Predominant Polarity and Polarity Index of Maintenance Treatments for Bipolar Disorder: A Validation Study in a Large Naturalistic Sample in Italy

Exploring the predictive role of the first mood episode on the predominant polarity in bipolar disorder: insights from a path analysis

BACKGROUND

The predominant polarity in bipolar disorder (BD) is defined by the skewness of mood episodes towards either the manic or depressive pole. However, since the predominant polarity can only be established over the long term, it is crucial to identify predictors of illness trajectory. Among these factors, the polarity at onset has been suggested to hold important implications, even though research in this field is not entirely consistent so far. In this retrospective study, we thus explored whether the polarity of the first episode can predict the predominant polarity in BD.

METHODS

We included subjects with BD consecutively referred to two acute inpatient units in the Milan metropolitan area from May 2020 to January 2024. Following Barcelona criteria, a manic (mPP) and a depressive (dPP) predominant polarity were defined as having a ratio ≥ 2:1 of past manic/hypomanic or depressive episodes, respectively. The relationship between first episode polarity and either mPP or dPP was examined using multivariable logistic regression models. A path analysis was then performed to jointly test the associations between putative variables and the predominant polarity.

RESULTS

This study included 128 participants. Regression models estimated an association between a manic onset and a mPP (β = 3.23, p < 0.001) as well as between a depressive onset and a dPP (β = 3.65, p < 0.001). Participants with a mPP showed a lower age at onset (β = - 0.13, p = 0.004), while subjects diagnosed with BD type I were less likely to show a dPP (β = - 2.09, p = 0.024). The path analysis highlighted an association between earlier onset and the likelihood of a first episode of manic polarity (coeff. = - 1.39, p = 0.021). A manic onset was associated with a higher likelihood of mPP (coeff. = 3.46, p < 0.001) and a lower likelihood of dPP (coeff. = - 3.71, p < 0.001). Consistently, participants with a manic onset were more likely to experience a lower number of depressive episodes (coeff. = - 1.36, p < 0.001). Finally, cannabis use disorder was associated with a lower number of depressive episodes (coeff. = - 0.57, p = 0.011).

CONCLUSIONS

These results provide important insights into the likely predictive value of first episode polarity in relation to the predominant polarity in BD. Though future studies validating these findings are needed, the polarity at onset may serve as an early marker for illness trajectory.

Prevalence and correlates of manic/hypomanic and depressive predominant polarity in bipolar disorder: systematic review and meta-analysis

BACKGROUND

Identification of the predominant polarity, i.e. hypomanic/manic (mPP) or depressive predominant polarity (dPP), might help clinicians to improve personalised management of bipolar disorder.

AIMS

We performed a systematic review and meta-analysis to estimate prevalence and correlates of mPP and dPP in bipolar disorder.

METHOD

The protocol was registered in the Open Science Framework Registries (https://doi.org/10.17605/OSF.IO/8S2HU). We searched main electronic databases up to December 2023 and performed random-effects meta-analyses of weighted prevalence of mPP and dPP. Odds ratios and weighted mean differences (WMDs) were used for relevant correlates.

RESULTS

We included 28 studies, providing information on rates and/or correlates of mPP and dPP. We estimated similar rates of mPP (weighted prevalence = 30.0%, 95% CI: 23.1 to 37.4%) and dPP (weighted prevalence = 28.5%, 95% CI: 23.7 to 33.7%) in bipolar disorder. Younger age (WMD = -3.19, 95% CI: -5.30 to -1.08 years), male gender (odds ratio = 1.39, 95% CI: 1.10 to 1.76), bipolar-I disorder (odds ratio = 4.82, 95% CI: 2.27 to 10.24), psychotic features (odds ratio = 1.56, 95% CI: 1.01 to 2.41), earlier onset (WMD = -1.57, 95% CI: -2.88 to -0.26 years) and manic onset (odds ratio = 13.54, 95% CI: 5.83 to 31.46) were associated with mPP (P < 0.05). Depressive onset (odds ratio = 12.09, 95% CI: 6.38 to 22.90), number of mood episodes (WMD = 0.99, 95% CI: 0.28 to 1.70 episodes), history of suicide attempts (odds ratio = 2.09, 95% CI: 1.49 to 2.93) and being in a relationship (odds ratio = 1.98, 95% CI: 1.22 to 3.22) were associated with dPP (P < 0.05). No differences were estimated for other variables.

CONCLUSIONS

Despite some limitations, our findings support the hypothesis that predominant polarity might be a useful specifier of bipolar disorder. Evidence quality was mixed, considering effects magnitude, consistency, precision and publication bias. Different predominant polarities may identify subgroups of patients with specific clinical characteristics.

Combining predominant polarity and affective spectrum concepts in bipolar disorder: towards a novel theoretical and clinical perspective

This is an overview of recent advances on predominant polarity conceptualization in bipolar disorder (BD). Current evidence on its operationalized definitions, possible contextualization within the affective spectrum, along with its epidemiological impact, and treatment implications, are summarized. Predominant polarity identifies three subgroups of patients with BD according to their mood recurrencies: (i) those with depressive or (ii) manic predominance as well as (iii) patients without any preponderance ('nuclear' type). A predominant polarity can be identified in approximately half of patients, with similar rates for depressive and manic predominance. Different factors may influence the predominant polarity, including affective temperaments. More generally, affective disorders should be considered as existing on a spectrum ranging from depressive to manic features, also accounting for disorders with 'ultrapredominant' polarity, i.e., unipolar depression and mania. While mixed findings emerge on its utility in clinical practice, it is likely that the construct of predominant polarity, in place of conventional differentiation between BD-I and BD-II, may be useful to clarify the natural history of the disorder and select the most appropriate interventions. The conceptualization of predominant polarity seems to reconcile previous theoretical views of both BD and affective spectrum into a novel perspective. It may provide useful information to clinicians for the early identification of possible trajectories of BD and thus guide them when selecting interventions for maintenance treatment. However, further research is needed to clarify the specific role of predominant polarity as a key determinant of BD course, outcome, and treatment response.

The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.