Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach

Sex-specific risk profiles for suicide mortality in bipolar disorder: incidence, healthcare utilization and comorbidity

BACKGROUND

Evidence on sex-specific incidence and comorbidity risk factors of suicide among patients with bipolar disorder is scarce. This study investigated the sex-specific risk profiles for suicide among the bipolar disorder population in terms of incidence, healthcare utilization and comorbidity.

METHODS

Using data from the Taiwan National Health Insurance Research Database between 1 January 2000 and 31 December 2016, this nationwide cohort study included patients with bipolar disorder (N = 46 490) and individuals representative of the general population (N = 185 960) matched by age and sex at a 1:4 ratio. Mortality rate ratios (MRRs) of suicide were calculated between suicide rates of bipolar disorder cohort and general population. In addition, a nested case-control study (1428 cases died by suicide and 5710 living controls) was conducted in the bipolar disorder cohort to examine the sex-specific risk of healthcare utilization and comorbidities.

RESULTS

Suicide risk was considerably higher in the cohort (MRR = 21.9) than in the general population, especially among women (MRR = 35.6). Sex-stratified analyses revealed distinct healthcare utilization patterns and physical comorbidity risk profiles between the sexes. Although female patients who died by suicide had higher risks of nonhypertensive cardiovascular disease, pneumonia, chronic kidney disease, peptic ulcer, irritable bowel syndrome, and sepsis compared to their living counterparts, male patients who died by suicide had higher risks of chronic kidney disease and sepsis compared to the living controls.

CONCLUSIONS

Patients with bipolar disorder who died by suicide had sex-specific risk profiles in incidence and physical comorbidities. Identifying these modifiable risk factors may guide interventions for suicide risk reduction.

Prevalence of suicide attempts and correlates among first-episode and untreated major depressive disorder patients with comorbid dyslipidemia of different ages of onset in a Chinese Han population: a large cross-sectional study

BACKGROUND

Patients with dyslipidemia are at increased risk for suicide, especially those with major depressive disorder (MDD). Few studies have investigated the independent effects of suicide attempts on comorbid dyslipidemia in patients with MDD. Moreover, there are no comparisons of differences in factors associated with suicide attempts among patients with MDD with dyslipidemia at different ages of onset. The aim of this study was to investigate the prevalence of suicide attempts and associated variables in first episode and untreated patients with MDD with comorbid dyslipidemia at different ages of onset.

METHODS

We recruited 1718 patients with first-episode untreated MDD in this study. Demographical and clinical data were collected, and lipid profiles, thyroid function, and blood glucose levels were measured. The Hamilton Depression Scale 17 (HAMD-17), Hamilton Anxiety Scale (HAMA), Clinical Global Impression Severity Scale (CGI), and Positive and Negative Syndrome Scale (PANSS) positive subscale were assessed for depression, anxiety and illness severity, as well as psychotic symptoms, respectively.

RESULTS

The percentage of patients with MDD with comorbid dyslipidemia was 61% (1048/1718). Among patients with MDD with comorbid dyslipidemia, the incidence of suicide attempts was 22.2% (170/765) for early adulthood onset and 26.5% (75/283) for mid-adulthood onset. Independent factors associated with suicide attempts in early adulthood onset patients with MDD with dyslipidemia were as follows: HAMA score (B = 0.328, P < 0.0001, OR = 1.388), Suspicion /persecution (B = -0.554, P = 0.006, OR = 0.575), CGI (B = 0.878, P < 0.0001, OR = 2.406), systolic blood pressure (B = 0.048, P = 0.004, OR = 1.049), hallucinatory behavior (B = 0.334, P = 0.025, OR = 1.397), and TPOAb (B = 0.003, p < 0.0001, OR = 1.003). Independent factors associated with suicide attempts in mid-adulthood onset patients with MDD with comorbid dyslipidemia were as follows: HAMA score (B = 0.182, P < 0.0001, OR = 1.200), CGI (B = 1.022, P < 0.0001, OR = 2.778), and TPOAb (B = 0.002, P = 0.009, OR = 1.002).

CONCLUSION

Our findings suggest an elevated risk of suicide attempts in patients with MDD with comorbid dyslipidemia. The incidence of suicide attempts was similar in the early- and mid-adulthood onset subgroups among patients with MDD with dyslipidemia, but the factors associated with suicide attempts were different in these two subgroups.

Developing "MinDag" - an app to capture symptom variation and illness mechanisms in bipolar disorder

Introduction

The illness course of bipolar disorder (BD) is highly heterogeneous with substantial variation between individuals with the same BD subtype and within individuals over time. This heterogeneity is not well-delineated and hampers the development of more targeted treatment. Furthermore, although lifestyle-related behaviors are believed to play a role in the illness course, such mechanisms are poorly understood. To address some of these knowledge gaps, we aimed to develop an app for collection of multi-dimensional longitudinal data on BD-relevant symptoms and lifestyle-related behaviors.

Methods

An app named MinDag was developed at the Norwegian Center for Mental Disorders Research in Oslo, Norway. The app was designed to tap into selected areas: mood, sleep, functioning/activities (social, occupational, physical exercise, leisure), substance use, emotional reactivity, and psychotic experiences. Ethical, security and usability issues were highly prioritized throughout the development and for the final app solution. We conducted beta- and pilot testing to eliminate technical problems and enhance usability and acceptability.

Results

The final version of MinDag comprises six modules; three which are presented for the user once daily (the Sleep module in the morning and the Mood and Functoning/Activities modules in the evening) and three which are presented once weekly (Substance Use, Emotional Reactivity, and Psychotic Experiences modules). In general, MinDag was well received in both in the beta-testing and the pilot study, and the participants provided valuable feedback that was taken into account in the final development. MinDag is now in use as part of the research protocol at the NORMENT center and in a specialized treatment unit for BD at Oslo University Hospital in Norway.

Discussion

We believe that MinDag will generate unique longitudinal data well suited for capturing the heterogeneity of BD and clarifying important unresolved issues such as how life-style related behavior may influence BD symptoms. Also, the experiences and knowledge derived from the development of MinDag may contribute to improving the security, acceptability, and benefit of digital tools in mental health.

Association between neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and C-reactive protein levels and metabolic status in patients with a bipolar disorder

OBJECTIVES

Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and C-Reactive Protein (CRP) are markers of inflammation that are elevated in bipolar disorder (BD) and are also related to a higher risk of metabolic syndrome (MetS). This study aimed at investigating for the first time the association between NLR, PLR, and CRP and the metabolic status in BD.

METHODS

We assessed the association between biomarkers and the metabolic status: number of metabolic risk factors, presence of MetS, insulin sensitivity (Quantitative Insulin Sensitivity Check Index, QUICKI) and insulin resistance (Homeostatic Model Assessment for Insulin Resistance, HOMA-IR index), in a sample of 219 outpatients with BD.

RESULTS

25.9% of the sample met the criteria for MetS. High levels of CRP were found in 12% of the sample. Older age, low PLR, high NLR, and high CRP levels significantly predicted a higher number of MetS risk factors (p < 0.001). Older age and low PLR were associated with a greater likelihood of developing MetS (p = 0.007).

CONCLUSIONS

Although further studies are needed to replicate and validate these findings, inflammatory biomarkers as CRP, PLR and NLR could be useful tools to identify patients with a BD at risk for a metabolic adverse outcome.

Key findings on bipolar disorders from the longitudinal FondaMental Advanced Center of Expertise-Bipolar Disorder (FACE-BD) cohort

BACKGROUND

The FACE-BD cohort is an observational cohort of individuals with bipolar disorders (BD) who benefited from a systematic evaluation with evidence-based treatment recommendations and who were followed-up every year for 3 years in France. The objectives were to describe the lifetime course of BD, associated psychiatric and somatic comorbidities, and cognition profile. This cohort aims to identify clinical/biological signatures of outcomes, trajectories of functioning and transition between clinical stages. This article summarizes 10 years of findings of the FACE-BD cohort.

METHOD & RESULTS

We included 4422 individuals, all having a baseline assessment, among which 61.2% had at least one follow-up visit at either one, two or three years. A subsample of 1200 individuals had at least one biological sample (serum, plasma, DNA). Assessments include family history of psychiatric disorders, psychiatric diagnosis, current mood symptoms, functioning, hospitalizations, suicidal attempts, physical health, routine blood tests, treatment history, psychological dimensions, medico-economic data and a cognitive assessment. Studies from this cohort illustrate that individuals with BD display multiple coexistent psychiatric associated conditions including sleep disturbances, anxiety disorders, substance use disorders and suicide attempts as well as a high prevalence of metabolic syndrome. During follow-up, we observed a 55% reduction of the number of days of hospitalization and a significant improvement in functioning.

CONCLUSIONS

The FACE-BD cohort provides a strong research infrastructure for clinical research in BD and has a unique position among international cohorts because of its comprehensive clinical assessment and sustainable funding from the French Ministry of Health.

Characterization of affective lability across subgroups of psychosis spectrum disorders

BACKGROUND

Affective lability is elevated and associated with increased clinical burden in psychosis spectrum disorders. The extent to which the level, structure and dispersion of affective lability varies between the specific disorders included in the psychosis spectrum is however unclear. To have potential value as a treatment target, further characterization of affective lability in these populations is necessary. The main aim of our study was to investigate differences in the architecture of affective lability in different psychosis spectrum disorders, and if putative differences remained when we controlled for current symptom status.

METHODS

Affective lability was measured with The Affective Lability Scale Short Form (ALS-SF) in participants with schizophrenia (SZ, n = 76), bipolar I disorder (BD-I, n = 105), bipolar II disorder (BD-II, n = 68) and a mixed psychosis-affective group (MP, n = 48). Multiple analyses of covariance were conducted to compare the ALS-SF total and subdimension scores of the diagnostic groups, correcting for current psychotic, affective and anxiety symptoms, substance use and sex. Double generalized linear models were performed to compare the dispersion of affective lability in the different groups.

RESULTS

Overall group differences in affective lability remained significant after adjusting for covariates (p = .001). BD-II had higher affective lability compared to SZ and BD-I (p = .004), with no significant differences between SZ and BD-I. There were no significant differences in the contributions of ALS-SF dimensions to the total affective lability or in dispersion of affective lability between the groups.

CONCLUSIONS

This study provides the construct of affective lability in psychosis spectrum disorders with more granular details that may have implications for research and clinical care. It demonstrates that despite overlap in core symptom profiles, BD-I is more similar to SZ than it is to BD-II concerning affective lability and the BD groups should consequently be studied apart. Further, affective lability appears to be characterized by fluctuations between depressive- and other affective states across different psychosis spectrum disorders, indicating that affective lability may be related to internalizing problems in these disorders. Finally, although the level varies between groups, affective lability is evenly spread and not driven by extremes across psychosis spectrum disorders and should be assessed irrespective of diagnosis.

Machine learning as the new approach in understanding biomarkers of suicidal behavior

In psychiatry, compared to other medical fields, the identification of biological markers that would complement current clinical interview, and enable more objective and faster clinical diagnosis, implement accurate monitoring of treatment response and remission, is grave. Current technological development enables analyses of various biological marks in high throughput scale at reasonable costs, and therefore 'omic' studies are entering the psychiatry research. However, big data demands a whole new plethora of skills in data processing, before clinically useful information can be extracted. So far the classical approach to data analysis did not really contribute to identification of biomarkers in psychiatry, but the extensive amounts of data might get to a higher level, if artificial intelligence in the shape of machine learning algorithms would be applied. Not many studies on machine learning in psychiatry have been published, but we can already see from that handful of studies that the potential to build a screening portfolio of biomarkers for different psychopathologies, including suicide, exists.

Inflammation, anxiety, and stress in bipolar disorder and borderline personality disorder: A narrative review

Bipolar disorder (BD) and borderline personality disorder (BPD) are serious and prevalent psychiatric diseases that share common phenomenological characteristics: symptoms (such as anxiety, affective lability or emotion dysregulation), neuroimaging features, risk factors and comorbidities. While several studies have focused on the link between stress and peripheral inflammation in other affective disorders such as anxiety or depression, fewer have explored this relationship in BD and BPD. This review reports on evidence showing an interplay between immune dysregulation, anxiety and stress, and how an altered acute neuroendocrine stress response may exist in these disorders. Moreover, we highlight limitations and confounding factors of these existing studies and discuss multidirectional hypotheses that either suggest inflammation or stress and anxiety as the primum movens in BD and BPD pathophysiology, or inflammation as a consequence of the pathophysiology of these diseases. Untangling these associations and implementing a transdiagnostic approach will have diagnostic, therapeutic and prognostic implications for BD and BPD patients.

Blood pressure in bipolar disorder: evidence of elevated pulse pressure and associations between mean pressure and mood instability

BACKGROUND

Bipolar disorder (BD) is associated with excess and premature cardiovascular mortality. Elevated blood pressure (BP) is a leading contributor to cardiovascular risk. However, few studies have examined BP in BD in comparison to other psychiatric disorders. Furthermore, the association between BP and mood instability is not presently clear despite increasing interest in repurposing existing antihypertensive medications as possible novel BD treatments. Thus we examined BP differences between BD and borderline personality disorder (BPD), a disorder with a similar symptom profile through chronic mood instability.

METHODS

A total of 106 adults (38 BD, 25 BPD, and 43 healthy controls), evaluated in the Automated Monitoring of Symptom Severity (AMoSS) study, completed a week-long home blood pressure monitoring assessment and ecological momentary assessment of mood. We examined group-wise differences in mean BP and BP variability and their association with mood instability.

RESULTS

BD individuals had a significantly wider resting pulse pressure (40.8 ± 7.4, mmHg) compared to BPD (35.7 ± 5.3, mmHg, P = 0.03) and control participants (37.3 ± 6.3, mmHg, P = 0.036). Systolic BP was negatively associated with sad mood instability, and all measures of mean BP (systolic, diastolic, and mean arterial pressure) were negatively associated with positive mood instability.

CONCLUSIONS

This study demonstrates BP differences between BD and healthy and clinical controls that are within a normotensive range. Early pulse pressure widening may be a modifiable pathophysiological feature of BD that confers later cardiovascular risk. BP may be an important transdiagnostic predictor of mood instability and a potential explicit treatment target.

A comparison of inflammatory markers in manic and euthymic states of bipolar disorder

OBJECTIVES

The number of studies investigating inflammatory biomarkers in bipolar disorder has increased significantly in recent years. The neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to lymphocyte ratio (MLR) are inexpensive and easy to obtain values used to measure the level of inflammation. This study compared the NLR, PLR, and MLR values in the manic and euthymic phases of the same patients.

METHODS

Patients who met the inclusion criteria and were hospitalized due to bipolar affective disorder manic episodes at the Ondokuz Mayis University Faculty of Medicine inpatient psychiatry clinic between 01.01.2013 and 01.01.2019 were enrolled in the study. One hundred thirteen patients undergoing manic episodes were included. White blood cells, neutrophil, lymphocyte, platelet, and monocyte counts were retrospectively recorded from complete blood count data collected during the hospital stay, and NLR, PLR, and MLR values were calculated from these.

RESULTS

Neutrophil, platelet, and monocyte counts, as well as NLR, PLR, and MLR values were higher in the manic episodes of bipolar disorder compared to the control group. Decreased neutrophil and lymphocyte counts, and decreased NLR, PLR, and MLR were observed in the remission period after-treatment of the manic bipolar disorder episodes. In the euthymic phase of bipolar disorder, however, platelet and monocyte counts and MLR were higher than in the control group.

CONCLUSIONS

The study indicates that NLR and PLR may be used as state markers and that MLR may be used as a trait marker in bipolar disorder.

Allostatic load, emotional hyper-reactivity, and functioning in individuals with bipolar disorder

OBJECTIVES

Diagnosis and management of bipolar disorder (BD) are limited by the absence of available biomarkers. Allostatic load (AL) represents the strain that stress, including the effects of acute phases and inter-episode chronic mood instability, exerts on interconnected biological systems. This study aimed to operationalize an AL index and explore whether it could be relevant to better characterize BD patients with and without emotional hyper-reactivity particularly those at higher risk of immune-cardiometabolic dysregulation and functional impairment.

METHODS

Levels of biomarkers of chronic inflammation (hsCRP and albumin), cardiovascular (systolic/diastolic blood pressure) and metabolic functions (fasting glucose, glycosylated hemoglobin, total cholesterol, LDL, HDL, and triglycerides) were measured in 1072 adult BD outpatients. Patients were classified in two groups (with/without emotional hyper-reactivity) assessed by the Multidimensional Assessment of Thymic States scale. An Allostatic Load Index for BD (BALLI), comprising six biomarkers, was constructed using data-driven biomarker selection.

RESULTS

BALLI showed 81.1% accuracy with good sensitivity (81%) and specificity (81.2%) for characterizing BD patients presenting emotional hyper-reactivity, elevated risk of inflammation (increased hsCRP, hypoalbuminemia) and cardiometabolic disturbances (hypertension, hyperglycemia, and hypertriglyceridemia). Patients classified by the BALLI as presenting emotional hyper-reactivity had significantly lower global and cognitive functioning than those without emotional hyper-reactivity (P < .0001).

CONCLUSIONS

A multidimensional approach based on a simple AL score (eg, BALLI) and dimensions of behavior (eg, emotional hyper-reactivity) alongside mood is clinically relevant. AL index could be a useful tool to detect multisystemic physiological dysregulations in BD patients with/without emotional hyper-reactivity particularly those at higher risk of immune-cardiometabolic disturbances and functional impairment.

Toi Même, a Mobile Health Platform for Measuring Bipolar Illness Activity: Protocol for a Feasibility Study

BACKGROUND

The diagnosis and management of bipolar disorder are limited by the absence of available biomarkers. Patients with bipolar disorder frequently present with mood instability even during remission, which is likely associated with the risk of relapse, impaired functioning, and suicidal behavior, indicating that the illness is active.

OBJECTIVE

This research protocol aimed to investigate the correlations between clinically rated mood symptoms and mood/behavioral data automatically collected using the Toi Même app in patients with bipolar disorder presenting with different mood episodes. This study also aimed to assess the feasibility of this app for self-monitoring subjective and objective mood/behavior parameters in those patients.

METHODS

This open-label, nonrandomized trial will enroll 93 (31 depressive, 31 euthymic, and 31 hypomanic) adults diagnosed with bipolar disorder type I/II (Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria) and owning an iPhone. Clinical evaluations will be performed by psychiatrists at the baseline and after 2 weeks, 1 month, 2 months, and 3 months during the follow-up. Rather than only accessing the daily mood symptoms, the Toi Même app also integrates ecological momentary assessments through 2 gamified tests to assess cognition speed (QUiCKBRAIN) and affective responses (PLAYiMOTIONS) in real-life contexts, continuously measures daily motor activities (eg, number of steps, distance) using the smartphone's motion sensors, and performs a comprehensive weekly assessment.

RESULTS

Recruitment began in April 2018 and the completion of the study is estimated to be in December 2021. As of April 2019, 25 participants were enrolled in the study. The first results are expected to be submitted for publication in 2020. This project has been funded by the Perception and Memory Unit of the Pasteur Institute (Paris) and it has received the final ethical/research approvals in April 2018 (ID-RCB: 2017-A02450-53).

CONCLUSIONS

Our results will add to the evidence of exploring other alternatives toward a more integrated approach in the management of bipolar disorder, including digital phenotyping, to develop an ethical and clinically meaningful framework for investigating, diagnosing, and treating individuals at risk of developing bipolar disorder or currently experiencing bipolar disorder. Further prospective studies on the validity of automatically generated smartphone data are needed for better understanding the longitudinal pattern of mood instability in bipolar disorder as well as to establish the reliability, efficacy, and cost-effectiveness of such an app intervention for patients with bipolar disorder.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03508427; https://clinicaltrials.gov/ct2/show/NCT03508427.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/18818.

Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations

Suicide is a leading cause of death that defies prediction and challenges prevention efforts worldwide. Artificial intelligence (AI) and machine learning (ML) have emerged as a means of investigating large datasets to enhance risk detection. A systematic review of ML investigations evaluating suicidal behaviors was conducted using PubMed/MEDLINE, PsychInfo, Web-of-Science, and EMBASE, employing search strings and MeSH terms relevant to suicide and AI. Databases were supplemented by hand-search techniques and Google Scholar. Inclusion criteria: (1) journal article, available in English, (2) original investigation, (3) employment of AI/ML, (4) evaluation of a suicide risk outcome. N = 594 records were identified based on abstract search, and 25 hand-searched reports. N = 461 reports remained after duplicates were removed, n = 316 were excluded after abstract screening. Of n = 149 full-text articles assessed for eligibility, n = 87 were included for quantitative synthesis, grouped according to suicide behavior outcome. Reports varied widely in methodology and outcomes. Results suggest high levels of risk classification accuracy (>90%) and Area Under the Curve (AUC) in the prediction of suicidal behaviors. We report key findings and central limitations in the use of AI/ML frameworks to guide additional research, which hold the potential to impact suicide on broad scale.

An emotional-response model of bipolar disorders integrating recent findings on amygdala circuits

Because of our classification system limitations for defining psychiatric disorders and understanding their physiopathology, a new research area based on dimensions has emerged. It consists of exploring domains derived from fundamental behavioral components linked to neurobiological systems. Emotional processing is among the most affected dimensions in bipolar disorders (BD), but is excluded from the definition criteria. The purpose of this review is to synthesize the emotional responses disruption during the different phases of BD, using intensity and valence as the two key characteristics of emotions. We integrate those emotional disruptions into an original, emotion-based model contrasting with the current diagnostic frame built on mood. Emotional processing is underpinned by cortico-limbic circuits involving the amygdala. Recent publications showed the crucial role of the amygdala in emotional processes triggered by stimuli of negative, but also positive valence. We show how these neuroscience data can provide physiological basis for emotional disturbances observed in BD. We conclude with translational perspectives to improve the current knowledge about neural substrates underlying altered emotional responses characterizing BD.

Odor-related brain hyper-reactivity in euthymic bipolar disorder: An fMRI and ERP study

Previous studies on olfactory function in patients with bipolar disorder (BD) are limited and contradictory. The current study aimed to comprehensively analyze the olfactory function of patients with euthymic BD using psychophysical, electrophysiological and neuroimaging techniques. Twenty-one patients with BD in remission and 20 healthy controls were tested with the "Sniffin' Sticks" olfactory test. Block-design fMRI data to a pleasant and an unpleasant stimulus were acquired while recording intensity and hedonic ratings. Olfactory event-related potentials (OERP) to the same stimuli were additionally recorded. Results show no differences between patients and healthy controls in terms of self-rated olfactory function and tested olfactory domains (odor threshold, discrimination or identification) (p>0.05). Compared to healthy controls, patients showed an increased fMRI activation in multiple cortical and subcortical regions as a response to olfactory stimulation, as well as larger amplitudes of OERPs regardless of the hedonic valence of the odor. All in all, patients with euthymic BD showed a stronger central responsiveness to odorous stimuli in fMRI and OERPs despite of normal psychophysical results, indicating the probable existence of an odor-related over-reactive brain network in the remission phase of BD.

Characterization of Mood Instability through Bipolar Disorders: A cluster-analytic approach using weekly prospective life-chart methodology

BackgroundThe aim of this study was to characterize mood instability (MI) in Bipolar Disorder (BD) and to investigate potential differences between subtype I and II. MethodsLife-charts from weekly mood ratings of 90 patients were used to compute: weeks spent with symptoms, number of episodes, and MI. Regression analyses were conducted to assess the relationship between BD subtype and MI adjusting by all potential confounding factors. Hierarchical cluster analysis was performed to determine the appropriate number of clusters that described the data and to assign subjects to a specific cluster based on their MI. We then compared clusters on clinical and psychosocial outcomes. ResultsMedian follow-up was 5 years (IQR: 3.6-7.9). Patients spent 15.2%, 5%, and 3% of follow-up with depressive, manic, and mixed symptoms, respectively. BD type II presented higher MI (β = 1.83, 95% CI: 0.66-3.00) and subsydromal symptoms than BD type I patients. No differences in functioning or recurrences were found between subtypes. Differences in MI between the two clusters mimicked those between type I and II but enhanced (β = 3.86, 95%CI -4.72, -2.66). High MI (n = 43) patients presented poorer functioning and higher recurrences compared to Low MI patients (n = 43). ConclusionBD type II presented higher MI and subsyndromal symptoms than BD type I patients. However, these differences did not translate into clinically relevant outcomes. A classification based on MI may provide useful clinical insights.