2024; 22(2): 364-369  
Defining “High Recurrence” of Depressive Episodes for Predicting Diagnostic Conversion from Major Depressive Disorder to Bipolar Disorder: A 5-year Retrospective Study
Won Joon Choi1, Young Sup Woo2, Won-Seok Choi2, Jonghun Lee3, Won-Myong Bahk2
1Cheongdamsungmo Psychiatric Clinic, Yesan, Korea
2Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea
3Department of Psychiatry, College of Medicine, Daegu Catholic University, Daegu, Korea
Correspondence to: Won-Myong Bahk
Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea
E-mail: wmbahk@catholic.ac.kr
ORCID: https://orcid.org/0000-0002-0156-2510

Young Sup Woo
Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 10 63-ro, Yeongdeungpo-gu, Seoul 07345, Korea
E-mail: youngwoo@catholic.ac.kr
ORCID: https://orcid.org/0000-0002-0961-838X
Received: February 26, 2024; Revised: March 11, 2024; Accepted: March 12, 2024; Published online: May 31, 2024.
© The Korean College of Neuropsychopharmacology. All rights reserved.

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Objective: This study determined the threshold for recurrent depressive episodes that predicted conversion from major depressive disorder (MDD) to bipolar disorder (BD).
Methods: We retrospectively reviewed the medical records of 296 patients diagnosed with MDD for a minimum of 5 years in two university hospitals. We examined their the Diagnostic and Statistical Manual of Mental Disorders, 5th edition diagnoses and detailed clinical information at the initial admission and yearly assessments after discharge to establish the threshold for recurrent depressive episodes indicating a risk of diagnostic conversion from MDD to BD. Optimal cut-offs were derived using receiver operating characteristic (ROC) curves.
Results: ROC curve analysis revealed that more than four recurrent depressive episodes was indicative of potential diagnostic conversion from MDD to BD (area under the curve, 0.604; sensitivity, 0.353; specificity, 0.855; positive predictive value, 0.421; negative predictive value, 0.816).
Conclusion: These findings suggest that the best predictor of conversion from MDD to BD is more than four recurrent depressive episodes. Our findings have the potential to enhance diagnostic accuracy and treatment efficiency. To validate our results, longitudinal prospective studies are necessary.
Keywords: Major depressive disorder; Recurrence; Bipolar disorder; Diagnostic conversion
INTRODUCTION

Bipolar disorder (BD) encompasses a spectrum of mood episodes, including mania, hypomania, and depressive episodes, along with cognitive and social function impairment. However, the clinical diagnosis of BD remains challenging. BD often begins with depressive episodes, leading to the initiation of treatment for major depressive disorder (MDD), and it is common for depressed individuals to be diagnosed and treated for MDD mistakenly; it may take approximately 10 years to receive proper treatment for BD after the onset of initial mood symptoms [1] and up to 8 years for a diagnosis of BD to be established [2,3]. Approximately one-third of individuals initially diagnosed with MDD experience subsequent changes in their psychiatric diagnoses [4,5]. A significant proportion of these patients undergo diagnostic conversion to BD, and 20−60% of patients receiving treatment for BD were previously diagnosed with MDD [6,7]. Misdiagnoses and delays in diagnosis and treatment contribute to increased morbidity and mortality, poor treatment outcomes, and progression to chronic illness and neurodegeneration [8-11]. Therefore, predicting diagnostic conversion from MDD to BD is important but remains challenging. Known clinical predictors include brief major depressive episodes (MDEs), a family history of BD in a first-degree relative, hyperthymic personality, atypical or mixed depressive features, psychotic symptoms, early age at onset, postpartum depression, psychomotor retardation, and treatment resistance [12,13].

Recurrent MDEs is an established predictor of the transition to BD [14]. In a large prospective study, patients with recurrent MDEs had a significantly higher risk of conversion from MDD to BD than patients with a single depressive episode [15]. However, there has been limited research to establish the number of recurrent MDEs that best predicts the transition to BD. Consequently, there is insufficient evidence to establish a consensus regarding the number of MDEs that predict BD conversion. Accordingly, studies differ in their definition of recurrent MDEs [16]. Benazzi [14] and Kessing et al. [17] considered a cutoff of more than four MDEs, while Ghaemi et al. [12] suggested the presence of more than three MDEs was a diagnostic criterion for bipolar spectrum disorders. Therefore, while different studies use different criteria to predict diagnostic conversion, there is insufficient research on this topic. Hence, in this study, we investigate the number of MDEs that best predicts the transition from MDD to BD by conducting a retrospective review of medical records of patients admitted to two university hospitals over 5 years.

METHODS

This study focused on patients who were admitted to the Departments of Psychiatry of Yeouido St. Mary’s Hospital and Daegu Catholic University Medical Center for inpatient treatment between 1 January 2010 and 31 December 2016, with a primary diagnosis of MDD based on the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) diagnostic criteria. Patients for whom a minimum of 5 years had elapsed since their initial admission were enrolled retrospectively, and their medical records were examined to assess their sociodemographic characteristics at the time of admission and the number of MDEs preceding the index admission. Furthermore, we assessed whether the diagnosis of MDD was maintained or converted to BD ≤ 5 years after admission. Patients with inadequate data or those diagnosed with severe physical conditions, mood disorders attributed to general medical conditions, or psychiatric disorders other than BD were excluded from the study.

The diagnosis of BD was based on the DSM-5 diagnostic criteria. Changes in psychiatric diagnoses were initially reviewed by two board-certified psychiatrists (YSW and JHL), and the final diagnosis was confirmed following reevaluation by two additional board-certified psychiatrists (WSC and WMB). If the diagnosis in the medical records was based on DSM-IV, it was reevaluated according to the diagnostic criteria of DSM-5. The enrolled patients were divided into diagnostic maintenance and diagnostic conversion groups. Socio-demographic characteristics and the number of previous MDEs were compared between these groups. For statistical comparisons between the two groups, Fisher’s exact test or the chi-square test was used for categorical variables, and the independent ttest or Mann–Whitney Utest was applied for continuous variables. To investigate conversion to BD based on the number of MDEs, receiver operating characteristic (ROC) curve analysis was conducted to determine sensitivity and specificity, and a cutoff total number of MDEs that predicts conversion to BD was established using the Youden index. Different cutoff values were compared by drawing graphs of the number of recurrences and calculating area under the curve (AUC) values. A two-tailed significance level of p < 0.05 was considered to indicate statistical significance.

This study was approved by the institutional review board of Yeouido St. Mary’s Hospital in Seoul, Korea (SC16RIMI0099), and it was conducted according to the principles of the Declaration of Helsinki. The institutional review board waived the requirement for informed consent because this study was a retrospective chart review.

RESULTS

Patient Demographic Characteristics

A total of 643 patients with MDD as the primary diagnosis received inpatient treatment. Of these patients, 296 met the inclusion criteria for the study. Table 1 summarizes the patients’ demographic characteristics. Of the included patients, 63 (23.0%) experienced conversion to BD. There were significant differences between the diagnostic conversion and maintenance groups in terms of the mean age at admission (43.2 ± 15.2 vs. 57.2 ± 15.3 years; p < 0.001) and mean age at onset (36.2 ± 14.8 vs. 50.0 ± 15.7 years; p < 0.001). The total number of MDEs also differed significantly (p = 0.015) between the diagnostic conversion (2.6 ± 2.9) and maintenance (1.6 ± 2.6) groups (Table 1). Moreover, in the diagnostic conversion group, the rates of family history of BD (38.2% vs. 10.1%; p < 0.001), early onset (onset before 25 years old; 41.2% vs. 7.9%; p < 0.001), and treatment resistance (did not respond adequately to more than three antidepressant treatments; 50.0% vs. 9.6%; p < 0.001) were significantly higher compared to the diagnostic maintenance group.

Validity Analysis

Sensitivity and specificity

Sensitivity and specificity were calculated based on the total number of MDEs (Table 2). When the cutoff value was set at more than two episodes, the sensitivity was 0.500 (95% confidence interval [CI], 0.376−0.624), specificity was 0.689 (95% CI, 0.624−0.748), positive predictive value (PPV) was 0.324 (95% CI, 0.261−0.394), and negative predictive value (NPV) was 0.822 (95% CI, 0.781−0.856). For a cutoff value of more than three episodes, the sensitivity, specificity, PPV, and NPV were 0.382 (95% CI, 0.267−0.508), 0.811 (95% CI, 0.754−0.860), 0.377 (95% CI, 0.288−0.476), and 0.815 (95% CI, 0.783−0.843), respectively. With a cutoff value of more than four episodes, the respective values were 0.353 (95% CI, 0.241−0.478), 0.855 (95% CI, 0.803−0.898), 0.421 (95% CI, 0.317−0.533), and 0.816 (95% CI, 0.786−0.842). When the cutoff value was more than five episodes, the respective values were 0.191 (95% CI, 0.106−0.305), 0.912 (95% CI, 0.868−0.946), 0.394 (95% CI, 0.255−0.553), and 0.791 (95% CI, 0.770−0.810). As the cutoff value increased, the sensitivity decreased, while the specificity and PPV increased.

Prediction of Diagnostic Conversion to Bipolar Disorder and Optimal Cutoff Value for the Number of Major Depressive Episodes

To evaluate the suitability of the number of MDEs for predicting diagnostic conversion to BD, ROC curve analysis was conducted (Fig. 1). The ROC curve should be in the upper-left area relative to the baseline diagonal for the number of MDEs to be considered a useful diagnostic tool. In this study, the ROC curve was in the upper-left area relative to the baseline diagonal. An AUC value of 1, representing the entire AUC, signifies perfect diagnostic performance. In this study, the highest AUC value was 0.604 (95% CI, 0.546−0.660), with a Youden’s index of 0.208 when the cutoff was set at more than four MDEs (Table 2).

DISCUSSION

This study compared the characteristics of patients with MDD who either maintained their diagnosis or converted to BD over a 5-year period starting from the initial hospitalization. The study also analyzed the total number of MDEs that predicts diagnostic conversion. We retrospectively examined the medical records of patients diagnosed with MDD who were admitted to two university hospitals and tracked for a minimum of 5 years. The BD conversion rate over 5 years was found to be 23.0%. In a meta-analysis of the conversion rate and predictors of conversion from MDD to BD [18], the yearly rate of conversion to BD was 3.9% in the first year after study entry, and 3.1% in years 1−2, 1.0% in years 2−5, and 0.8% in years 5−10. The cumulative risk of conversion for 5 years was 9.4%. The conversion rate in our study was higher than that reported in the meta-analysis. This difference may be attributed to the smaller sample size and particular characteristics of the sample in our study, which focused exclusively on hospitalized patients. Our sample might have included a higher proportion of severely ill patients compared to the studies included in the meta-analysis by Kessing et al. [18], which encompassed studies from community samples, outpatient settings, and inpatient settings. Given that the severity of depression is a significant predictor of diagnostic conversion from MDD to BD [18], our study might be expected to have a higher diagnostic conversion rate compared to previous studies.

The ROC curve analysis revealed that a cutoff value exceeding four episodes gave the highest AUC value of 0.604 and highest Youden index of 0.208. Because AUC values can be classified as non-informative (AUC = 0.5), less accurate (0.5 < AUC < 0.7), moderately accurate (0.7 < AUC < 0.9), very accurate (0.9 < AUC < 1), or perfect (AUC = 1) [19], the AUC value in this study indicates that accurately predicting the conversion from MDD to BD based solely on the frequency of MDEs is challenging.

Although Ghaemi et al. [20] proposed that more than three MDEs is associated with bipolarity in the definition of bipolar spectrum disorder, and many researchers have suggested that ‘highly recurrent’ MDEs are associated with the existence of a bipolar diathesis, little research has focused on the number of MDEs that best predicts conversion from MDD to BD. However, in studies comparing the clinical characteristics of patients with MDD and BD, the frequency of recurrent MDEs has frequently been cited as a distinguishing factor, although the definition of highly recurrent MDEs has varied among researchers.

For example, Benazzi [21] compared the clinical characteristics of patients with MDD and bipolar II disorder (BD-II). The percentage of patients with more than three recurrent MDEs was significantly higher in the BD-II patient group (79%) than in the MDD group (60%), suggesting that more than three MDEs is indicative of BD rather than MDD. In a study of inpatients with MDD, Shabani et al. [22] found that recurrent depression, defined as more than three MDEs, significantly predicted bipolarity. Moreover, Takeshima and Oka [23] reported that more than three MDEs predicted a soft bipolarity diagnosis (BD-II or BD not otherwise specified), and Mazzarini et al. [16] reported that their high recurrence MDD group (more than MDEs) differed from a low recurrence group (up to two MDEs) for bipolar/mixed features.

However, our results indicate that ‘highly recurrent MDEs’ associated with bipolar diathesis could be defined as more than four previous MDEs. This result is in line with a few previous studies. In a study of 151 patients with MDD and 226 with BD-II, Akiskal and Benazzi [24] found that more than four MDEs occurred significantly more often in the type II BD group (81.4%) compared to the MDD group (62.2%). Benazzi [14] studied 89 patients with MDD and 115 with BD-II, and found that highly recurrent (> 4 MDEs) depression was associated with bipolarity. We investigated the number of previous MDEs in patients diagnosed with BD during the follow-up period among those originally diagnosed with MDD. Therefore, direct comparison with previous studies exploring the association between the number of previous MDEs and bipolar diathesis is challenging due to the varied methodologies. It is important to interpret the findings with caution considering the differences among studies in the age at onset of the subjects, diagnoses of BD (e.g., BD-I, BD-II, BD not otherwise specified, and bipolar spectrum disorder), and clinical characteristics indicative of bipolar diathesis. Moreover, the AUC value of 0.604 observed in this study suggests that predicting the transition from MDD to BD solely based on the number of MDEs is challenging. Therefore, to assess bipolar diathesis in individual patients, it is necessary to comprehensively consider other characteristics and variables indicative of bipolarity.

This study had several limitations. First, it enrolled patients admitted to only two university hospitals, and the sample size was small. Second, the study relied on a retrospective review of computerized medical records, and the lack of an objective diagnostic tool raises concerns about the validity of the diagnoses. Third, as this study relied on a retrospective examination of medical records, the possibility of recall error with respect to self-reported history of mania or hypomania, the frequency of depressive episodes, and other diverse clinical characteristics must be acknowledged. Fourth, since information about medication was not obtained, we could not consider the impact of the type and dosage of medications used during the study period on the course of the illness. Fifth, we used 5-year follow-up data; therefore, it is important to note that cases with subsequent conversion from MDD to BD cannot be ruled out. In addition, investigating the rate of patients switching from MDD to BD annually could have provided additional information, but this was not investigated in this study. Finally, we did not account for other clinical variables that could influence the transition to BD. Furthermore, the impact of commonly accompanying psychiatric comorbidities in BD was not examined, thus their influence remains indeterminate. Despite these limitations, this study investigated the frequency of recurrent MDEs among inpatients, predicted diagnostic conversion to BD based on the number of MDEs, and identified the optimal cutoff number of recurrences for diagnosis for the first time.

This study investigated the number of recurrent MDEs in patients with a history of MDD but no prior diagnosis of BD, and determined the optimal number of MDEs for predicting diagnostic conversion to BD from MDD. The ROC curve analysis indicated that more than four MDEs was the most accurate predictor of BD. This finding may enhance the accuracy of diagnosis and promote efficacious treatment. Given the current lack of sufficient clinical approaches and research on the outcomes of these patients, future studies must delve deeper into this population for a better understanding of clinical strategies and treatment outcomes.

Funding

None.

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Author Contributions

Conceptualization: Won Joon Choi, Young Sup Woo. Data acquisition: Won Joon Choi, Won-Seok Choi, Jonghun Lee, Formal analysis: Won Joon Choi, Jonghun Lee. Funding: Won-Myong Bahk. Supervision: Won-Myong Bahk. Writing—original draft: Won Joon Choi. Writing—review & editing: Won Joon Choi, Young Sup Woo, Won-Myong Bahk.

Figures
Fig. 1. Receiver operating characteristic curves for the numbers of depressive episodes.
Tables

Characteristics of the evaluable patients at the index episode

Variables Total (n = 296) Unipolar group (n = 228) Diagnostic conversion group (n = 68) pvalue
Age (yr) 54.0 ± 18.4 57.2 ± 15.3 43.2 ± 15.2 < 0.001
Sex (female) 225 (76.0) 177 (77.6) 48 (70.6) 0.233
Married 202 (68.2) 160 (70.2) 42 (61.8) 0.191
Age at onset (yr) 46.8 ± 16.5 50.0 ± 15.7 36.2 ± 14.8 < 0.001
Total number of MDEs 1.9 ± 2.7 1.6 ± 2.6 2.6 ± 2.9 0.015
Family history of BD 49 (16.6) 23 (10.1) 26 (38.2) < 0.001
Early onset (< age 25 yr) 46 (15.5) 18 (7.9) 28 (41.2) < 0.001
History of treatment resistance (> 3 ADs) 56 (18.9) 22 (9.6) 34 (50.0) < 0.001

Values are presented as mean ± standard deviation or number (%).

MDEs, major depressive episodes; BD, bipolar disorder; AD, antidepressants.

Criterion values and coordinates of the receiver operating characteristic curve

Total number of MDEs AUC Sensitivity Specificity PPV NPV Youden index (j)
1 or more 0.500 (0.442−0.558) 1 (0.947−1.000) 0 (0.000−0.016) 0.230 (0.230−0.230) 0.000
> 1 0.575 (0.517−0.632) 0.765 (0.646−0.859) 0.386 (0.322−0.453) 0.271 (0.239−0.305) 0.846 (0.776−0.900) 0.151
> 2 0.594 (0.536−0.651) 0.500 (0.376−0.624) 0.689 (0.624−0.748) 0.324 (0.261−0.394) 0.822 (0.781−0.856) 0.189
> 3 0.597 (0.539−0.653) 0.382 (0.267−0.508) 0.811 (0.754−0.860) 0.377 (0.288−0.476) 0.815 (0.783−0.843) 0.193
> 4 0.604 (0.546−0.660) 0.353 (0.241−0.478) 0.855 (0.803−0.898) 0.421 (0.317−0.533) 0.816 (0.786−0.842) 0.208
> 5 0.552 (0.493−0.609) 0.191 (0.106−0.305) 0.912 (0.868−0.946) 0.394 (0.255−0.553) 0.791 (0.770−0.810) 0.103
> 6 0.516 (0.458−0.575) 0.103 (0.042−0.201) 0.930 (0.889−0.960) 0.305 (0.158−0.505) 0.776 (0.761−0.791) 0.033
> 7 0.513 (0.464−0.593) 0.088 (0.033−0.182) 0.939 (0.899−0.966) 0.300 (0.146−0.518) 0.775 (0.761−0.789) 0.027
> 10 0.504 (0.445−0.562) 0.029 (0.004−0.102) 0.978 (0.950−0.993) 0.286 (0.074−0.669) 0.771 (0.763−0.779) 0.007

Values are presented as number (95% confidence interval).

MDEs, major depressive episodes; AUC, area under the curve; PPV, positive predictive value; NPV, negative predictive value.

References
  1. Goldberg JF, Ernst CL. Features associated with the delayed initiation of mood stabilizers at illness onset in bipolar disorder. J Clin Psychiatry 2002;63:985-991.
    Pubmed CrossRef
  2. Baldessarini RJ, Tondo L, Hennen J, Floris G. Latency and episodes before treatment: response to lithium maintenance in bipolar I and II disorders. Bipolar Disord 1999;1:91-97.
    Pubmed CrossRef
  3. Lish JD, Dime-Meenan S, Whybrow PC, Price RA, Hirschfeld RM. The National Depressive and Manic-depressive Association (DMDA) survey of bipolar members. J Affect Disord 1994;31:281-294.
    Pubmed CrossRef
  4. Kessing LV. Diagnostic stability in depressive disorder as according to ICD-10 in clinical practice. Psychopathology 2005;38:32-37.
    Pubmed CrossRef
  5. Kim W, Woo YS, Chae JH, Bahk WM. The diagnostic stability of DSM-IV diagnoses: an examination of major depressive disorder, bipolar I disorder, and schizophrenia in Korean patients. Clin Psychopharmacol Neurosci 2011;9:117-121.
    Pubmed KoreaMed CrossRef
  6. Ghaemi SN, Sachs GS, Chiou AM, Pandurangi AK, Goodwin K. Is bipolar disorder still underdiagnosed? Are antidepres-sants overutilized? J Affect Disord 1992;52:135-144.
    Pubmed CrossRef
  7. Hirschfeld RM, Lewis L, Vornik LA. Perceptions and impact of bipolar disorder: how far have we really come? Results of the national depressive and manic-depressive association 2000 survey of individuals with bipolar disorder. J Clin Psychiatry 2003;64:161-174.
    Pubmed CrossRef
  8. Dunner DL. Clinical consequences of under-recognized bipolar spectrum disorder. Bipolar Disord 2003;5:456-463.
    Pubmed CrossRef
  9. Chang WH, Su CC, Chen KC, Hsiao YY, Chen PS, Yang YK. Which severe mental illnesses most increase the risk of developing dementia? Comparing the risk of dementia in patients with schizophrenia, major depressive disorder and bipolar disorder. Clin Psychopharmacol Neurosci 2023;21:478-487.
    Pubmed KoreaMed CrossRef
  10. Jeong JH, Bahk WM, Woo YS, Yoon BH, Lee JG, Kim W, et al. Korean medication algorithm project for bipolar disorder 2022: comparisons with other treatment guidelines. Clin Psychopharmacol Neurosci 2023;21:32-48.
    Pubmed KoreaMed CrossRef
  11. Woo YS, Bahk WM, Jeong JH, Lee JG, Kim W, Sohn I, et al. Korean medication algorithm project for bipolar disorder 2022, fifth revision: an executive summary. Clin Psychopharmacol Neurosci 2022;20:747-761.
    Pubmed KoreaMed CrossRef
  12. Ghaemi SN, Ko JY, Goodwin FK. "Cade's disease" and beyond: misdiagnosis, antidepressant use, and a proposed definition for bipolar spectrum disorder. Can J Psychiatry 2002;47:125-134.
    Pubmed CrossRef
  13. Vieta E, Salagre E, Grande I, Carvalho AF, Fernandes BS, Berk M, et al. Early intervention in bipolar disorder. Am J Psychiatry 2018;175:411-426.
    Pubmed CrossRef
  14. Benazzi F. Highly recurrent unipolar may be related to bipolar II. Compr Psychiatry 2002;43:263-268.
    Pubmed CrossRef
  15. Baryshnikov I, Sund R, Marttunen M, Svirskis T, Partonen T, Pirkola S, et al. Diagnostic conversion from unipolar depression to bipolar disorder, schizophrenia, or schizoaffective disorder: a nationwide prospective 15-year register study on 43 495 inpatients. Bipolar Disord 2020;22:582-592.
    Pubmed CrossRef
  16. Mazzarini L, Kotzalidis GD, Piacentino D, Rizzato S, Angst J, Azorin JM, et al. Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study. J Affect Disord 2018;229:164-170.
    Pubmed CrossRef
  17. Kessing LV, Andersen PK, Mortensen PB, Bolwig TG. Recurrence in affective disorder. I. Case register study. Br J Psychiatry 1998;172:23-28.
    Pubmed CrossRef
  18. Kessing LV, Willer I, Andersen PK, Bukh JD. Rate and predictors of conversion from unipolar to bipolar disorder: a systematic review and meta-analysis. Bipolar Disord 2017;19:324-335.
    Pubmed CrossRef
  19. Greiner M, Pfeiffer D, Smith RD. Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Prev Vet Med 2000;45:23-41.
    Pubmed CrossRef
  20. Ghaemi SN, Ko JY, Goodwin FK. The bipolar spectrum and the antidepressant view of the world. J Psychiatr Pract 2001;7:287-297.
    Pubmed CrossRef
  21. Benazzi F. Is 4 days the minimum duration of hypomania in bipolar II disorder? Eur Arch Psychiatry Clin Neurosci 2001;251:32-34.
    Pubmed CrossRef
  22. Shabani A, Zolfigol F, Akbari M. Brief major depressive episode as an essential predictor of the Bipolar Spectrum Disorder. J Res Med Sci 2009;14:29-35.
  23. Takeshima M, Oka T. A comprehensive analysis of features that suggest bipolarity in patients with a major depressive episode: which is the best combination to predict soft bipolarity diagnosis? J Affect Disord 2013;147:150-155.
    Pubmed CrossRef
  24. Akiskal HS, Benazzi F. Family history validation of the bipolar nature of depressive mixed states. J Affect Disord 2003;73:113-122.
    Pubmed CrossRef


This Article

Close ✕


Cited By Articles
  • CrossRef (0)
  • Scopus (0)
  • Download (54)

Author ORCID Information

Services
Social Network Service

e-submission

Archives