Bipolar Disorders最新文献

Objective: Individuals with bipolar disorder are at greater risk of developing cardiovascular disease. However, the mechanisms underlying this association remain poorly understood. This study aimed to (1) determine the risk of major adverse cardiovascular events (MACE) after adjusting for important confounders and (2) evaluate the neural, autonomic, and immune mechanisms underlying the link between bipolar disorder and cardiovascular disease.

Methods: Leveraging the Mass General Brigham Biobank, bipolar disorder and incident MACE were identified using the International Classification of Disease (ICD) codes. Incident MACE events were assessed from enrollment to the date of data lock (December 2020); or to the 10-year period. Health behavior data were derived from optional surveys. Cox regression hazard models were applied.

Results: Of 118,827 Biobank participants, 6009 were diagnosed with bipolar disorder. Those with bipolar disorder (vs. without) demonstrated a higher risk of MACE after adjusting for cardiovascular risk factors (hazard ratio [95% confidence interval] = 1.29 [1.10-1.51], p = 0.002). The relationship remained significant over 10 years after adjustment for unhealthy lifestyle behaviors (1.29 [1.03, 1.61], p = 0.025). Furthermore, SNA, autonomic nervous system, and inflammatory markers each significantly associated with both bipolar disorder and MACE risk. Each of these measures mediated the association between bipolar disorder and MACE (accounting for 3.8%-17.8% of the relationship).

Conclusion: This study demonstrates that bipolar disorder associates with heightened cardiovascular risk, even after accounting for cardiovascular risk. Moreover, the findings suggest that neurobiological pathways and perturbations in autonomic and inflammatory pathways may confer cardiovascular risk in bipolar disorder.

Objectives: Most bipolar disorder (BD) patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study aims to identify features predictive of the conversion from Major Depressive Disorder (MDD) to BD by leveraging electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia.

Methods: We employed a multivariable Cox regression model to identify important predictors of conversion from MDD to BD.

Results: Analyzing 15 years of EHR data from 13,607 patients diagnosed with MDD, a total of 1610 (11.8%) transitioned to BD. Predictive features of the conversion to BD included severity of the initial MDD episode, presence of psychosis and hospitalization at first episode, family history of BD, and female gender. Additionally, we observed associations with medication classes (positive associations with prescriptions of mood stabilizers, antipsychotics, and negative associations with antidepressants) and a positive association with suicidality, a feature derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within 5 years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%.

Conclusions: Our study confirms previously identified risk factors identified through registry-based studies (female gender and psychotic depression at the index MDD episode) and identifies novel ones (suicidality extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion and underscore its potential for the identification of novel risk factors, thereby improving early diagnosis.

Objectives: Register-based cohorts allow us to better understand bipolar disorder over a life course. They are inclusive and their long-term data collection provides a longer scope than most clinical trials. This mapping review provides an overview of register-based cohort studies of bipolar disorder to inform researchers of the strengths and limitations to this body of research and identify gaps for future research.

Methods: A systematic search was performed of Medline, EMBASE, and PsycINFO databases. Cohort studies were included if they focused on bipolar disorder and had a minimum of 1 year of longitudinal data. Studies needed to be from databases that monitor the whole state or national population. A descriptive analysis of the studies' populations and methodology provides an overview of this field of study and identifies evidence gaps.

Results: A hundred and forty-six studies were included. The majority were from databases in Taiwan (n = 63), Denmark (n = 38), Sweden (n = 23), and Finland (n = 11). Forty-eight studies focused on aetiological questions. Sixty prognostic studies identified cohorts with bipolar disorder and described the impact of the illness by considering comorbidity, prescribing patterns, social functioning, and mortality. Thirty-six treatment studies focused on the efficacy and adverse effects of pharmaceuticals and ECT. No studies focused on psychological treatments.

Conclusion: Bipolar disorder research should include register-based cohorts with greater geopolitical and cultural diversity. Custodians of health registers should consider how non-pharmaceutical interventions such as psychotherapy are captured. Register-based cohorts investigating treatments of bipolar disorder should consider long-term social outcomes alongside the usual clinical outcomes.