UNASSIGNED: Depressive disorder is common among haemodialysis patients. The purpose of this study was to explore approaches to diagnosing depression in the context of a real-life setting, with the view of creating practical recommendations. It also aimed to evaluate the prevalence of depression and dementia.
UNASSIGNED: We conducted a cross-sectional study in two Dialysis Centres in Poland. Cognitive functions were evaluated using Mini-Mental State Examination (MMSE). The screening for depressive symptoms was assessed using Beck Depression Inventory II (BDI-II). The diagnosis of major depressive disorder was confirmed by a psychiatrist using Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5). Sociodemographic and clinical data were also collected.
UNASSIGNED: Initially, 136 patients agreed to participate in the study. Dementia was found in 13% of the study group. Sixty-two patients did not agree to perform all the proposed tests and were not included in the analysis, which eventually consisted of 70 patients. According to BDI-II, depressive symptoms were present in 35.7% of patients, while the diagnosis of major depressive disorder (MDD) was confirmed by the psychiatrist in 25.7%. According to the ROC analysis the optimal cut-off score for diagnosing MDD using BDI-II was ≥13 points.
UNASSIGNED: This study suggests that the regular screening for depressive symptoms, followed by a psychiatric consultation in selected patients, might improve diagnosing depression with the goal of achieving a higher quality of life and a lower mortality rate. It may also be a cost-effective model for the management of depression among the haemodialysis population.

Clinical drug development in psychiatry is challenging due to heterogeneous patient populations and the uncertainty of measuring neuropsychiatric constructs with symptom rating scales. Here we describe the development and implementation of an enrichment algorithm that identifies canonical versus anomalous symptom presentations, at the individual subject level, based on MADRS ratings obtained at screening and baseline. Data from 5 randomized, placebo-controlled, phase 3 trials in bipolar I disorder was used (N = 2026 subjects and 15,239 MADRS assessments). A variance-covariance difference (VCD) vector was developed to encode individual symptom structure using the 10 items of MADRS from the two sequential assessments. An anomaly score, calculated from each subject\'s VCD vector was derived by isolation forest to quantify the degree of disparity from the hypothesized canonical item structure. A retrospective application of the algorithm reliably identified a threshold anomaly score above which the psychometric properties of MADRS deteriorate. Consistent with increasing the certainty of MADRS ratings, subjects with a canonical symptom structure at baseline demonstrated greater effect sizes post-baseline in a phase 2 placebo-controlled trial of non-racemic amisulpride (SEP-4199) for bipolar depression, analyzed retrospectively. Our analyses show that the developed algorithm can reduce the symptom structure heterogeneity at baseline and thus improve the measurement certainty of psychiatric symptoms in clinical trials. This novel enrichment method has been prospectively implemented in a Phase 3 clinical study of SEP-4199 and is consistent with regulatory guidelines aimed at increasing the statistical power and lowering patient-burden in clinical trials. Clinical Trials Registry: NCT00868452, NCT00868699, NCT01284517, NCT01986101, NCT03543410, NCT05169710.

BACKGROUND: It is previously reported that the Montgomery-Åsberg Depression Rating Scale (MADRS) anhedonia factor score is correlated with scales assessing function in patients with major depressive disorder (MDD).
METHODS: This was an analysis of a database including 5 long-term, extension studies of prior controlled trials, which evaluated the effects of open-label, maintenance treatment with vortioxetine (5-20 mg/day over 1-year) in adults with MDD. We assessed the association of changes in MADRS anhedonia factor scores with changes in the Clinical Global Impression of Severity (CGI-S), Sheehan Disability scale (SDS), and the SF-36. A minimal clinically important change (MCIC) for MADRS anhedonia factor scores was determined using the CGI-S as anchor.
RESULTS: In patients who had completed the prior controlled studies, MADRS anhedonia factor scores continued to improve over 1-year of maintenance treatment (mean ± SE change from baseline of -6.2 ± 0.2 at Month 12). Change in MADRS anhedonia factors score correlated with change in CGI-S (Week 4, r = 0.71), SDS (Week 24 r = 0.60) and SF-36 domains (Week 24 r = -0.19 to -0.61) scores. Using a 1 level improvement on CGI-S as anchor, the MCIC for MADRS anhedonia factor scores versus baseline were - 4.6 at Week 4, -5.5 at Week 24, and - 5.3 at Week 52.
CONCLUSIONS: Neither the MADRS scale, nor the primary studies, were specifically designed to assess anhedonia.
CONCLUSIONS: These open-label data suggest that patients treated with vortioxetine continued to show clinically relevant improvements in their anhedonia over 1-year of maintenance therapy. Improvements in anhedonia correlated with improvements in measures of functioning and quality of life.

BACKGROUND: The Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) are commonly used scales to measure depression severity in older adults.
METHODS: We utilized data from the Optimizing Outcomes of Treatment-Resistant Depression in Older Adults (OPTIMUM) clinical trial to produce conversion tables relating PHQ-9 and MADRS total scores. We split the sample into training (N = 555) and validation samples (N = 187). Equipercentile linking was performed on the training sample to produce conversion tables for PHQ-9 and MADRS. We compared the original and estimated scores in the validation sample with Bland-Altman analysis. We compared the depression severity level using the original and estimated scores with Chi-square tests.
RESULTS: The Bland-Altman analysis confirmed that differences between the original and estimated scores for at least 95 % of the sample fit within 1.96 standard deviations of the mean difference. Chi-square tests showed a significant difference in the proportion of participants at each depression severity category determined using the original and estimated scores.
CONCLUSIONS: The conversion tables should be used with caution when comparing depression severity at the individual level.
CONCLUSIONS: Our conversion tables relating PHQ-9 and MADRS scores can be used to compare treatment outcomes using aggregate data in studies that only used one of these scales.

OBJECTIVE: Depressive disorder is often evaluated using established rating scales. However, consistent data collection with these scales requires trained professionals. In the present study, the \"rater & estimation-system\" reliability was assessed between consensus evaluation by trained psychiatrists and the estimation by 2 models of the AI-MADRS (Montgomery-Asberg Depression Rating Scale) estimation system, a machine learning algorithm-based model developed to assess the severity of depression.
METHODS: During interviews with trained psychiatrists and the AI-MADRS estimation system, patients responded orally to machine-generated voice prompts from the AI-MADRS structured interview questions. The severity scores estimated from two models of the AI-MADRS estimation system, the max estimation model and the average estimation model, were compared with those by trained psychiatrists.
RESULTS: A total of 51 evaluation interviews conducted on 30 patients were analyzed. Pearson\'s correlation coefficient with the scores evaluated by trained psychiatrists was 0.76 (95% confidence interval 0.62-0.86) for the max estimation model, and 0.86 (0.76-0.92) for the average estimation model. The ANOVA ICC rater & estimation-system reliability with the evaluation scores by trained psychiatrists was 0.51 (-0.09 to 0.79) for the max estimation model, and 0.75 (0.55-0.86) for the average estimation model.
CONCLUSIONS: The average estimation model of AI-MADRS demonstrated substantially acceptable rater & estimation-system reliability with trained psychiatrists. Accumulating a broader training dataset and the refinement of AI-MADRS interviews are expected to improve the performance of AI-MADRS. Our findings suggest that AI technologies can significantly modernize and potentially revolutionize the realm of depression assessments.

Post-stroke depression affects about 30% of stroke patients and often hampers functional recovery. The diagnosis of depression encompasses heterogeneous symptoms at emotional, motivational, cognitive, behavioural or somatic levels. Evidence indicates that depression is caused by disruption of bio-aminergic fibre tracts between prefrontal and limbic or striatal brain regions comprising different functional networks. Voxel-based lesion-symptom mapping studies reported discrepant findings regarding the association between infarct locations and depression. Inconsistencies may be due to the usage of sum scores, thereby mixing different symptoms of depression. In this cross-sectional study, we used multivariate support vector regression for lesion-symptom mapping to identify regions significantly involved in distinct depressive symptom domains and global depression. MRI lesion data were included from 200 patients with acute first-ever ischaemic stroke (mean 0.9 ± 1.5 days of post-stroke). The Montgomery-Åsberg Depression Rating interview assessed depression severity in five symptom domains encompassing motivational, emotional and cognitive symptoms deficits, anxiety and somatic symptoms and was examined 8.4 days of post-stroke (±4.3). We found that global depression severity, irrespective of individual symptom domains, was primarily linked to right hemispheric lesions in the dorsolateral prefrontal cortex and inferior frontal gyrus. In contrast, when considering distinct symptom domains individually, the analyses yielded much more sensitive results in regions where the correlations with the global depression score yielded no effects. Accordingly, motivational deficits were associated with lesions in orbitofrontal cortex, dorsolateral prefrontal cortex, pre- and post-central gyri and basal ganglia, including putamen and pallidum. Lesions affecting the dorsal thalamus, anterior insula and somatosensory cortex were significantly associated with emotional symptoms such as sadness. Damage to the dorsolateral prefrontal cortex was associated with concentration deficits, cognitive symptoms of guilt and self-reproach. Furthermore, somatic symptoms, including loss of appetite and sleep disturbances, were linked to the insula, parietal operculum and amygdala lesions. Likewise, anxiety was associated with lesions impacting the central operculum, insula and inferior frontal gyrus. Interestingly, symptoms of anxiety were exclusively left hemispheric, whereas the lesion-symptom associations of the other domains were lateralized to the right hemisphere. In conclusion, this large-scale study shows that in acute stroke patients, differential post-stroke depression symptom domains are associated with specific structural correlates. Our findings extend existing concepts on the neural underpinnings of depressive symptoms, indicating that differential lesion patterns lead to distinct depressive symptoms in the first weeks of post-stroke. These findings may facilitate the development of personalized treatments to improve post-stroke rehabilitation.

Quantifying depression mainly relies on the use of depression scales, and understanding their factor structure is crucial for evaluating their validity.
This post-hoc analysis utilized prospectively collected data from a naturalistic study of 1014 inpatients with major depression. Confirmatory and exploratory factor analyses were performed to test the psychometric abilities of the Hamilton Depression Rating Scale, the Montgomery Asberg Depression Rating Scale, and the self-rated Beck Depression Inventory. A combined factor analysis was also conducted including all items of all scales.
All three scales showed good to very good internal consistency. The HAMD-17 had four factors: an \"anxiety\" factor, a \"depression\" factor, an \"insomnia\" factor, and a \"somatic\" factor. The MADRS also had four factors: a \"sadness\" factor, a neurovegetative factor, a \"detachment\" factor and a \"negative thoughts\" factor, while the BDI had three factors: a \"negative attitude towards self\" factor, a \"performance impairment\" factor, and a \"somatic\" factor. The combined factor analysis suggested that self-ratings might reflect a distinct illness dimension within major depression.
The factors obtained in this study are comparable to those found in previous research. Self and clinician ratings are complementary and not redundant, highlighting the importance of using multiple measures to quantify depression.

Numerous studies have demonstrated that low-dose subanesthetic intravenous ketamine infusion treatment leads to rapid improvement of treatment-resistant depression. The following case report describes the use of a very low-dose subcutaneous ketamine as a form of maintenance in a patient with severe treatment-resistant depression using a retrospective chart review.

Derive and confirm factor structure of the Montgomery-Åsberg Depression Rating Scale (MADRS) in patients with treatment-resistant depression (TRD) and evaluate how the factors evident at baseline change over 4 weeks of esketamine treatment.
Two similarly-designed, short-term TRANSFORM trials randomized adults to esketamine or matching placebo nasal spray, each with a newly-initiated oral antidepressant, for 4 weeks (TRANSFORM-1: N = 342 patients; TRANSFORM-2: N = 223 patients). The factor structure of MADRS item scores at baseline was determined by exploratory factor analysis in TRANSFORM-2 and corroborated by confirmatory factor analysis in TRANSFORM-1. Change in MADRS factor scores from baseline (day 1) to the end of the 28-day double-blind treatment phase of TRANSFORM-2 was analyzed using a mixed-effects model for repeated measures (MMRM).
Three factors were identified based on analysis of MADRS items: Factor 1 labeled affective and anhedonic symptoms (apparent sadness, reported sadness, lassitude, inability to feel), Factor 2 labeled anxiety and vegetative symptoms (inner tension, reduced sleep, reduced appetite, concentration difficulties), and Factor 3 labeled hopelessness (pessimistic thoughts, suicidal thoughts). The three-factor structure observed in TRANSFORM-2 was verified in TRANSFORM-1. Treatment benefit at 24 h with esketamine versus placebo was observed on all 3 factors and continued throughout the 4-week double-blind treatment period.
A three-factor structure for MADRS appears to generalize to TRD. All three factors improved over 4 weeks of treatment with esketamine nasal spray.

Major depressive disorder (MDD) is characterized by a high rate of treatment resistance. Omega (ω)-3 polyunsaturated fatty acids (PUFAs) were shown to correlate with depressive phenotype both in rodents and in humans. However, few studies to date have investigated the role of PUFAs in antidepressant response. The primary aim of this study was to assess the link between baseline PUFA composition and changes in depressive symptoms as well as antidepressant response in a multicenter study of depressed patients.
Sixty depressed adults who met criteria for MDD according to DSM-IV-TR were recruited. Neuropsychiatric evaluations occurred at baseline and after 4 and 8 weeks of treatment with standard antidepressants, including escitalopram (N = 45), sertraline (N = 13) and venlafaxine (N = 2). At study endpoint, patients were stratified into responders (R) or non-responders (NR) based on their MADRS (Montgomery-Åsberg Depression Rating Scale) score. Baseline PUFA levels were assessed and their association with clinical response was determined.
Lower ω-3 PUFA levels were associated to worse baseline symptomatology. Baseline levels of PUFAs were significantly different between R and NR, with R exhibiting lower docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and ω-3 index; and higher ω-6/ω-3 ratio than NR before the start of antidepressant treatment. DHA levels as well as the ω-3 index and ω-6/ω-3 ratio significantly predicted response to antidepressants at study endpoint.
These results show that baseline levels of PUFAs predict later response to standard antidepressants in depressed subjects. They suggest that PUFA intake and/or metabolism represent a novel modifiable tool for the management of unresponsive depressed patients.