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

Published online by Cambridge University Press:  06 May 2024

Francesco Bartoli*
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Carlo Bassetti
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Marco Gazzola
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Letizia Gianfelice
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Daniele Cavaleri
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Cristina Crocamo
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
Giuseppe Carrà
Affiliation:
Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy; and Division of Psychiatry, University College London, UK
*
Correspondence: Francesco Bartoli. Email: francesco.bartoli@unimib.it
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Abstract

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.

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of Royal College of Psychiatrists

Bipolar disorder is a severe and chronic condition, affecting about 1–2% of the general population.Reference McIntyre, Berk, Brietzke, Goldstein, López-Jaramillo and Kessing1,Reference Vieta, Berk, Schulze, Carvalho, Suppes and Calabrese2 Its clinical course is characterised by mood recurrencies, in which depressive episodes alternate with manic or hypomanic episodes, according to the conventional differentiation between bipolar-I disorder (BD-I) and bipolar-II disorder (BD-II).3 However, despite epidemiological assumptions that people with bipolar disorder spend more time affected by depression than by mania,Reference Calabrese, Hirschfeld, Frye and Reed4,Reference Kupka, Altshuler, Nolen, Suppes, Luckenbaugh and Leverich5 the clinical course and trajectories of bipolar disorder may be rather heterogeneous.Reference Bartoli6,Reference Mignogna and Goes7 In particular, it has been proposed that a more fine-grained classification of bipolar disorder should consider whether the clinical course is characterised by a depressive (dPP) or manic/hypomanic (mPP) predominant polarity.Reference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8,Reference Colom, Vieta and Suppes9 The concept of predominant polarity was first introduced by Jules Angst,Reference Angst10 based on a study investigating 95 individuals with bipolar disorder. Participants were subdivided into three subtypes according to their mood recurrencies, i.e. the preponderantly manic, the preponderantly depressed and the nuclear type, in which there was a balanced proportion of depressive and manic episodes.Reference Angst10 Thereafter, Colom et alReference Colom, Vieta, Daban, Pacchiarotti and Sánchez-Moreno11 provided a more detailed definition of predominant polarity in bipolar disorder, proposing that to define mPP, manic/hypomanic episodes should represent at least two-thirds of the overall number of lifetime mood episodes. On the other hand, dPP requires that among lifetime mood episodes, at least two-thirds are depressive. Finally, an undetermined predominant polarity should be considered if there is a sufficiently balanced proportion between manic and depressive episodes in the clinical course of bipolar disorder, without any clear mood episode predominance.Reference Colom, Vieta, Daban, Pacchiarotti and Sánchez-Moreno11 Alternative definitions have been proposed,Reference Baldessarini, Undurraga, Vázquez, Tondo, Salvatore and Ha12 together suggesting that the identification of the predominant polarity might help clinicians to improve the personalised management of bipolar disorder by making its clinical trajectories clearer.Reference Colom, Vieta and Suppes9 Indeed, available evidence suggests that mPP or dPP may influence individual response to acute and long-term treatment for bipolar disorder, as well as the effectiveness of psychopharmacological agents used for the stabilisation phase.Reference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8,Reference Carvalho, Quevedo, McIntyre, Soeiro-de-Souza, Fountoulakis and Berk13 Exploring the hypothesis of predominant polarity as a possible clinical specifier, previous reviews have suggested that mPP and dPP might involve approximately half of all people with bipolar disorder and might be associated with particular individual characteristics.Reference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8,Reference García-Jiménez, Álvarez-Fernández, Aguado-Bailón and Gutiérrez-Rojas14 However, despite the growing scientific interest in this field,Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15Reference Sentissi, Popovic, Moeglin, Stukalin, Mosheva and Vieta18 no systematic analyses on rates and individual characteristics associated with mPP versus dPP are available so far. To shed light on this topic, we performed a systematic review and meta-analysis of observational studies aimed at identifying the prevalence and clinical correlates of different mood predominance types in bipolar disorder, as well as assessing the quality of evidence in terms of strength, precision, consistency and risk of publication bias.

Method

Study design and protocol

This systematic review and meta-analysis is reported following the Meta-analysis Of Observational Studies in Epidemiology guidelines.Reference Stroup, Berlin, Morton, Olkin, Williamson and Rennie19 The study protocol was registered on 27 November 2023 in Open Science Framework Registries (https://doi.org/10.17605/OSF.IO/8S2HU) and amended on 8 December 2023 because of changes in the search strategy.

Eligibility criteria

We included any observational studies (a) providing information on prevalence rates of mPP and dPP in people with bipolar disorder and (b) comparing them with respect to one or more sociodemographic or clinical characteristics. To be considered, studies had to include at least ten individuals in each group (mPP and dPP). Moreover, in order to improve consistency across studies and to reduce the risk of misclassification bias, we included only studies which used the recommended Colom's definition for predominant polarity.Reference Colom, Vieta, Daban, Pacchiarotti and Sánchez-Moreno11 Based on this, mPP and dPP are defined as a lifetime ratio ≥2:1 of either hypomanic/manic episodes or depressive episodes, respectively. This restrictive definition, splitting patients in three categories (mPP, dPP and undetermined predominant polarity), is considered to be more stable and conservative over time than other definitions,Reference Baldessarini, Undurraga, Vázquez, Tondo, Salvatore and Ha12 making patients less likely to be switched from one category to another across different episodes.Reference Colom, Vieta and Suppes9 We excluded studies (a) not providing information on predominant polarity, (b) not comparing mPP and dPP in terms of relevant sociodemographic or clinical characteristics, (c) including samples with a mean age <18 years, (d) using definitions of predominant polarity based on different criteria, and (e) published before the release date of DSM-IV.20 In order to avoid duplicate results, we excluded data on correlates derived from the same sample, including only the study that provided the larger amount of information. Finally, we excluded scientific reports not undergoing a peer-review process, such as conference abstracts, dissertations and grey literature.

Article screening

We searched the Embase, PubMed, APA PsycInfo (via ProQuest), and Emcare (via Ovid) databases for articles indexed up to 8 December 2023, without any language restrictions. We used the following search phrases adapted for each database: (a) Embase: ‘bipolar disorder’:ti,ab,kw AND ‘predominant polarity’:ti,ab,kw; (b) PubMed: bipolar [Title/Abstract] AND predominant polarity [Title/Abstract]; (c) PsycInfo: tiab(bipolar disorder) AND tiab(predominant polarity); (d) Ovid Emcare: (bipolar and (predominance or ‘predominant polarity’)).ti. or (bipolar and (predominance or ‘predominant polarity’)).ab. An additional manual search of studies included in two relevant reviewsReference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8,Reference García-Jiménez, Álvarez-Fernández, Aguado-Bailón and Gutiérrez-Rojas14 was carried out to check for further potentially eligible studies. References were managed using EndNote web software. After the preliminary screening based on titles and abstracts had been completed, full texts were retrieved to assess the final eligibility of studies. These procedures were completed by three authors (C.B., M.G. and L.G.) independently, and reasons for exclusion after full-text review were recorded. Disagreements concerning suitability for inclusion were resolved by discussion and consensus involving all authors.

Data extraction

Data were extracted between 11 and 13 December 2023, using a standard template to collect key information from all eligible studies: year of publication; country; setting; inclusion and exclusion criteria; sample size, mean age, and sex proportion; methods used to define predominant polarity; prevalence rates of mPP and dPP; and sociodemographic and clinical correlates of mPP versus dPP. Four authors (F.B., C.B., M.G. and L.G.) independently extracted data and blindly cross-checked them for accuracy.

Data analysis

Meta-analyses of mPP and dPP prevalence in bipolar disorder were based on random-effects weighted proportions with 95% confidence intervals using arcsine-based transformation. Considering the expected low consistency of meta-analyses of prevalence rates,Reference Migliavaca, Stein, Colpani, Barker, Ziegelmann and Munn21 subgroup analyses were run to test potential variations in mPP and dPP prevalence rates by the geographical area of included studies. An omnibus test from the random-effects meta-regression was performed to test the overall moderating effects of subgroups. Moreover, in order to deal with a skewed distribution of prevalence rates, we reported the overall median and interquartile range of the mPP and dPP point prevalences for descriptive purposes. Weighted differences in arcsine-transformed proportions (WPDs) were estimated for both overall and subgroup analyses by geographical area.

To compare mPP and dPP for relevant correlates, random-effects meta-analyses were conducted for variables with data available from at least five different studies. P < 0.05 was used as the threshold for statistical significance. We used odds ratios and weighted mean differences (WMDs) with 95% confidence intervals for categorical and continuous variables, respectively. Heterogeneity across studies was evaluated according to standard cut-offs for I2 statistics to measure inconsistency of meta-analyses on correlates.Reference Higgins, Thompson, Deeks and Altman22 Publication bias was assessed using Egger's test for meta-analyses with data available from at least ten studies.Reference Sterne, Egger, Moher, Higgins and Green23 To evaluating the magnitude and precision of the effects (see ‘Grading of the evidence’ section), each WMD was converted into the equivalent effect size (standardised mean difference [SMD]), performing relevant meta-analysis, while each odds ratio was converted into an SMD by dividing the relevant ln(OR) by 1.81.Reference Chinn24 Conventional cut-offs (0.2 small, 0.5 medium, 0.8 large) were used to interpret the magnitude of the effect.Reference Andrade25 Data analyses were performed using Stata statistical software, release 17 (StataCorp LLC, 2021). OpenMeta[Analyst] softwareReference Wallace, Schmid, Lau and Trikalinos26 was used to generate forest plots.

Grading of the evidence

Following a similar approach used in recent meta-analyses,Reference Bartoli, Callovini, Cavaleri, Cioni, Bachi and Calabrese27,Reference Bartoli, Nasti, Palpella, Piacenti, Di Lella and Mauro28 we used GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) items,Reference Schünemann, Higgins, Vist, Glasziou, Akl, Skoetz, Higgins, Thomas, Chandler, Cumpston, Li and Page29 adapted for non-interventional observational studies, to classify the quality of evidence as high, moderate, low or very low for each variable showing a statistically significant estimate (P < 0.05).

First, we assessed the consistency of findings according to the I 2 value. We downgraded by one level the quality of evidence if inconsistency was estimated (I 2 ≥ 50%).

Second, we evaluated the precision of findings by checking the width of the equivalent effect size 95% CI. We downgraded the quality of evidence by one level if (a) the 95% CI width of the equivalent effect size was ≥0.40 for meta-analyses showing small or medium effect sizes, or (b) the 95% lower and upper confidence limits of the equivalent effect size (SMD) were not both ≥0.80 for meta-analyses showing large effect sizes.

In addition, we assessed the risk of publication bias, downgrading the quality of evidence by one level if (a) meta-analyses included fewer than ten studies, or (b) the Egger's test P-value was <0.10 for meta-analyses including at least ten studies.

Finally, we evaluated the magnitude of the effect, upgrading the quality of evidence by one level if the magnitude of the equivalent effect size was large (SMD ≥ 0.80).

Results

Study selection

The systematic search on relevant databases generated 374 records, namely 140 from Embase, 89 from PubMed, 80 from APA PsycInfo and 65 from Ovid Emcare. After deduplication, there were 192 articles left to be screened, including additional studies retrieved from the reference lists of the two reviews.Reference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8,Reference García-Jiménez, Álvarez-Fernández, Aguado-Bailón and Gutiérrez-Rojas14 After screening by titles and abstracts, 70 studies were identified as potentially eligible. Following the final screening based on full texts, 28 studies met the eligibility criteria and were included in the meta-analysis.Reference Baldessarini, Undurraga, Vázquez, Tondo, Salvatore and Ha12,Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15Reference Sentissi, Popovic, Moeglin, Stukalin, Mosheva and Vieta18,Reference Albert, Manchia, Burato, Carpiniello, Di Salvo and Pinna30Reference Wenzel, Althen, Veeh and Reif52 A flowchart with details of screening, the study selection process and reasons for exclusion is presented in Fig. 1.

Fig. 1 Flow diagram of included and excluded studies.

Study characteristics

Studies were published between 2009Reference Mazzarini, Pacchiarotti, Colom, Sani, Kotzalidis and Rosa40,Reference Vieta, Berk, Wang, Colom, Tohen and Baldessarini50 and 2023.Reference Argyropoulos, Christidi, Karavasilis, Bede, Antoniou and Velonakis31 All studies, with the exception of one reported in Spanish,Reference Obando, García, Rodríguez, Palacio, Ontoso and Tamayo43 were written in English. The sample sizes varied between 42Reference Argyropoulos, Christidi, Karavasilis, Bede, Antoniou and Velonakis31 and 788.Reference Vieta, Berk, Wang, Colom, Tohen and Baldessarini50 The majority of studies (k = 16) were conducted in Europe, i.e. six were from Italy,Reference Albert, Manchia, Burato, Carpiniello, Di Salvo and Pinna30,Reference Janiri, Di Nicola, Martinotti and Janiri38Reference Murru, Pacchiarotti, Verdolini, Reinares, Torrent and Geoffroy41,Reference Pacchiarotti, Mazzarini, Kotzalidis, Valentí, Nivoli and Sani45 three from Spain,Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15,Reference Popovic, Torrent, Goikolea, Cruz, Sánchez-Moreno and González-Pinto46,Reference Vidal-Rubio, Balanzá-Martínez, Cuenca, Vila-Francés, Vieta and Romeu49 two from FranceReference Azorin, Adida and Belzeaux32,Reference Murru, Primavera, Oliva, Meloni, Vieta and Carpiniello42 and Germany,Reference Volkert, Zierhut, Schiele, Wenzel, Kopf and Kittel-Schneider51,Reference Wenzel, Althen, Veeh and Reif52 and one each from Belgium,Reference Sentissi, Popovic, Moeglin, Stukalin, Mosheva and Vieta18 FinlandReference Pallaskorpi, Suominen, Rosenström, Mantere, Arvilommi and Valtonen17 and Greece.Reference Argyropoulos, Christidi, Karavasilis, Bede, Antoniou and Velonakis31 Five studies were conducted in Asia: four in IndiaReference Grover, Avasthi, Chakravarty, Dan, Chakraborty and Neogi16,Reference Ghosal, Mallik, Acharya, Dasgupta, Mondal and Pal36,Reference Pal44,Reference Rangappa, Munivenkatappa, Narayanaswamy, Jain and Reddy47 and one in Singapore;Reference Gunasekaran, Teh, Liu, Cetty, Mok and Subramaniam37 and five studies in South America, i.e. three were from BrazilReference Belizario, Junior, Salvini, Lafer and Dias33,Reference Belizario, Silva and Lafer34,Reference Rosa, Andreazza, Kunz, Gomes, Santin and Sanchez-Moreno48 and two from Colombia.Reference Ruiz G, Ospina JP, Vargas, Aguirre Acevedo and López-Jaramillo35,Reference Obando, García, Rodríguez, Palacio, Ontoso and Tamayo43 Two studies were based on data from multiple countries of different geographical areas.Reference Baldessarini, Undurraga, Vázquez, Tondo, Salvatore and Ha12,Reference Vieta, Berk, Wang, Colom, Tohen and Baldessarini50 Study characteristics are reported in Table 1. Some studies were likely to have a partial overlap between included samples, i.e. (a) Belizario et al (2019)Reference Belizario, Junior, Salvini, Lafer and Dias33 and Belizario et al (2018);Reference Belizario, Silva and Lafer34 (b) Fico et al (2022)Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15 and Popovic et al (2014);Reference Popovic, Torrent, Goikolea, Cruz, Sánchez-Moreno and González-Pinto46 and (c) Pacchiarotti et al (2011)Reference Pacchiarotti, Mazzarini, Kotzalidis, Valentí, Nivoli and Sani45 and Mazzarini et al (2009).Reference Mazzarini, Pacchiarotti, Colom, Sani, Kotzalidis and Rosa40 We prioritised data from Belizario et al (2019),Reference Belizario, Junior, Salvini, Lafer and Dias33 Fico et al (2022)Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15 and Pacchiarotti et al (2011),Reference Pacchiarotti, Mazzarini, Kotzalidis, Valentí, Nivoli and Sani45 respectively, as these studies were all based on larger sample sizes. For meta-analyses, we used data from smaller studiesReference Belizario, Silva and Lafer34,Reference Mazzarini, Pacchiarotti, Colom, Sani, Kotzalidis and Rosa40,Reference Popovic, Torrent, Goikolea, Cruz, Sánchez-Moreno and González-Pinto46 only if these were not provided by the main study.

Table 1 Characteristics of included studies

BD-I, bipolar-I disorder; NR, not reported.

Prevalence of hypomanic/manic and depressive predominant polarity in bipolar disorder

Twenty-four studiesReference Baldessarini, Undurraga, Vázquez, Tondo, Salvatore and Ha12,Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15Reference Sentissi, Popovic, Moeglin, Stukalin, Mosheva and Vieta18,Reference Albert, Manchia, Burato, Carpiniello, Di Salvo and Pinna30Reference Azorin, Adida and Belzeaux32,Reference Belizario, Silva and Lafer34Reference Janiri, Simonetti, Piras, Ciullo, Spalletta and Sani39,Reference Murru, Pacchiarotti, Verdolini, Reinares, Torrent and Geoffroy41Reference Pacchiarotti, Mazzarini, Kotzalidis, Valentí, Nivoli and Sani45,Reference Rangappa, Munivenkatappa, Narayanaswamy, Jain and Reddy47Reference Volkert, Zierhut, Schiele, Wenzel, Kopf and Kittel-Schneider51 including 7381 individuals with bipolar disorder were included in the meta-analyses on weighted prevalence of mPP and dPP. We found similar rates of mPP (weighted prevalence = 30.0%, 95% CI: 23.1 to 37.4%; Supplementary Fig. 1 available at https://doi.org/10.1192/bjo.2024.51) and dPP (weighted prevalence = 28.5%, 95% CI: 23.7 to 33.7%; Supplementary Fig. 2) across studies (WPD = 1.6%, 95% CI: −9.6 to 12.9%, P = 0.78; Supplementary Fig. 3). The risk of publication bias was low (Egger's coefficient: 1.60, P = 0.63). However, statistically significant variations were estimated by subgroup analyses (omnibus P < 0.001). In Europe (k = 13; N = 3790), rates of mPP (weighted prevalence = 20.1%, 95% CI: 15.2 to 25.4%) were significantly lower (WPD = −15.0%, 95% CI: −24.3 to −5.7%; p = 0.002) than rates of dPP (weighted prevalence = 33.2%, 95% CI: 25.3 to 41.6%). The opposite trend was estimated for studies conducted in Asia (k = 5; N = 1307): mPP affected more than half of people with bipolar disorder (weighted prevalence = 52.7%, 95% CI: 35.8 to 69.2%), whereas dPP occurred in around a fifth of patients (weighted prevalence = 20.5, 95% CI: 15.6 to 26.0%). The difference was statistically significant (WPD = 33.3%, 95% CI: 11.1 to 55.5%; P = 0.003). A similar trend was observed in studies carried out in South America, although the difference between mPP (weighted prevalence = 42.7%, 95% CI: 28.3 to 57.8%) and dPP (weighted prevalence = 23.7%, 95% CI: 15.1 to 33.4%) was not statistically significant (WPD = 20.8%, 95% CI: −4.8 to 46.3%), possibly because of the limited number of included studies (k = 4) and the small resulting sample size (N = 568). Results are reported in Table 2.

Table 2 Meta-analyses of prevalence rates of hypomanic/manic and depressive predominant polarity in people with bipolar disorder by geographical area

IQR, interquartile range, expressed as (1st quartile to 3rd quartile); k, number of included studies; N, number of study participants; WP, weighted prevalence; WPD, weighted prevalence difference.

Selection of variables

We extracted data for 22 correlates from at least five studies based on unique samples. Twenty-four studiesReference Baldessarini, Undurraga, Vázquez, Tondo, Salvatore and Ha12,Reference Fico, Anmella, Sagué-Villavella, Gomez-Ramiro, Hidalgo-Mazzei and Vieta15Reference Sentissi, Popovic, Moeglin, Stukalin, Mosheva and Vieta18,Reference Albert, Manchia, Burato, Carpiniello, Di Salvo and Pinna30Reference Ghosal, Mallik, Acharya, Dasgupta, Mondal and Pal36,Reference Janiri, Di Nicola, Martinotti and Janiri38Reference Mazzarini, Pacchiarotti, Colom, Sani, Kotzalidis and Rosa40,Reference Obando, García, Rodríguez, Palacio, Ontoso and Tamayo43,Reference Pal44,Reference Popovic, Torrent, Goikolea, Cruz, Sánchez-Moreno and González-Pinto46Reference Wenzel, Althen, Veeh and Reif52 had data suitable for at least one correlate. We did not consider manic and depressive symptoms or the lifetime number of manic/hypomanic and depressive episodes, even if these variables were based on more than five studies, owing to the inherent association with the corresponding predominant polarity. Moreover, we did not consider pharmacological treatments because of the extreme variability across studies in terms of current and lifetime treatments. We distinguished variables included for meta-analyses as ‘variables associated with mPP’, ‘variables associated with dPP’ and ‘variables not associated with any predominant polarity’.

Variables associated with hypomanic/manic predominant polarity

A summary of findings and related details on quality of evidence are reported in Tables 3 and 4, respectively.

Table 3 Factors associated with hypomanic/manic or depressive predominant polarity: summary of findings

k, number of included studies; N, number of study participants; N/A, not applicable; OR, odds ratio; SMD, standardised mean difference; WMD, weighted mean difference.

Table 4 Factors associated with hypomanic/manic or depressive predominant polarity: quality of evidence

↓, downgrade by one level; =, no upgrade/downgrade; ↑, upgrade by one level.

Age

A meta-analysis based on 18 studies including a total of 2827 participants showed that individuals with mPP were younger than those with dPP (WMD = −3.19 years, 95% CI: −5.30 to −1.08 years; P = 0.003; Supplementary Fig. 4). The quality of evidence was moderate, as although the meta-analysis was inconsistent (I 2 = 74.3%), it produced a small but precise estimate (equivalent effect size: SMD = −0.26, 95% CI: −0.43 to −0.08) with a low risk of publication bias (Egger's coefficient: −0.99, P = 0.43).

Gender

Based on a meta-analysis of 19 studies with 3335 total participants, we found that people with mPP were more likely to be male (odds ratio = 1.39, 95% CI: 1.10 to 1.76; P = 0.005; Supplementary Fig. 5). The overall quality of evidence was high, considering the low between-study heterogeneity (I 2 = 45.9%), the precision of findings (equivalent effect size: SMD = 0.18, 95% CI: 0.05 to 0.31) and the low risk of publication bias (Egger's coefficient: −0.28, P = 0.73).

Age at onset

Based on 13 studies including 2494 individuals with bipolar disorder, we estimated that people with mPP had earlier onset of bipolar disorder than people with dPP (WMD = −1.57 years, 95% CI: −2.88 to −0.26 years; P = 0.019; Supplementary Fig. 6). The overall quality of evidence was high, considering the low between-study heterogeneity (I 2 = 42.3%), the precision of findings (equivalent effect size: SMD = −0.15, 95% CI: −0.27 to −0.02) and the low risk of publication bias (Egger's coefficient: 0.44, P = 0.69).

Manic polarity of first episode

We found that people with mPP were more likely to report a first mood episode characterised by manic polarity (k = 8, N = 1557; odds ratio = 13.54, 95% CI: 5.83 to 31.46; P < 0.001; Supplementary Fig. 7). The overall quality of evidence was moderate; despite the inconsistency of findings (I 2 = 84.8%) and the unclear risk of publication bias, the magnitude of the effect and the lower and upper confidence limits (equivalent effect size: SMD = 1.44, 95% CI: 0.97 to 1.90) were large.

Bipolar-I disorder

The meta-analysis (k = 12; N = 1661) showed that people with mPP were more often affected by BD-I than individuals with dPP (odds ratio = 4.82, 95% CI: 2.27 to 10.24; P < 0.001; Supplementary Fig. 8), with a large effect (equivalent effect size: SMD = 0.87, 95% CI: 0.45 to 1.28). The evidence was of moderate quality, given the low precision of findings and the inconsistency (I 2 = 81.8%), despite a low risk of publication bias (Egger's coefficient: 1.08, P = 0.54).

Psychotic features

Based on ten studies including 1970 participants with bipolar disorder, those with mPP were more likely to have psychotic features than those with dPP (odds ratio = 1.56, 95% CI: 1.01 to 2.41; P = 0.047; Supplementary Fig. 9). However, the overall evidence was of low quality, because of the moderate-to-high heterogeneity (I 2 = 66.1%) and imprecision (equivalent effect size: SMD = 0.25, 95% CI: 0.01 to 0.49), regardless of the low risk of publication bias (Egger's coefficient: −0.56, P = 0.71).

Variables associated with depressive predominant polarity

A summary of findings is provided in Table 3, and related details on the quality of evidence are given in Table 4.

History of suicide attempts

Meta-analysis based on ten studies and 1793 subjects showed that people with dPP were more likely to have attempted suicide (odds ratio = 2.09, 95% CI: 1.49 to 2.93; P < 0.001; Supplementary Fig. 10). The quality of evidence was high in terms of consistency (I 2 = 45.2%), precision (equivalent effect size: SMD = 0.41, 95% CI: 0.22 to 0.59) and risk of publication bias (Egger's coefficient: −0.64, P = 0.67).

Depressive polarity of first episode

We found that a depressive polarity of the first mood episode was associated with dPP (k = 9, N = 1655; odds ratio = 12.09, 95% CI: 6.38 to 22.90; P < 0.001; Supplementary Fig. 11). The evidence was of moderate quality, considering the poor consistency across studies (I 2 = 78.3%) and the unclear risk of publication bias, despite the large effect (equivalent effect size: SMD = 1.37, 95% CI: 1.02 to 1.73).

Number of mood episodes

Individuals with dPP had more mood episodes than people with mPP (k = 9; N = 1773; WMD = 0.99 mood episodes; 95% CI: 0.28 to 1.70 mood episodes; P = 0.006; Supplementary Fig. 12). Despite the consistency across studies (I 2 = 0%) and the precision of findings (equivalent effect size: SMD = 0.12, 95% CI: 0.02 to 0.22), the evidence was of moderate quality, being downgraded by one level because of uncertainty about publication bias.

Being in a relationship

Meta-analysis based on six studies and 856 participants showed that people with dPP were more often married or in a relationship than those with mPP (odds ratio = 1.98, 95% CI: 1.22 to 3.22; P = 0.006; Supplementary Fig. 13). However, the quality of evidence was low, owing to the poor precision of findings (equivalent effect size: SMD = 0.38, 95% CI: 0.11 to 0.65) and the unclear risk of publication bias, despite the low between-study heterogeneity (I 2 = 28.9%).

Variables not associated with any predominant polarity

We found no differences between mPP and dPP as regards other variables, including years of education, unemployment, duration of illness, mixed polarity of first episode, rapid cycling course, number of hospital admissions, number of suicide attempts, comorbid alcohol and substance use disorders, and family history of bipolar disorder, any affective disorders or suicide. A summary of these findings is provided in Supplementary Table 1, and relevant forest plots are shown in Supplementary Figs. 14–25.

Discussion

Summary and interpretation of findings

To our knowledge, this is the first systematic review and meta-analysis investigating prevalence rates and possible correlates of mPP and dPP in bipolar disorder. Based on 28 studies, conducted in 12 countries across Europe, Asia and South America, our work provides several important findings.

First, we found no differences in prevalence rates between predominant polarities, as around a third of subjects with bipolar disorder had mPP, and a similar proportion of individuals had dPP. Thus, a predominant polarity, as defined by Colom's criteria,Reference Colom, Vieta, Daban, Pacchiarotti and Sánchez-Moreno11 seems to affect approximately two-thirds of patients with bipolar disorder. Overall rates of both mPP and dPP as estimated in our work appeared higher than those reported in a previous review on this topic, which found that around half of people with bipolar disorder might have a well-defined predominant polarity.Reference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8

Second, rates of mPP and dPP might vary according to different geographical areas. Whereas dPP was more frequent than mPP in European countries, opposite estimates were found in studies conducted in Asia, in which prevalence rates of mPP were almost double those of dPP. This was not surprising, as the clinical trajectory of bipolar disorder might be influenced by genetic, cultural and environmental factors that are likely to vary by country,Reference Rowland and Marwaha53 shaping the expression of manic and depressive symptoms. Moreover, differences in predominant polarity might be explained also by cross-national variations in prevalence rates of BD-I and BD-II,Reference Merikangas and Lamers54 which are associated with mPP and dPP, respectively. Finally, it should be considered that even the heterogeneity of mental healthcare delivery systems worldwide may influence the probability of access to care for patients with bipolar disorder, especially during depressive episodes.Reference Bartoli, Bachi, Calabrese, Cioni, Guzzi and Nasti55,Reference Bartoli, Cavaleri, Nasti, Palpella, Guzzi and Riboldi56 Indeed, fewer than half of people with bipolar disorder receive mental health treatment, particularly in low-income countries, and only a quarter report contacts with the mental health system.Reference Merikangas, Jin, He, Kessler, Lee and Sampson57 However, those with manic episodes and related behavioural abnormalities may be less likely to avoid detection and treatment.

Third, we uncovered several clinically meaningful correlates associated with a distinct predominant polarity. Individuals with mPP were younger, more often male and more likely to be affected by BD-I, as well as being more likely to show psychotic features and have an earlier onset characterised by manic symptoms. These findings were consistent with evidence from a recently published meta-analysis involving participants whose manic predominance was set by definition, i.e. those with unipolar mania, who were again more often males, with younger age at onset and higher rates of psychotic features.Reference Bartoli, Nasti, Palpella, Piacenti, Di Lella and Mauro28 In addition, our findings, showing an association between mPP and BD-I, seem consistent with the natural history of BD-I,Reference Baldessarini, Bolzani, Cruz, Jones, Lai and Lepri58 which is typically characterised by more psychotic features and an earlier onset than BD-II. On the other hand, people with dPP were more likely to have a depressive polarity at onset, a higher number of mood episodes and a history of suicide attempts, and were more often in a relationship than people with mPP. Our findings seem to be supported by a relatively recent body of evidence in the field.Reference McIntyre, Berk, Brietzke, Goldstein, López-Jaramillo and Kessing1,Reference Grande, Berk, Birmaher and Vieta59

A balanced interpretation of our findings needs to consider that for some explored variables, the quality of evidence was low (i.e. psychotic features and being in a relationship) or moderate (i.e. age, polarity of first episode, BD-I and number of mood episodes). This was influenced by several issues, including the imprecision and inconsistency of overall estimates, as well as the uncertain probability of publication bias. Additional research is needed to substantiate our meta-analytic evidence for these variables. Nonetheless, our findings reasonably support the hypothesis that predominant polarity might identify specific subgroups of people with bipolar disorder; in particular, the associations with male gender and earlier bipolar disorder onset in mPP and with higher rates of suicide attempts in dPP were based on evidence of high quality.

Clinical implications

The assessment and definition of predominant polarity, because of its potential as a long-term specifier, may represent a valuable tool in clinical practice to help choose appropriate treatments and predict probable outcomes for individuals with bipolar disorder. In particular, the predominant polarity conceptualisation might represent a useful alternative to the traditional and yet complexReference Kogan, Maj, Rebello, Keeley, Kulygina and Matsumoto60,Reference McIntyre, Alda, Baldessarini, Bauer, Berk and Correll61 distinction between BD-I and BD-II.Reference Colom, Vieta and Suppes9 In view of the existing scientific evidence in this field, the inclusion of predominant polarity in the treatment decision-making process for bipolar disorder has been already hypothesised, with the concept of the polarity index.Reference Colom, Vieta and Suppes9,Reference Carvalho, Quevedo, McIntyre, Soeiro-de-Souza, Fountoulakis and Berk13 This defines the ratio between antimanic and antidepressant properties of single pharmacological and non-pharmacological approaches used for maintenance treatment of bipolar disorder.Reference Popovic, Reinares, Goikolea, Bonnin, Gonzalez-Pinto and Vieta62,Reference Popovic, Reinares, Scott, Nivoli, Murru and Pacchiarotti63 More generally, establishing clinical features associated with mPP or dPP may guide clinicians in the early identification of possible trajectories of bipolar disorder and in the selection of the most appropriate interventions for the prevention of mood relapses. In addition, the conceptualisation of predominant polarity, involving a fine-grained assessment of the behaviour, cognition, emotions and social interactions of individuals with bipolar disorder, might clash with emerging perspectives towards an unified and transdiagnostic view of affective disorders.Reference Norton and Paulus64

Another important clinical implication of this study is related to the strong concordance between the long-term predominant polarity and the polarity of the first mood episode: our meta-analyses showed large effects for the relationships between a manic onset and mPP, as well as between a depressive onset and dPP, ruling out any association between mixed symptoms at onset and subsequent predominant polarity. While stressing the clinical heterogeneity of mixed features possibly occurring in both manic and depressive episodes,Reference Bartoli, Crocamo and Carrà65 our findings make clearer the predictive role of the first mood episode on predominant polarity. This has also been suggested by some pioneering studies in the field,Reference Daban, Colom, Sanchez-Moreno, García-Amador and Vieta66,Reference Turvey, Coryell, Arndt, Solomon, Leon and Endicott67 which showed that affective polarity at onset was associated with the polarity of the following episodes. As the main critical element of the current conceptualisation of predominant polarity involves the large amount of time that elapses between onset of bipolar disorder and the subsequent assessment of mPP, dPP or undefined polarity, across at least three mood episodes,Reference Carvalho, McIntyre, Dimelis, Gonda, Berk and Nunes-Neto8 the first manic or depressive episode might be considered to be a useful clinical proxy for the polarity of subsequent recurrences.

Finally, from a completely different perspective, the definition of potential neurobiological correlates of mPP and dPP might represent an important area for future research. Recent studies have reported, for example, that individuals with predominant polarity – especially those with mPP – may show differences in cortical thickness in several areas of the central nervous system.Reference Argyropoulos, Christidi, Karavasilis, Bede, Antoniou and Velonakis31,Reference Ruiz G, Ospina JP, Vargas, Aguirre Acevedo and López-Jaramillo35 Further evidence highlighted that biomarkers of bipolar disorder may be more influenced by its specific clinical features, e.g. depression and mania, than by the disease itself.Reference Bartoli, Cioni, Cavaleri, Callovini, Crocamo and Misiak68Reference Zhang, Xiao, Wang, Gao, Su and Lu70 Potential neurobiological underpinnings of predominant polarity in bipolar disorder are also a matter for future research.

Limitations

The findings of the current systematic review and meta-analysis should be interpreted with caution, considering some limitations. First, as our work investigated cross-sectional differences between mPP and dPP, we cannot draw any conclusions about causal inference. Second, we need to consider some methodological variability across studies in terms of objectives, sample size, inclusion criteria and methods used to assess clinical variables. For instance, the retrospective nature of data should be considered as a possible source of misclassification of predominant polarity. Third, owing to the observational nature of the included studies, without any predefined protocol, we should consider that the possible effects of unpublished data and the likelihood of selective reporting bias may have at least partially influenced our meta-analytic estimates. Moreover, considering the lack of valid and recommended tools for meta-analyses based on non-intervention and non-randomised studies,Reference Stang71 we did not formally assess the risk of bias of included studies. Although we included only studies with consistent definitions of predominant polarity, the poor representativeness of some studies (e.g. those including only in-patients) and some risk of recall bias (due to the nature of the tested variables) may have affected the results of our meta-analysis. In addition, the clinical course of bipolar disorder may be influenced by the different effectiveness of treatments for preventing relapses; however, insufficient data were available from the included studies for us to explore the role of this confounder on polarity predominance. For example, lithium, the gold-standard treatment for bipolar disorder,Reference Bartoli72 has shown to be more effective in preventing mania than depression,Reference Fountoulakis, Tohen and Zarate73 and, in general, there are fewer evidence-based treatments for bipolar depression than for mania.Reference Ketter, Miller, Dell'Osso, Calabrese, Frye and Citrome74 Similarly, data on other important correlates, such as seasonality,Reference Fico, de Toffol, Anmella, Sagué-Vilavella, Dellink and Verdolini75 affective temperamentsReference Azorin, Adida and Belzeaux32 and comorbid anxiety disorders,Reference Pallaskorpi, Suominen, Rosenström, Mantere, Arvilommi and Valtonen17 were available only from a limited number of studies, suggesting a need for additional research.

Future perspectives

The findings of this systematic review and meta-analysis support the hypothesis that predominant polarity might be a useful specifier of bipolar disorder, identifying subgroups of individuals with different clinical characteristics. High quality of evidence shows an association of mPP with male gender and an earlier onset of bipolar disorder, whereas dPP is more often associated with a history of suicide attempts. Different predominant polarities in bipolar disorder may represent particular targets for more appropriate care programmes and effective approaches to personalised treatment.

Supplementary material

Supplementary material is available online at https://doi.org/10.1192/bjo.2024.51.

Data availability

The data that support the findings of this study are available from the corresponding author (F.B.) upon reasonable request.

Author contributions

Study conception and design: F.B.; review of the scientific literature: F.B. and G.C.; article screening: F.B., C.B., L.G. and M.G.; article eligibility: F.B., C.B., L.G. and M.G.; data extraction: F.B., C.B., L.G. and M.G.; quality check: F.B., C.C. and D.C.; data analysis: F.B., C.C. and G.C.; data interpretation: F.B., D.C. and G.C.; first draft: F.B., D.C. and C.C.; draft revision: C.B., L.G., M.G. and G.C.; figures and tables: F.B., D.C. and C.C.; supplementary files: C.B. and D.C.; references: C.B., L.G. and M.G.; work supervision: F.B. and G.C. All authors made substantial contributions to the conception and design of the work, as well as the acquisition, analysis and interpretation of data; drafted the work or reviewed it for important intellectual content; approved the final version of the manuscript; and were involved in any aspects regarding accuracy and integrity of any part of the work.

Funding

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Declaration of interest

None.

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Figure 0

Fig. 1 Flow diagram of included and excluded studies.

Figure 1

Table 1 Characteristics of included studies

Figure 2

Table 2 Meta-analyses of prevalence rates of hypomanic/manic and depressive predominant polarity in people with bipolar disorder by geographical area

Figure 3

Table 3 Factors associated with hypomanic/manic or depressive predominant polarity: summary of findings

Figure 4

Table 4 Factors associated with hypomanic/manic or depressive predominant polarity: quality of evidence

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