The Symptom Frequency Characteristics of the Hamilton Depression Rating Scale and Possible Symptom Clusters of Depressive Disorders in Korea: The CRESCEND Study

Toward practical machine-learning-based diagnosis for drug-naïve women with major depressive disorder using EEG channel reduction approach

BACKGROUND

A machine-learning-based computer-aided diagnosis (CAD) system can complement the traditional diagnostic error for major depressive disorder (MDD) using trait-like neurophysiological biomarkers. Previous studies have shown that the CAD system has the potential to differentiate between female MDD patients and healthy controls. The aim of this study was to develop a practically useful resting-state electroencephalography (EEG)-based CAD system to assist in the diagnosis of drug-naïve female MDD patients by considering both the drug and gender effects. In addition, the feasibility of the practical use of the resting-state EEG-based CAD system was evaluated using a channel reduction approach.

METHODS

Eyes-closed, resting-state EEG data were recorded from 49 drug-naïve female MDD patients and 49 sex-matched healthy controls. Six different EEG feature sets were extracted: power spectrum densities (PSDs), phase-locking values (PLVs), and network indices for both sensor- and source-level, and four different EEG channel montages (62, 30, 19, and 10-channels) were designed to investigate the channel reduction effects in terms of classification performance.

RESULTS

The classification performances for each feature set were evaluated using a support vector machine with leave-one-out cross-validation. The optimum classification performance was achieved when using sensor-level PLVs (accuracy: 83.67 % and area under curve: 0.92). Moreover, the classification performance was maintained until the number of EEG channels was reduced to 19 (over 80 % accuracy).

CONCLUSION

We demonstrated the promising potential of sensor-level PLVs as diagnostic features when developing a resting-state EEG-based CAD system for the diagnosis of drug-naïve female MDD patients and verified the feasibility of the practical use of the developed resting-state EEG-based CAD system using the channel reduction approach.

Latent structure of the symptomatology of hospitalized patients with bipolar mania

Several studies have attempted to understand the dimensions of psychiatric symptoms in manic episodes, but only a few have been able to model the latent structure of mania in bipolar disorder patients using confirmatory factor analysis. The objective of the present study was to search for the best model of the symptomatology of hospitalized manic patients. To achieve this goal, 117 manic inpatients during a manic crisis participated in this research. Exploratory factor analysis was conducted followed by confirmatory factor analysis using an exploratory factor analysis solution and three other theory-based models. The exploratory factor analysis results revealed a six-factor structure: depression, suicide, insomnia, mania, psychosis, and anxiety. This solution also presented the best fit to the data when tested with confirmatory factor analysis. A five-factor solution, without suicide as a separate dimension, appeared to be more theoretically suitable. Another important finding was that anxiety was an independent dimension in mania. Some hypotheses are discussed in light of contemporary theories, and future studies should investigate this aspect further.

Cross-Cultural Psychometric Properties of the Hamilton Depression Rating Scale

OBJECTIVE

The Hamilton Depression Rating Scale (HDRS) is considered the gold standard measure of depression. The factor structure of the HDRS is generally unstable, but 4 to 8 items appear to form a general depression factor. As transcultural studies of the HDRS have received little attention, and as most of the studies have taken a data-driven approach with a tendency to yield fragmented results, it is not clear if an HDRS general depression factor can also be found in non-Western populations. This is an important issue in deciding on the appropriateness of the scale as a gold standard in transcultural psychiatry.

METHOD

A systematic review was carried out to compare previously reported factor structures of the HDRS in non-Western cultures. Overlapping clusters across studies were identified and subsequently tested with confirmatory factor analysis (CFA) of responses from an independent sample.

RESULTS

Fourteen relevant studies were identified, 12 of which were obtained. A general depression factor was identified, consisting of the following symptoms: depressed mood, guilt, loss of interests, retardation, suicide, and psychological anxiety. The subsequent CFA analysis supported the fit of this model.

CONCLUSIONS

This study indicates that a general depression cluster is manifest in responses to the HDRS across cultures. While psychometric properties of the full-length HDRS are still debated, the general depression cluster appears pertinent to the assessment of depression across cultures. We recommend that cross-cultural clinicians and researchers focus on the use of unidimensional depression scales, which are in agreement with this cluster.

Distinctive Clinical Correlates of Psychotic Major Depression: The CRESCEND Study

OBJECTIVE

The purpose of this investigation was to identify distinctive clinical correlates of psychotic major depression (PMD) as compared with non-psychotic major depression (NPMD) in a large cohort of Korean patients with major depressive disorder (MDD).

METHODS

We recruited 966 MDD patients of age over 18 years from the Clinical Research Center for Depression of South Korea (CRESCEND) study. Diagnoses of PMD (n=24) and NPMD (n=942) were made with the DSM-IV definitions and confirmed with SCID. Psychometric scales were used to assess overall psychiatric symptoms (BPRS), depression (HAMD), anxiety (HAMA), global severity (CGI-S), suicidal ideation (SSI-Beck), functioning (SOFAS), and quality of life (WHOQOL-BREF). Using independent t-tests and χ(2) tests, we compared clinical characteristics of patients with PMD and NPMD. A binary logistic regression model was constructed to identify factors independently associated with increased likelihood of PMD.

RESULTS

PMD subjects were characterized by a higher rate of inpatient enrollment, and higher scores on many items on BPRS (somatic concern, anxiety, emotional withdrawal, guilt feelings, tension, depression, suspiciousness, hallucination, motor retardation, blunted affect and excitement) global severity (CGI-s), and suicidal ideation (SSI-Beck). The explanatory factor model revealed that high levels of tension, excitement, and suicidal ideation were associated with increased likelihood of PMD.

CONCLUSION

Our findings partly support the view that PMD has its own distinctive clinical manifestation and course, and may be considered a diagnostic entity separate from NPMD.

Prevalence and Clinical Correlates of Insomnia in Depressive Disorders: The CRESCEND Study

OBJECTIVE

To investigate the prevalence, clinical manifestations, and clinical correlates of insomnia in a large cohort of Korean patients with depressive disorders.

METHODS

We recruited 944 patients with depressive disorders from the Clinical Research Center for Depression of South Korea (CRESCEND) study. Psychometric scales were used to assess depression (HAMD), anxiety (HAMA), psychotic symptoms (BPRS), global severity (CGI-S), and functioning (SOFAS). Insomnia levels were determined by adding the scores for all items on the HAMD insomnia subscale. The clinical characteristics of the patients with 'low insomnia' (summed score ≤3 on the HAMD subscale) and 'high insomnia' (score ≥4) were compared using statistical analyses. A logistic regression model was constructed to identify factors associated with 'high insomnia' status.

RESULTS

Symptoms of insomnia were present in 93% of patients, while simultaneous early, middle, and late insomnia affected 64.1%. The high insomnia patients were characterized by significantly greater age, higher symptom levels (including core, gastrointestinal somatic and anxiety symptoms, and suicidal ideation), higher global severity and incidence of physical disorders, and greater insight. Explanatory factors of 'high insomnia' status were older age, higher gastrointestinal somatic and anxiety symptom levels, higher global severity, and greater insight.

CONCLUSION

In clinical psychiatry, insomnia has been significantly underdiagnosed and undertreated. It affects most patients with depressive disorders, and is indicative of the global severity of depression. Active efforts to diagnose and treat insomnia in patients with depressive disorders should be strongly encouraged. Further research is needed to improve the diagnosis and treatment of insomnia in depressive patients.