Is it depression or is it bipolar depression?

Improving hemodialysis patient depression outcomes with acupuncture: A randomized controlled trial

OBJECTIVE

To evaluate the efficacy and safety of acupuncture as a supplementary treatment for mild to moderate depression in hemodialysis patients.

METHOD

This multicenter, randomized, controlled, single-masked trial included 64 hemodialysis patients aged 18-75 divided into two groups. One group received genuine acupuncture, while the other received sham acupuncture over 12 weeks. The primary outcome measure was Hamilton Depression Scale (HAMD) scores; an inclusion criterion was HAMD scores of 10-23. Secondary outcomes included life quality improvements and changes in biochemical markers, such as serum albumin and hemoglobin levels. To assess the predictive effects of acupuncture treatment and biochemical parameters on depressive symptoms, a multivariable linear regression analysis was conducted.

RESULTS

Following acupuncture treatment, HAMD scores significantly decreased, quality of life scores improved, and biochemical indicators (serum albumin, hemoglobin, transferrin, and total protein levels) showed some improvement, indicating the effectiveness of acupuncture in alleviating depressive symptoms and enhancing overall health in hemodialysis patients. Multivariable regression analysis showed that acupuncture treatment (P = 0.004) and serum albumin levels (P = 0.03) were significant predictors of improvement in depressive symptoms, with an adjusted R2 of 0.45, indicating that the model explained 45 % of the variance in symptom improvement. Other biochemical indicators, such as hemoglobin, transferrin, and total protein, did not show significant predictive effects (P > 0.05). No serious adverse events were observed during the treatment.

CONCLUSION

Acupuncture is a safe and effective adjunct therapy for alleviating mild to moderate depression in hemodialysis patients. Acupuncture treatment and certain biochemical indicators (such as serum albumin) have significant predictive value for improving depressive symptoms.

The differences in testosterone and stress hormones between unipolar and bipolar depression in adolescents and adults

BACKGROUND

While patients with major depressive disorder (MDD) and bipolar disorder (BD) often exhibit aberrant hormones, it is still unknown whether the hormones differ between MDD and BD across the age spectrum. We aimed to investigate the differences in testosterone and stress hormones between depressed patients with MDD and BD in adolescents and adults, and the impact of suicidal ideation on these.

METHODS

A total of 432 depressed patients (270 MDD and 162 BD) were recruited, including 177 adolescents and 255 adults. Plasma levels of adrenocorticotropic hormone (ACTH), cortisol (CORT), testosterone (T), and prolactin (PRL) were measured in all patients. Suicidal ideation was assessed by item 3 of the Hamilton Depression Rating Scale.

RESULTS

In adolescents, plasma T levels were higher in MDD than in BD (p=0.018), MDD patients with suicidal ideation exhibited higher T levels than BD patients with suicidal ideation (p=0.036), and plasma T levels were associated with diagnosis (ORadjus=0.777, p=0.023). In adults, plasma ACTH levels were elevated in MDD versus BD (p=0.012) and were also diagnosis-related (ORadjus=0.972, p=0.019). Plasma levels of other hormones were not significantly different between MDD and BD in adolescents or adults (all p>0.05).

CONCLUSIONS

There was an age-specific difference in the T and ACTH between depressed patients with MDD and BD. Suicidal ideation was linked to T in adolescents.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

Resting-State Electroencephalogram Depression Diagnosis Based on Traditional Machine Learning and Deep Learning: A Comparative Analysis

The global prevalence of Major Depressive Disorder (MDD) is increasing at an alarming rate, underscoring the urgent need for timely and accurate diagnoses to facilitate effective interventions and treatments. Electroencephalography remains a widely used neuroimaging technique in psychiatry, due to its non-invasive nature and cost-effectiveness. With the rise of computational psychiatry, the integration of EEG with artificial intelligence has yielded remarkable results in diagnosing depression. This review offers a comparative analysis of two predominant methodologies in research: traditional machine learning and deep learning methods. Furthermore, this review addresses key challenges in current research and suggests potential solutions. These insights aim to enhance diagnostic accuracy for depression and also foster further development in the area of computational psychiatry.

[Anton Bruckner: the Linz cathedral organist, university teacher, symphonic musician : Could modern intensive care medicine have helped him and his illnesses?]

BACKGROUND

Anton Bruckner was a famous cathedral organist, university teacher, and symphonic composer, but his life, illnesses, death and dying are little or not known to many.

OBJECTIVES

Which illnesses determined Bruckner's life and did lifestyle and illnesses influence his compositional work? From today's perspective, could modern intensive care medicine have helped him?

MATERIALS AND METHODS

A detailed analysis of Bruckner's diseases was carried out using the scientific databases PubMed® and MEDLINE®. All published articles were evaluated and examined in detail. In addition, data from a concert tour of the author to Linz and the St. Florian Abbey Basilica were collected.

RESULTS

Anton Bruckner was born on 4 September 1824 in Ansfelden, Austria. As a child he received piano and organ lessons. After his father's death, he devoted himself to playing the organ and became in 1855 cathedral organist in Linz. His further career took him to Vienna, where he became a professor at the conservatory and turned to composition. His symphonies, his masses, and his Te Deum are his most famous works. During the first 40 years of his life, Bruckner suffered from psychopathological illnesses, including depression, delusions of persecution, and neuroses. Later, he suffered from chronic heart failure with recurrent right and left heart decompensation up to the development of cardiac cachexia, possibly caused by dilated cardiomyopathy due to alcohol toxicity. He died on 11 October 1896 in Vienna.

CONCLUSION

Bruckners life was marked by a wide variety of illnesses. His penchant for death and the dead was also striking. Modern medicine would probably have improved his quality of life through consequent heart failure therapy; an implantable automatic defibrillator with resynchronization therapy would probably have prolonged his life.

Serum Levels of Zinc, Albumin, Interleukin-6 and CRP in Patients with Unipolar and Bipolar Depression: Cross Sectional Study

Unipolar (UD) and bipolar depression (BDD) show a high degree of similarity in clinical presentations, which complicates the differential diagnosis of these disorders. The aim of this study was to investigate the serum levels of interleukin 6 (IL-6), C-reactive protein (CRP), albumin (Alb), and zinc (Zn) in patients with UD, BDD, and healthy controls (HC). A total of 211 samples were collected: 131 patient samples (65 UD and 68 BDD) and 80 HC. The Montgomery-Asberg Depression Rating Scale (MADRS), along with the Hamilton Depression Rating Scale (HAMD-17), were administered to patient groups to evaluate symptoms. A cross-sectional study was performed to analyse the serum levels of IL-6, CRP, albumin, and zinc. The concentration of CRP was determined using the immunoturbidimetry method, zinc using the colorimetric method, and albumin using the colorimetric method with bromocresol green on the Alinity c device. IL-6 cytokine concentration in serum samples was ascertained using a commercial enzyme immunoassay, ELISA. We found no significant differences in serum concentrations of zinc, albumin, CRP, and IL-6 between the groups of patients with unipolar and bipolar depression. There was a significant statistical difference (p < 0.001) between serum levels of all investigated parameters in both groups of depressed patients in comparison with HC. Furthermore, correlations with specific items on HAMD-17; (namely, hypochondrias, work and activities, somatic symptoms-general, and weight loss) and on MADRS (concentration difficulties, lassitude) were observed in both patient groups. These findings confirm the presence of low-grade inflammation in depression, thus adding better insight into the inflammation hypothesis directed to explain the aetiology of depressive disorders. Our results do not indicate potential biomarkers for distinguishing between unipolar and bipolar depression.

Longitudinal associations between psychedelic use and psychotic symptoms in the United States and the United Kingdom

It has long been speculated that psychedelic use could provoke the onset of psychosis, but there is little evidence to support this conjecture. Using a longitudinal research design with samples representative of the US and UK adult populations with regard to sex, age, and ethnicity (n = 9732), we investigated associations between psychedelic use and change in the number of psychotic symptoms during the two-month study period. In covariate-adjusted regression models, psychedelic use during the study period was not associated with a change in the number of psychotic symptoms unless it interacted with a personal or family history of bipolar disorder, in which case the number of symptoms increased, or with a personal (but not family) history of psychotic disorders, in which case the number of symptoms decreased. Taken together, these findings indicate that psychedelic use may affect psychotic symptoms in individuals with a personal or family history of certain disorders characterized by psychotic symptomatology.

Systemic inflammation and oxidative stress markers in patients with unipolar and bipolar depression: A large-scale study

OBJECTIVE

Numerous studies have demonstrated that neutrophil/HDL ratio (NHR), lymphocyte/HDL ratio (LHR), monocyte/HDL (MHR) ratio, platelet/HDL ratio (PHR), neutrophil/ALB ratio (NAR) and platelet/ALB ratio (PAR) can serve as systemic inflammation and oxidative stress markers in a variety of diseases. However, few studies have estimated the associations of these markers with unipolar depression (UD) and bipolar depression (BD), as well as psychotic symptoms in UD and BD.

METHODS

6297 UD patients, 1828 BD patients and 7630 healthy subjects were recruited. The differences in these indicators among different groups were compared, and the influencing factors for the occurrence of UD or BD and psychotic symptoms were analyzed.

RESULTS

These ratios displayed unique variation patterns across different diagnostic groups. BD group exhibited higher NHR, LHR, MHR, NAR and lower PAR than UD and HC groups, UD group showed higher MHR than HC group. The psychotic UD group had higher NHR, LHR, MHR and NAR than non-psychotic UD group. Higher LHR, MHR, NAR and lower PAR were risk factors in BD when compared to UD group.

CONCLUSIONS

Our study demonstrated differences in inflammation and oxidative stress profile between UD and BD patients, as well as between subjects with or without psychotic symptom exist, highlighting the role of inflammation and oxidative stress in the pathophysiology of UD and BD.

Identification of shared disease marker genes and underlying mechanisms between major depression and rheumatoid arthritis

Both depression and rheumatoid arthritis (RA) have a very high comorbidity rate. A bilateral association is estimated to increase the mutual risk and the common denominator is inflammation being observed in both diseases. Previous studies have mainly focused on assessing peripheral blood's inflammatory and pro-inflammatory cytokines levels. We aimed to extend insights into the molecular mechanisms of depression based on hub RA genes. To do so, we prioritized RA-related genes using in-silico tools. We then investigated whether RA-related genes undergo altered expression in patients with unipolar and bipolar depression without a concurrent RA diagnosis and any exponents of active inflammation. In addition, we selected a homogeneous group of patients treated with lithium (Li), which has immunomodulatory properties. The study was performed on patients with bipolar depression (BD, n = 45; Li, n = 20), unipolar depression (UD, n = 27), and healthy controls (HC, n = 22) of both sexes. To identify DEGs in peripheral blood mononuclear cells (PBMCs), we used the SurePrint G3 Microarray and GeneSpring software. We selected a list of 180 hub genes whose altered expression we analyzed using the expression microarray results. In the entire study group, we identified altered expression of 93 of the 180 genes, including 35 down-regulated (OPRM1 gene with highest FC > 3) and 58 up-regulated (TLR4 gene with highest FC > 3). In UD patients, we observed maximally up-regulated expression of the TEK gene (FC > 3), and in BD of the CXCL8 gene (FC > 5). On the other hand, in lithium-treated patients, the gene with the most reduced expression was the TRPV1 gene. The study proved that depression and RA are produced by a partially shared "inflammatory interactome" in which the opioid and angiogenesis pathways are important.

Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management

Introduction

Digital health technologies (DHTs) driven by artificial intelligence applications, particularly those including predictive models derived with machine learning methods, have garnered substantial attention and financial investment in recent years. Yet, there is little evidence of widespread adoption and scant proof of gains in patient health outcomes. One factor of this paradox is the disconnect between DHT developers and digital health ecosystem stakeholders, which can result in developing technologies that are highly sophisticated but clinically irrelevant. Here, we aimed to uncover challenges faced by psychiatrists treating patients with major depressive disorder (MDD). Specifically, we focused on challenges psychiatrists raised about bipolar disorder (BD) misdiagnosis.

Methods

We conducted semi-structured interviews with 10 United States-based psychiatrists. We applied text and thematic analysis to the resulting interview transcripts.

Results

Three main themes emerged: (1) BD is often misdiagnosed, (2) information crucial to evaluating BD is often occluded from clinical observation, and (3) BD misdiagnosis has important treatment implications.

Discussion

Using upstream stakeholder engagement methods, we were able to identify a narrow, unforeseen, and clinically relevant problem. We propose an organizing framework for development of digital tools based upon clinician-identified unmet need.

Optimizing multi-domain hematologic biomarkers and clinical features for the differential diagnosis of unipolar depression and bipolar depression

There is a lack of objective features for the differential diagnosis of unipolar and bipolar depression, especially those that are readily available in practical settings. We investigated whether clinical features of disease course, biomarkers from complete blood count, and blood biochemical markers could accurately classify unipolar and bipolar depression using machine learning methods. This retrospective study included 1160 eligible patients (918 with unipolar depression and 242 with bipolar depression). Patient data were randomly split into training (85%) and open test (15%) sets 1000 times, and the average performance was reported. XGBoost achieved the optimal open-test performance using selected biomarkers and clinical features-AUC 0.889, sensitivity 0.831, specificity 0.839, and accuracy 0.863. The importance of features for differential diagnosis was measured using SHapley Additive exPlanations (SHAP) values. The most informative features include (1) clinical features of disease duration and age of onset, (2) biochemical markers of albumin, low density lipoprotein (LDL), and potassium, and (3) complete blood count-derived biomarkers of white blood cell count (WBC), platelet-to-lymphocyte ratio (PLR), and monocytes (MONO). Overall, onset features and hematologic biomarkers appear to be reliable information that can be readily obtained in clinical settings to facilitate the differential diagnosis of unipolar and bipolar depression.

Anticipating Unipolar Depression and Bipolar Depression in young adult with first episode of depression using childhood trauma and personality

Objective

Relevant research focusing on young adults with Unipolar Depression (UD) and Bipolar Depression (BD) is limited. The current research aims to investigate childhood trauma and personality traits in young adults with UD and BD.

Methods

Two hundred and thirty-five patients in a first depressive episode (diagnosed UD and BD), 16-25 years old, were recruited from Second Xiangya Hospital. And 79 healthy controls (HC) were recruited from the community to form the comparison group. Patients' childhood trauma was measured by the Childhood Trauma Questionnaire (CTQ), and personality was measured by Eysenck Personality Inventory (EPI). The Kruskal-Wallis test was used to compare depression, anxiety, CTQ, and EPI scores between the HC (n = 79), UD (n = 131), and BD (n = 104) groups. Factors independently associated with mood disorders and BD were determined using binary logistic regression analyses.

Results

Compared with HC, mood disorders had more severe anxiety and depression symptoms, and higher CTQ. Emotional abuse (OR = 1.47; 95% CI = 1.08-2.01), emotional neglect (OR = 1.24; 95% CI = 1.05-1.46), and neuroticism (OR = 1.25; 95% CI = 1.16-1.35) were associated with significantly increased odds of mood disorders. Whereas, higher extraversion scores were a protective factor for mood disorders. Compared with UD, BD had more severe anxiety symptoms, and higher CTQ, than extraversion and neuroticism personality scores. Anxiety (OR = 1.06; 95% CI = 1.02-1.08) and extraversion (OR = 1.05; 95% CI = 1.03-1.09) were associated with significantly increased odds of BD.

Conclusion

Interventions to prevent childhood trauma may improve young adults' mental health. Using childhood trauma and personality to anticipate BD and UD creates more accurate treatment for young adults with first depression.

Comorbidity of adult ADHD and substance use disorder in a sample of inpatients bipolar disorder in Iran

BACKGROUNDS

The study of the relationship between adult Attention deficit hyperactivity disorder (ADHD) and bipolar disorder has received more attention in recent years and there is limited information in this area. On the other hand, there is a significant comorbidity between ADHD and bipolar disorder with substance use disorder. In this study, we investigated the prevalence of comorbidity of adult ADHD and substance use disorder among a group of bipolar patients admitted to a psychiatric hospital.

METHODS

One hundred fifty patients from a total of 200 consecutive patients who were referred to the emergency department of Roozbeh Psychiatric Hospital in Tehran, diagnosed with bipolar disorder based on the initial psychiatric interview and needed hospitalization, were evaluated again by an experienced faculty member psychiatrist by using a subsequent interview based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition(DSM-5). They were evaluated using the Structured Clinical Interview for DSM-5 (SCID-5) questionnaire to confirm the diagnosis of bipolar disorder and the comorbidity of adult ADHD and substance use disorder.

RESULTS

From 150 patients diagnosed with bipolar disorder, 106 patients (70.7%) had adult ADHD. 89 patients (59.3%) had substance use disorder and 58 patients (38.7%) had both of these comorbidities with bipolar disorder. Comorbidity of adult ADHD was associated with the earlier onset of the first mood episode in bipolar disorder (p value = 0.025). There was no statistically significant relationship between substance use disorder and age of onset of the first episode. (P value = 0.57).

CONCLUSIONS

Due to the limitations of studies on adult ADHD comorbidity with bipolar disorder, especially in hospital settings, as well as the increased risk of association with substance use disorder, further multicenter studies in this area with larger sample sizes can increase awareness in this regard.

Sex differences in the blood-brain barrier: Implications for mental health

Prevalence of mental disorders, including major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ) are increasing at alarming rates in our societies. Growing evidence points toward major sex differences in these conditions, and high rates of treatment resistance support the need to consider novel biological mechanisms outside of neuronal function to gain mechanistic insights that could lead to innovative therapies. Blood-brain barrier alterations have been reported in MDD, BD and SZ. Here, we provide an overview of sex-specific immune, endocrine, vascular and transcriptional-mediated changes that could affect neurovascular integrity and possibly contribute to the pathogenesis of mental disorders. We also identify pitfalls in current literature and highlight promising vascular biomarkers. Better understanding of how these adaptations can contribute to mental health status is essential not only in the context of MDD, BD and SZ but also cardiovascular diseases and stroke which are associated with higher prevalence of these conditions.

Place of care and costs associated with acute episodes and remission in bipolar I disorder

AIMS

To our knowledge, literature describing the place of care and associated costs during acute bipolar I disorder (BP-I) episodes is limited. We conducted a claims-based retrospective study to address this gap.

MATERIALS AND METHODS

Adults with BP-I were identified via IBM MarketScan Commercial and Medicare Supplemental databases. The acute episode index date was defined by ≥1 inpatient BP-I claim(s) or ≥1 outpatient or ≥3 outpatient BP-I claims (depending on visit type) in a 2-week (manic/mixed) or 4-week (depressive) period. Likely acute episodes were defined as 3- and 6-week periods for manic/mixed and depressive episodes, respectively; total mental health-related medical costs (health plan + patient) were collected during these intervals and stratified by setting (inpatient versus outpatient). Initial and subsequent episodes were captured; data were reported in subgroups without and with clozapine use, a proxy for disease severity. The remission index date was the earliest outpatient claim with a bipolar remission diagnosis with no acute episode or treatment. Remission costs were collected over a 3-month period. All results were analyzed descriptively.

RESULTS

A total of 41,516 patients with 130,221 acute manic/mixed episodes and 47,763 patients with 149,207 acute depressive episodes met the study criteria. Over 84% of acute episodes were treated in outpatient settings. Mental health-related medical costs for manic/mixed episodes were $15,444 for inpatient and $1,577 for outpatient settings; inpatient and outpatient costs for depressive episodes were $17,376 and $2,154, respectively. Health plans covered approximately 78% of medical costs for both episode types with and without prior clozapine use. A total of 8,143 patients met remission criteria; the total 3-month outpatient costs were $1,225.

CONCLUSIONS

Most BP-I acute manic/mixed or depressive episodes were treated in the outpatient setting. Episodes with inpatient care were 8-10 times more costly than outpatient-only episodes. Health plans covered most medical costs, but additional patient-incurred out-of-pocket costs remained.

The Rapid Mood Screener (RMS): a novel and pragmatic screener for bipolar I disorder

OBJECTIVE

Depressive episodes and symptoms of bipolar I disorder are commonly misdiagnosed as major depressive disorder (MDD) in primary care. The novel and pragmatic Rapid Mood Screener (RMS) was developed to screen for manic symptoms and bipolar I disorder features (e.g. age of depression onset) to address this unmet clinical need.

METHODS

A targeted literature search was conducted to select concepts thought to differentiate bipolar I from MDD and screener tool items were drafted. Items were tested and refined in cognitive debriefing interviews with individuals with self-reported bipolar I or MDD (n = 12). An observational study was conducted to evaluate predictive validity. Participants with clinical interview-confirmed bipolar I or MDD diagnoses (n = 139) completed a draft 10-item screening tool and other questionnaires. Data were analyzed to identify the smallest possible subset of items with optimized sensitivity and specificity.

RESULTS

Adults with confirmed bipolar I (n = 67) or MDD (n = 72) participated in the observational study. Ten draft screening tool items were reduced to 6 final RMS items based on the item-level analysis. When 4 or more items of the RMS were endorsed ("yes"), sensitivity was 0.88 and specificity was 0.80; positive and negative predictive values were 0.80 and 0.88, respectively. These properties were an improvement over the Mood Disorder Questionnaire in the same analysis sample while using 60% fewer items.

CONCLUSION

The pragmatic 6-item RMS differentiates bipolar I disorder from MDD in patients with depressive symptoms, providing real-world guidance to primary care practitioners on whether a more comprehensive assessment for bipolar I disorder is warranted.