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We evaluate for the first time the associations of brain white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) with neuropsychological variables among middle-aged bipolar I (BPI), II (BPII) and major depressive disorder (MDD) patients and controls using a path model.
Thirteen BPI, 15 BPII, 16 MDD patients, and 21 controls underwent brain MRI and a neuropsychological examination. Two experienced neuroradiologists evaluated WMHs on the MRI scans. We constructed structural equation models to test the strength of the associations between deep WMH (DWMH) grade, neuropsychological performance and diagnostic group.
Belonging in the BPI group as opposed to the control group predicted higher DWMH grade (coefficient estimate 1.13, P = 0.012). The DWMH grade independently predicted worse performance on the Visual Span Forward test (coefficient estimate −0.48, P = 0.002). Group effects of BPI and MDD were significant in predicting poorer performance on the Digit Symbol test (coefficient estimate −5.57, P = 0.016 and coefficient estimate −5.66, P = 0.034, respectively).
Because of the small number of study subjects in groups, the negative results must be considered with caution.
Only BPI patients had an increased risk for DWMHs. DWMHs were independently associated with deficits in visual attention.
To study, whether temperament and character remain stable over time and whether they differ between patients with and without personality disorder (PD) and between patients with specific PDs.
Patients with (n = 225) or without (n = 285) PD from Jorvi Bipolar Study, Vantaa Depression Study (VDS) and Vantaa Primary Care Depression Study were interviewed at baseline and at 18 months, and in the VDS also at 5 years. A general population comparison group (n = 264) was surveyed by mail.
Compared with non-PD patients, PD patients scored lower on self-directedness and cooperativeness. Cluster B and C PDs associated with high Novelty Seeking and Harm Avoidance, respectively. In logistic regression models, sensitivity and specificity of Temperament and Character Inventory (TCI) dimensions for presence of any PD were 53% and 75%, and for specific PDs from 11% to 41% and from 92% to 100%, respectively. The 18-month test-retest correlations of TCI-R dimensions ranged from 0.58 to 0.82.
Medium-term temporal stability of TCI in a clinical population appears good. Character scores differ markedly between PD and non-PD patients, whereas temperament scores differ only somewhat between the specific PDs. However, the TCI dimensions capture only a portion of the differences between PD and non-PD patients.
People with psychotic disorders have increased mortality compared to the general population. The mortality is mostly due to natural causes and it is disproportionately high compared to the somatic morbidity of people with psychotic disorders.
We aimed to find predictors of mortality in psychotic disorders and to evaluate the extent to which sociodemographic and health-related factors explain the excess mortality.
In a nationally representative sample of Finns aged 30–70 years (n = 5642), psychotic disorders were diagnosed in 2000–2001. Information on mortality and causes of death was obtained of those who died by the end of year 2013. Cox proportional hazards models were used to investigate the mortality risk.
Adjusting for age and sex, diagnosis of nonaffective psychotic disorder (NAP) (n = 106) was statistically significantly associated with all-cause mortality (HR 2.99, 95% CI 2.03–4.41) and natural-cause mortality (HR 2.81, 95% CI 1.85–4.28). After adjusting for sociodemographic factors, health status, inflammation and smoking, the HR dropped to 2.11 (95% CI 1.10–4.05) for all-cause and to 1.98 (95% CI 0.94–4.16) for natural-cause mortality. Within the NAP group, antipsychotic use at baseline was associated with reduced HR for natural-cause mortality (HR 0.25, 95% CI 0.07–0.96), and smoking with increased HR (HR 3.54, 95% CI 1.07–11.69).
The elevated mortality risk associated with NAP is only partly explained by socioeconomic factors, lifestyle, cardiometabolic comorbidities and inflammation. Smoking cessation should be prioritized in treatment of psychotic disorders. More research is needed on the quality of treatment of somatic conditions in people with psychotic disorders.
Disclosure of interest
Jaakko Keinänen owns shares in pharmaceutical company Orion.
Although suicidal behavior is very common in bipolar disorder (BD), few long-term studies have investigated incidence and risk factors of suicide attempts (SAs) specifically related to illness phases of BD.
We examined incidence of SAs during different phases of BD in a long-term prospective cohort of bipolar I (BD-I) and II (BD-II) patients and risk factors specifically for SAs during major depressive episodes (MDEs).
In the Jorvi bipolar study (JoBS), 191 BD-I and BD-II patients were followed using life-chart methodology. Prospective information on SAs of 177 patients (92.7%) during different illness phases was available up to five years. Incidence of SAs and their predictors were investigated using logistic and Poisson regression models. Analyses of risk factors for SAs occurring during MDEs were conducted using two-level random-intercept logistic regression models.
During the five-year follow-up, 90 SAs per 718 patient-years occurred. Compared with euthymia the incidence was highest, over 120-fold, during mixed states (765/1000 person-years [95% confidence interval (CI) 461–1269]) and also very high in MDEs, almost 60-fold (354/1000 [95%CI 277–451]). For risk of SAs during MDEs, the duration of MDEs, severity of depression and cluster C personality disorders were significant predictors.
In this long-term study, the highest incidences of SAs occurred in mixed phases and MDEs. The variations in incidence rates between euthymia and illness phases were remarkably large, suggesting that the question “when” rather than “who” may be more relevant for suicide risk in BD. However, risk during MDEs is likely also influenced by personality factors.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Anxiety disorders are highly prevalent in people with bipolar disorder, but it is not clear how many have anxiety disorders even at times when they are free of major mood episodes. We aimed to establish what proportion of euthymic individuals with bipolar disorder meet diagnostic criteria for anxiety disorders.
We performed a random-effects meta-analysis of prevalence rates of current DSM-III- and DSM-IV-defined anxiety disorders (panic disorder, agoraphobia, social anxiety disorder, generalized anxiety disorder, specific phobia, obsessive–compulsive disorder, post-traumatic stress disorder, and anxiety disorder not otherwise specified) in euthymic adults with bipolar disorder in studies published by 31 December 2015.
Across 10 samples with 2120 individuals with bipolar disorder, 34.7% met diagnostic criteria for one or more anxiety disorders during euthymia [95% confidence interval (CI) 23.9–45.5%]. Direct comparison of 189 euthymic individuals with bipolar disorder and 17 109 population controls across three studies showed a 4.6-fold increase (risk ratio 4.60, 95% CI 2.37–8.92, p < 0.001) in prevalence of anxiety disorders in those with bipolar disorder.
These findings suggest that anxiety disorders are common in people with bipolar disorder even when their mood is adequately controlled. Euthymic people with bipolar disorder should be routinely assessed for anxiety disorders and anxiety-focused treatment should be initiated if indicated.
Delusion is the most characteristic symptom of psychosis. While researchers suggested an association between changes of the cortical salience network (CSN) and delusion, whether these CSN findings are a cause or a consequence of delusion remains unknown.
To assess the effect of CSN functioning to forthcoming changes in delusion scores, we measured brain activation with 3-T functional magnetic resonance imaging in two independent samples of first-episode psychosis patients (total of 27 patients and 23 healthy controls). During scanning, the patients evaluated statements about whether an individual's psychosis-related experiences should be described as a mental illness, and control statements that were also evaluated by healthy controls. Symptoms were assessed at the baseline and at 2 months follow-up with Brief Psychiatric Rating Scale.
Both tasks activated the CSN in comparison with rest. Activation of CSN (‘illness evaluation v. control task’ contrast) in patients positively correlated with worsening of or less improvement in delusions at the 2-month follow-up assessment. This finding was independent of delusion and clinical insight scores at the baseline evaluation.
Our findings link symptom-evaluation-related CSN functioning to severity of delusion and, importantly, add a new layer of evidence for the contribution of CSN functioning to the longitudinal course of delusions.
We tested the degree to which longitudinal observations fit two hypotheses of psychiatric co-morbidity in DSM-IV major depressive disorder (MDD) among adult patients: (1) Axis I co-morbidity is dependent on major depressive episode (MDE) course, and (2) Axis I co-morbidity is independent of MDE course.
In the Vantaa Depression Study (VDS), 269 psychiatric secondary-care patients with a DSM-IV MDD were evaluated with the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) at intake and at 6 and 18 months. Three evaluations of co-morbidity were available for 193 out of 259 living patients (75%). A latent curve model (LCM) was used to examine individual-level changes in depressive and anxiety symptoms across time. Outcome of MDD was modeled in terms of categorical DSM-IV diagnosis and Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HAMD) scores, and co-morbidity in terms of categorical DSM-IV anxiety and alcohol use disorder (AUD) diagnoses and Beck Anxiety Inventory (BAI) scores.
Depression and anxiety correlated cross-sectionally at baseline. Longitudinally, changes in depression and anxiety correlated in both the 0–6 and 6–18 months time windows. Higher baseline depression raised the likelihood of an AUD at 6 months, and patients with more depressive symptoms in the 0–6 months time window were more likely to have had an AUD at 6 months, which further linked to less improvement in depression symptoms in the 6–18 months time window.
Longitudinal and individual-level courses of both internalizing and externalizing disorders in adult patients with MDD seem to be dependent, albeit to differing degrees, on the course of depressive symptoms.
Individual variation in the clinical course of bipolar disorder may have prognostic and therapeutic implications but is poorly reflected in current classifications. We aimed to establish a typology of the individual clinical trajectories based on detailed prospective medium-term follow-up.
Latent class analysis (LCA) of nine characteristics of clinical course (time depressed, severity of depression, stability of depression, time manic, severity of mania, stability of mania, mixed symptoms, mania-to-depression and depression-to-mania phase switching) derived from life charts prospectively tracking the onsets and offsets of (hypo)manic, depressive, mixed and subsyndromal episodes in a representative sample of 176 patients with bipolar disorder.
The best-fitting model separated patients with bipolar disorder into large classes of episodic bipolar (47%) and depressive type (32%), moderately sized classes characterized by prolonged hypomanias (10%) and mixed episodes (5%) and five small classes with unusual course characteristics including mania-to-depression and depression-to-mania transitions and chronic mixed affective symptoms. This empirical typology is relatively independent of the distinction between bipolar disorder type I and type II. Lifetime co-morbidity of alcohol use disorders is characteristic of the episodic bipolar course type.
There is potential for a new typology of clinical course based on medium-term naturalistic follow-up of a representative clinical sample of patients with bipolar disorder. Predictive validity and stability over longer follow-up periods remain to be established.
Whether temperament and character differ between bipolar disorder (BD) and major depressive disorder (MDD) patients and general population subjects, or between BD I and BD II patients, remains unclear.
BD patients (n=191) from the Jorvi Bipolar Study and MDD patients (n=266) from the Vantaa Depression Study (VDS) and the Vantaa Primary Care Depression Study were interviewed at baseline, at 6 and 18 months, and in the VDS at 5 years. A general population comparison group (n=264) was surveyed by mail. BD patients' scores on the Temperament and Character Inventory-Revised were compared at an index interview, when levels of depression and mania were lowest, with scores of MDD patients and controls. BD I (n=99) and BD II (n=92) patients were compared.
Compared with controls, both BD and MDD patients had higher harm avoidance [odds ratio (OR) 1.027, p<0.001 and OR 1.047, p<0.001, respectively] and lower persistence (OR 0.983, p=0.006 and OR 0.968, p<0.001, respectively) scores. Moreover, BD patients had lower self-directedness (OR 0.979, p=0.003), MDD patients lower reward dependence (OR 0.976, p=0.002) and self-transcendence (OR 0.966, p<0.001) scores. BD patients scored lower in harm avoidance (OR 0.980, p=0.002) and higher in novelty seeking (OR 1.027, p<0.001) and self-transcendence (OR 1.028, p<0.001) than MDD patients. No differences existed between BD I and II patients.
The patterns of temperament and character dimensions differed less between BD and MDD patients, than patients from their controls. The most pronounced difference was higher novelty seeking in BD than MDD patients. The dimensions investigated are unlikely to differ between BD I and BD II patients.
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