Clinical Validation of the Psychotic Depression Assessment Scale, Hamilton Depression Rating Scale-6, and Brief Psychiatric Rating Scale-5: Results from the Clinical Research Center for Depression Study

A Machine-Learning-Algorithm-Based Prediction Model for Psychotic Symptoms in Patients with Depressive Disorder

Psychotic symptoms are rarely concurrent with the clinical manifestations of depression. Additionally, whether psychotic major depression is a subtype of major depression or a clinical syndrome distinct from non-psychotic major depression remains controversial. Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, we developed a machine-learning-algorithm-based prediction model for concurrent psychotic symptoms in patients with depressive disorders. The advantages of machine learning algorithms include the easy identification of trends and patterns, handling of multi-dimensional and multi-faceted data, and wide application. Among 1171 patients with depressive disorders, those with psychotic symptoms were characterized by significantly higher rates of depressed mood, loss of interest and enjoyment, reduced energy and diminished activity, reduced self-esteem and self-confidence, ideas of guilt and unworthiness, psychomotor agitation or retardation, disturbed sleep, diminished appetite, and greater proportions of moderate and severe degrees of depression compared to patients without psychotic symptoms. The area under the curve was 0.823. The overall accuracy was 0.931 (95% confidence interval: 0.897-0.956). Severe depression (degree of depression) was the most important variable in the prediction model, followed by diminished appetite, subthreshold (degree of depression), ideas or acts of self-harm or suicide, outpatient status, age, psychomotor retardation or agitation, and others. In conclusion, the machine-learning-based model predicted concurrent psychotic symptoms in patients with major depression in connection with the "severity psychosis" hypothesis.

Decreased Alpha Reactivity from Eyes-Closed to Eyes-Open in Non-Demented Older Adults with Alzheimer’s Disease: A Combined EEG and [18F]florbetaben PET Study

Background: The degree of alpha attenuation from eyes-closed (EC) to eyes-open (EO) has been suggested as a neural marker of cognitive health, and its disruption has been reported in patients with clinically defined Alzheimer’s disease (AD) dementia. Objective: We tested if EC-to-EO alpha reactivity was related to cerebral amyloid-β (Aβ) deposition during the early stage of AD. Methods: Non-demented participants aged ≥55 years who visited the memory clinic between March 2018 and June 2019 (N = 143; 67.8% female; mean age±standard deviation, 74.0±7.6 years) were included in the analyses. Based on the [18F]florbetaben positron emission tomography assessment, the participants were divided into Aβ+ (N = 70) and Aβ- (N = 73) groups. EEG was recorded during the 7 min EC condition followed by a 3 min EO phase, and a Fourier transform spectral analysis was performed. Results: A significant three-way interaction was detected among Aβ positivity, eye condition, and the laterality factor on alpha-band power after adjusting for age, sex, educational years, global cognition, depression, medication use, and white matter hyperintensities on magnetic resonance imaging (F = 5.987, p = 0.016); EC-to-EO alpha reactivity in the left hemisphere was significantly reduced in Aβ+ subjects without dementia compared with the others (F = 3.984, p = 0.048). Conclusion: Among mild cognitive impairment subjects, alpha reactivity additively contributed to predict cerebral Aβ positivity beyond the clinical predictors, including vascular risks, impaired memory function, and apolipoprotein E ɛ4. These findings support that EC-to-EO alpha reactivity acts as an early biomarker of cerebral Aβ deposition and is a useful measurement for screening early-stage AD.

Psychotic depression in hospitalized patients: Longitudinal outcomes of psychotic vs. nonpsychotic depression among inpatients

Even though psychotic depression is related to worse outcomes than nonpsychotic depression, there is increasing evidence that this greater severity is not solely explained by the depressive symptoms. We evaluated the socio-demographic and clinical characteristics, as well as the differences in clinical outcomes of psychiatric hospitalization between psychotic and non-psychotic depression. Two-hundred-eighty-eight depressive inpatients were assessed within 72 h after hospitalization and 24 h before discharge. We compared scores of Hamilton Depression Rating Scale 17-items (HDRS-17), Clinical Global Impression (CGI), Brief Psychiatric Rating Scale (BPRS), and Global Assessment of Functioning (GAF) between psychotic and nonpsychotic patients. Instruments were compared both cross-sectionally - on admission and discharge - and longitudinally. Longitudinal outcomes were corrected for potential confounders (sex, age, age at disease onset, years of study, previous history of mania/hypomania, electroconvulsive therapy in current hospitalization, history of attempted suicide, number of suicide attempts, and previous hospitalizations). One-hundred-thirty-one depressive inpatients (45.4%) presented psychotic features. Both groups showed similar HDRS-17 scores at admission and discharge. However, psychotic patients had worse scores on BPRS, CGI, and GAF at both timepoints. Both groups had similar improvement on HDRS-17 (P = 0.75), CGI (P = 0.5), and GAF (P = 0.84), but psychotic patients had greater improvement on BPRS (P < 0.001). Psychotic inpatients showed worse clinical and functional parameters. Nonetheless, the groups did not differ in depressive symptom severity. These findings reinforce the hypothesis that depressive episode with psychotic features is a more severe form of the disease irrespective of intensity of affective symptomatology.

Diagnostic Issues of Depressive Disorders from Kraepelinian Dualism to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Because the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) was mainly influenced by the neo-Kraepelinian approach, its categorical approach to defining mental disorders has been criticized from the viewpoint of etiological neutrality. In the context of bridging the gap between "presumed etiologies-based symptomatology" and "identifiable pathophysiological etiologies," the content in 5th edition, the DSM-5, has been revised to incorporate a combination of categorical and dimensional approaches. The most remarkable change of note regarding the diagnostic classification of depressive disorders in the DSM-5 is the splitting of mood disorders into bipolar disorders and depressive disorders, which is in accordance with the deconstruction of the Kraepelinian dualism for psychoses. The transdiagnostic specifiers "with mixed features," "with psychotic features," and "with anxious distress" are introduced to describe the relationships of depressive disorders with bipolar disorders, schizophrenia, and generalized anxiety disorder, respectively, in a dimensional manner. The lowering of the diagnostic threshold for major depressive disorder (MDD) may be caused by the addition of "hopelessness" to the subjective descriptors of depressive mood and the elimination of "bereavement exclusion" from the definition of MDD. Since the heterogeneity of MDD is equivalent to the Wittgensteinian "games" analogy, the different types of MDD are related not by a single essential feature but rather by "family resemblance." Network analyses of MDD symptoms may therefore need further review to elucidate the connections among interrelated symptoms and other clinical elements.

Process Evaluation of a Pilot Intervention for Psychosocial Rehabilitation for Service Users with Schizophrenia in North West Province, South Africa

This study investigated a non-specialist delivered programme for psychosocial rehabilitation for service users with schizophrenia in a low-resource South African setting. Forty-four service users with schizophrenia living in the community, receiving ongoing medication through primary care, participated in a structured support group. Quantitative measures (WHODAS 12 item, Brief Psychiatric Rating Scale and Internalized Stigma of Mental Illness Inventory) were assessed at baseline and 12 months. Sixteen service users were interviewed on their experiences. WHODAS data showed a small reduction. ISMI assessment showed a statistically significant reduction. Qualitative data revealed: improved self-esteem and increased illness knowledge, reduced risk taking, reduced social isolation and improved pro-social behavior, improved financial management and engagement in income generation activities as well as improved acceptance by the community. This study provides preliminary evidence on the benefits of this programme that warrant further study incorporating experimental methods.