deficits remains to be fully demonstrated.

3. ▪ Basal cortisol levels do not fully characterise hypothalamic–pituitary–adrenal dysfunction.