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Keywords:

  • bipolar disorder;
  • naturalistic study;
  • treatment;
  • predominant polarity;
  • polarity index

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

Objective

Predominant polarity (PP) is an important variable in maintenance treatment of bipolar disorder (BD). This study aimed at determining the role of polarity index (PI), a metric indicating antimanic versus antidepressive prophylactic potential of drugs, in clinical decision-making.

Method

Two hundred and fifty-seven of 604 (43%) of patients with BD-I or II fulfilled criteria for manic (MPP) or depressive PP (DPP). The PI, representing the ratio of number needed to treat (NNT) for depression prevention to NNT for mania prevention, was calculated for patients' current treatment. MPP and DPP groups were compared regarding sociodemographic, clinical and therapeutic characteristics.

Results

One hundred and forty-three patients (55.6%) fulfilled criteria for DPP and 114 (44.4%) for MPP. Total PI, Antipsychotics' PI, and mood stabilizers PI were higher, indicating a stronger antimanic action, in MPP. MPP presented higher prevalence of BD-I, male gender, younger age, age at onset and at first hospitalization, more hospitalizations, primary substance misuse, and psychotic symptoms. DP correlated with BD-II, depressive onset, primary life events, melancholia, and suicide attempts.

Conclusion

The results confirm the usefulness of the PI. In this large sample, clinical differences among these groups justify differential treatment approach. The PI appears to be a useful operationalization of what clinicians do for maintenance therapy in BD.

Significant outcomes
  • Important clinical differences between predominantly manic and predominantly depressed patients justify the need for differential treatment.
  • Polarity index, indicating antimanic versus antidepressive prophylactic potential of drugs, was applied to real-world setting. Treatments prescribed to predominantly manic patients had a higher total polarity index, as well as polarity index of mood stabilizers and antipsychotics separately.
Limitations
  • Tertiary-center setting.
  • Issues related to polarity index itself, since it derives from clinical trials data.

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

Bipolar disorder is a lifelong, potentially treatable psychiatric disorder with substantial morbidity and mortality [1].

Relapse rates, even in treated patients and after a first lifetime episode, range from 40 to 60%, with nearly one-half of patients experiencing a second mood episode within a year of recovery [2, 3].

There are a number of effective maintenance treatments for bipolar disorder [4, 5]. Inadequate treatment results in increased rates of relapse, whereas multiple episodes may create utter vulnerability to subsequent episodes and reduce the response to therapy [6], impact patients' psychosocial functioning [7, 8], and increase morbidity and mortality [9].

Emerging evidence suggests that the polarity of episodes over the course of bipolar disorder as well as the polarity of initial or index episode may be among the strongest predictors of recurrence to a specific episode [10, 11]. Around one-half of patients were reported to present predominant polarity [12, 13], and various studies have detected clinical differences between predominantly manic and predominantly depressed patients [7, 12, 14, 15].

Thus, predominant polarity (PP), defined as at least twice as many episodes of one pole of the disorder over the other [12], should be taken into account when implementing maintenance therapy of bipolar disorder. To that end, our group has recently developed the polarity index, a numeric expression of the efficacy profile of a given drug obtained from number needed to treat (NNT) for prevention of depressive episodes and NNT for mania prevention ratio [13]. Drugs with a polarity index superior to 1 have stronger antimanic versus antidepressant prophylactic properties, while those with polarity index inferior to 1 are more effective for preventing depressive episodes than the manic ones. Drugs with the polarity index of 1 may have a similar antimanic and antidepressive potential. The polarity index for the drugs used in maintenance therapy for bipolar disorder, a measure of how much antidepressant versus antimanic a drug is, resulted in 12.09 for risperidone, 4.38 for aripiprazole, 3.91 for ziprasidone, 2.98 for olanzapine, 1.39 for lithium, 1.14 for quetiapine, and 0.40 for lamotrigine. Polarity index values of valproate (0.49) and oxcarbazepine (0.62) may not be reliable due to the failure of their maintenance trials and therefore were not accounted for in the current paper. On these grounds, we have calculated mean polarity index for current pharmacological treatment of patients enrolled in Bipolar Disorders Program of the Hospital Clinic and University of Barcelona who present PP. Given that our program delivers evidence-based treatment for patients with bipolar disorder in the context of a specialized setting [16-18], we were willing to test whether clinicians were actually applying the concept of polarity index (PI) to their patients. Theoretically, patients with manic predominant polarity (MPP) would be receiving treatments with higher PI than patients with depressive predominant polarity (DPP). As combination drug regimens are ubiquitous in clinical practice [19, 20], polarity index was calculated as a mean of polarity index of all the prescribed drugs in each patient.

Aims of the study

The aim of this study was to apply polarity index to real-world setting. Secondary aim of this naturalistic study was to ally polarity index to assess eventual differences between predominantly manic and depressed patients, with a special focus on their pharmacological treatment.

Material and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

Depressive predominant polarity was defined as at least two-thirds of a patient's past episodes fulfilling DSM-IV criteria for major depressive episode.

Manic or hypomanic predominant polarity was defined as at least two-thirds of past episodes fulfilling DSM-IV criteria for manic or hypomanic episodes [12]. Mixed episodes were counted for as well but were not considered as a part of depressive polarity or manic polarity. The patients who did not meet criteria for either PP were excluded from the analysis.

Polarity index, an innovative metric indicating antimanic and antidepressive prophylactic potential of drugs, was retrieved by calculating NNT for prevention of depression and NNT for prevention of mania ratio[13, 21], as emerging from the results of randomized placebo-controlled trials (Table 1). Number needed to treats were calculated as weighted mean from the results of all published studies that satisfied the following inclusion criteria: randomized and double-blind studies, with a minimal duration of 24 weeks, assessing effectiveness of a mood stabilizer or an antipsychotic drug alone or in combination with a mood stabilizing agent versus a placebo comparator as maintenance treatment in patients affected by bipolar disorder type I or II and aged ≥18 [21].The proportions used to calculate the NNTs are available in a prior publication by our group [21], which will permit the critical reader to interpret more adequately the NNTs. In the interest of precision, although NNTs are usually shown as whole numbers, we have maintained the fractional portions of NNT and have not rounded upwards to the next whole number when calculating the polarity index. A polarity index of 1 indicates equal efficacy of a drug in prevention of manic and depressive episodes. Drugs with a polarity index superior to 1 may have stronger antimanic versus antidepressant prophylactic properties, while those with polarity index inferior to 1 are more effective for preventing depressive episodes than the manic ones.

Table 1. Number needed to treat for prevention of manic and depressive episodes and polarity index of antipsychotics in maintenance treatment of bipolar disorder (modified from Popovic et al., [13])
 NNT ManiaNNT DepressionNNT Any episodePolarity index
  1. LAI, Long-acting injection.

Aripiprazole [22, 23]8.8138.556.64.38
Olanzapine [2, 24, 25]4.7143.52.98
Quetiapine [9, 26, 27]3.542.81.14
Risperidone LAI [25, 28, 29]4.453.24.512.09
Ziprasidone [30]14.155.17.83.91
Lamotrigine [31, 32]50.420.211.60.4
Lithium [27, 31-34]4.46.13.51.39

Polarity index was calculated for current treatment of each patient, independently from the prescribed dosage. When patients received more than one pharmacological treatment polarity index was calculated as mean of all the prescribed treatments; for example, polarity index of patient treated with lithium and lamotrigine is calculated as following:

  • display math

Polarity index of 1.13 suggests a balanced, slightly more antimanic than antidepressive profile of the drug regimen.

Subsequently, the mean polarity index for each group was calculated, and the groups were compared as to the mean polarity index, as well as sociodemographic, clinical, and therapeutic characteristics.

Study sample

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

The study sample is composed of 604 consecutive patients enrolled in the systematic prospective naturalistic follow-up study of the Bipolar Disorders Program of the Hospital Clinic and University of Barcelona, a tertiary center providing integrated care for patients from a specific catchment area as well as difficult-to-treat bipolar patients derived from all over Spain, ongoing from 1994 up to date, as already described elsewhere [12]. The systematic prospective follow-up was approved by the Ethical and Research Committee of the Hospital University Clinic.

Patients' clinical and sociodemographic data were systematically collected on bimonthly bases. Eligibility criteria were represented by age ≥18, fulfilling DSM-IV-TR criteria for bipolar I or II disorder and providing written informed consent.

Data collection

Psychiatric diagnoses were formulated by senior psychiatrists according to DSM-IV-TR criteria and confirmed by Structured Clinical Interview for DSM-III-R-axis I (SCID-I) and axis II-SCID-I and SCID-II [36]. Episodes were prospectively assessed through DSM-IV check list for mania, hypomania, mixed episodes, or depression. Clinical variables, such as number and polarity of previous episodes, number of hospitalizations, age at onset, age of first hospitalization, polarity of first episode, history of psychosis and suicidal behavior, were obtained from the structured interviews with patients and their relatives. Several more variables were specifically assessed, namely demographic data, medical and psychiatric comorbidities, and psychiatric history of first-degree relatives, seasonality, and rapid cycling (according to DSM-IV criteria), while information regarding social and occupational functioning and presence of life events related to illness onset were assessed by the means of the Holmes and Rahe inventory [37].

Patients were divided into two groups on the basis of the type of PP: DPP and MPP. The two groups were compared regarding clinical and sociodemographic variables as well as regarding polarity index, which was calculated for current pharmacological treatment of each patient.

Statistical analyses

Descriptive analyses were utilized for the definition of the frequencies. Continuous variables were compared by Student's t-tests, and anova and categorical variables by Pearson's chi-square with Yates' correction and Fisher's exact test for the comparison of categorical data (α value, two-tailed). Analysis of covariance (ancova), with age included as covariate, and BD subtype and gender as cofactors, was used to examine the role of potential confounding factors on between-group differences in polarity index of drugs. Univariant analysis was performed to see the effect of current antidepressant prescription on PP and the polarity index. Mean differences in quantitative variables with a non-normal distribution were assessed by Mann–Whitney U-test for independent variables. Given the exploratory nature of our study, we did not apply corrections for multiple comparisons, and alpha level was set at the 0.05 level (two-tailed). Statistical analyses were performed using the Statistical Package for Social Sciences (spss, 18.0 version for Windows, spss Inc., Chicago, IL, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

Three hundred forty-seven patients (57.45%) of the first consecutive 604 patients screened were excluded from the analyses as they did not present a specific PP according to the definition by Colom et al. [12].The mean duration of follow-up for our sample was 10.4 years (SD = 4.97). Two hundred fifty-seven patients (n = 257, 52.55%) fulfilled the inclusion criteria. One hundred forty-three patients (n = 143, 55.6%) were classified as depressive polarity, while one hundred fourteen (n = 114, 44.4%) patients fulfilled criteria for manic polarity.

Demographic characteristics, global social functioning variables, and clinical features are shown in Table 2. Regarding demographic and global social functioning variables, MPP and DPP groups presented significant difference concerning gender, where male patients were more likely to have MPP, as well as younger age in the MPP group. As to the distinguishing clinical features, the MPP group presented significantly with higher prevalence of bipolar disorder I diagnosis, substance use prior to the illness onset, and more psychotic symptoms (lifetime and at onset) than the DPP group. In contrast, depressive polarity group was strongly associated with bipolar II diagnosis, depressive onset, presence of life events preceding first episode, the presence of melancholia, and suicide attempts rate.

Table 2. Demographic and clinical characteristics of the study sample
 Manic polarity n (%)/Mean (SD)Depressive polarity n (%)/Mean (SD)χ²/ t/ U P
  1. a

    P < 0.05.

Gender  11.5910.001a
Male69/114 (60.5)56/143 (39.2)  
Level of working activity  1.8440.175
Good74/110 (67.3)77/131 (58.8)  
Autonomy  2.1790.140
Good95/109 (87.2)104/130 (80.0)  
Educational level  0.6010.438
Qualified50/111 (45.0) 68/136 (50.0)  
Subtype  23.5300.000a
BD-I100/113 (88.5)86/140 (61.4)  
BD-II13/113 (11.5)54/140 (38.5)  
First episode  76.3650.000a
Depression39/110 (35.5)119/134 (88.8)  
Primary substance use68/102 (66.7)61/128 (47.7)17.1740.001a
Primary life events49/92 (53.3)85/120 (70.8)6.9150.009a
Substance use  27.8530.366
None27/108 (25.0)48/136 (35.3)  
Alcohol31/108 (28.7)36/136 (26.5)  
Cannabinoids29/108 (26.9)53/136 (39.0)  
Rapid cycling12/106 (11.3)15/132 (11.4)0.0000.992
Melancholia23/100 (23.0)54/121 (44.6)11.2810.001a
Catatonia4/99 (4.0)5/121 (4.1)0.0010.973
Seasonal pattern21/102 (20.6)38/130 (29.2)2.2510.134
Psychotic symptoms75/109 (68.8)66/132 (50.0)8.6990.003a
Psychosis at I episode55/90 (61.1)35/90 (38.9)14.9150.000a
Suicidal ideation52/92 (56.5)85/127 (66.9)2.4670.116
Suicide attempts22/100 (22.0)43/124 (34.7)4.3190.038a
Family history of affective disorders64/106 (60.9)85/128 (66.4)0.9110.340
Family history of suicide12/107 (11.2)22/126 (17.5)1.8110.178
Family history of psychiatric disorders86/108 (79.6)103/132 (78.0)0.0910.763
Atypic depression13/94 (13.8)26/116 (22.4)2.5300.112
Medical comorbidity18/41 (43.9)21/59 (35.6)0.7020.402
Psychoeducation17/103 (16.5)14/127 (11.0)3.2290.199
Compliance71/105 (67.6)82/126 (65.1)0.1650.684
Axis I comorbidity27/105 (25.7)37/131 (28.2)20.8770.589
Axis II comorbidity18/105 (17.1)32/132 (24.2)20.6470.192
Axis III comorbidity45/97 (46.4)49/114 (43.0)3.5430.315
Age47.29 (14.5)57.00 (27.9)−3.3750.001a
Age of onset26.16 (10.7)30.57 (11.8)−3.0090.003a
Age of first hospitalization29.89 (13.6)37.35 (14.19)−3.2680.001a
Number of hospitalizations2.17 (2.6)1.40 (1.8)2.6480.009a
Total number of episodes11.67 (18.2)12.21 (16.4)−0.2450.807
Number of manic episodes3.79 (4.7)0.98 (1.3)6.2020.000a
Number of hypomanic episodes4.79 (9.9)2.35 (4.5)2.3360.021a
Number of depressive episodes2.86 (5.9)8.20 (11.7)−4.7550.000a
Number of mixed episodes0.45 (1.5)0.73 (1.6)−1.3600.175
Number of suicide attempts0.80 (3.8)0.75 (1.4)109.9080.129

Differential quantitative features between MPP and DPP groups consist in younger age, younger age at onset, and younger age at first hospitalization, higher hospitalization rate as well as more manic and hypomanic episodes in the MPP group. Depressive episodes were more frequent in the DPP group, while no difference was detected between the two groups regarding total number of episodes, number of mixed episodes nor number of suicide attempts.

Table 3 provides the polarity index reflecting current pharmacological treatment of the two groups. Total polarity index (calculated as mean value of polarity index of all prescribed antipsychotics and mood stabilizers in each patient), as well as polarity index of antipsychotics and mood stabilizers taken separately, were higher, indicating a stronger antimanic regimen, in the MPP group.

Table 3. Polarity index of drugs in manic and depressive polarity groups
 Manic polarity (n = 114)Depressive polarity (n = 143)Mann–Whitney U-test P Kolmogorov–Smirnov Z-test P
MeanSDMeanSD
  1. AP, antipsychotics; MS, mood stabilizers.

  2. a

    P < 0.05.

Polarity index AP + MS3.683.192.222.363385.50.000a2.0690.000a
Polarity index AP6.784.684.774.531281.50.006a1.4250.035a
Polarity index MS1.31 0.231.140.382679.00.001a 1.4290.034a

Table 4 summarizes the current pharmacological treatment of manic polarity and depressive polarity patients. When analyzing single drugs, the prescription of first-generation antipsychotics and second-generation antipsychotics olanzapine and risperidone was significantly more frequent among MPP patients, while use of lamotrigine, antidepressants and benzodiazepines was more prevalent among DPP patients. Interestingly, lithium showed a trend for higher prescription rate in the manic polarity group, but without reaching statistical significance (χ² = 3.521, P = 0.061). Quetiapine had similar rates of prescription in both groups. It is noteworthy that as this is a naturalistic study, results are due to combined therapies and not from isolated drugs.

Table 4. Frequency of prescription of each drug according to predominant polarity
 Manic polarity n (%)Depressive polarity n (%)χ² P
  1. SSRIs, selective serotonin reuptake inhibitors; SNRIs, serotonin–norepinephrine reuptake inhibitors, TCAs, tricyclic antidepressants, IMAOs, MAO inhibitors; ECT, electro convulsive therapy.

  2. a

    P < 0.05.

Mood stabilizers
Carbamazepine13/99 (13.1)16/128 (12.5)0.200.888
Gabapentin0/114 (0)6/143 (4.2)5.0810.79
Lamotrigine9/90 (10.0)30/124 (24.2)7.0490.008a
Lithium75/112 (67.0)74/134 (55.2)3.5210.061
Oxcarbazepine5/114 (4.4)2/143 (1.4)3.2800.194
Topiramate2/114 (1.8)9/143 (6.3)6.0090.50
Valproate20/98 (20.4)23/133 (17.3)0.3610.548
Second-generation antipsychotics
Aripiprazole0/81 (0)3/114 (2.6)2.1650.141
Clozapine3/94 (3.2)1/123 (0.8)1.6660.197
Olanzapine26/103 (25.2)15/127 (11.8)7.0050.008a
Quetiapine12/87 (13.8)21/118 (17.8)0.5940.441
Risperidone32/103 (31.1)14/129 (10.9)14.7230.000a
Ziprasidone1/84 (1.2)1/112 (0.9)0.0420.837
First-generation antipsychotics12/96 (12.5)7 (5.5)15.4090.000a
Antidepressants14/114 (12.3)73/143 (51.0)42.5750.000a
TCAs2/96 (0.0)10/127 (0.1)8.9380.011a
IMAOs 0/91 (0)2/122 (0.0)1.4820.224
SSRIs8/96 (8.3)41/135 (30.4)16.3030.000a
SNRIs 4/93 (4.3)31/134 (23.1)14.9310.000a
Benzodiazepines52/103 (50.5)89/133 (66.9)8.7940.032a
ECT1/95 (1.1)1/124 (0.8)0.0360.849

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

The present study aimed to apply polarity index, a novel metric aiming to help clinicians to understand the prophylactic efficacy profile of drugs used for treatment of bipolar disorder, to real-world clinical practice.

The results of the present study confirm that in clinical settings, the maintenance treatment of bipolar disorder is in accordance with the results emerging from data retrieved from randomized clinical trials by calculating NNT for prevention of depression vs. mania ratio, namely patients with MPP presented significantly higher polarity index, indicating that clinicians chose a treatment regimen with stronger antimanic prophylactic action, than for DPP patients. The same was true for polarity index of atypical antipsychotics and polarity index of mood stabilizers when analyzed separately. It is noteworthy that the majority of patients in our sample did not meet criteria for either PP and thus by design were excluded from the analysis. Nevertheless, the analysis of the polarity index of this group evidenced that the patients who did not present PP had intermediate polarity index values with respect to MPP and DPP groups (Total PI = 2.63 ± 2.85; PI of antipsychotics 5.41 ± 4.63; PI of mood stabilizers 1.14 ± 0.38).

When examining the prevalence of prescription of single mood stabilizing drugs, lamotrigine was prescribed more frequently in patients with DPP, alongside with most antidepressants (tricyclic antidepressants, selective serotonin reuptake inhibitors, and serotonin–norepinephrine reuptake inhibitors) and benzodiazepines. In comparison, risperidone, olanzapine and first-generation antipsychotics were prescribed more often in the MPP group. The only exception was quetiapine, which had similar rates of prescription in both groups. The same was true for lithium, although in this compound, there was a numerical greater use in MPP.

In addition to different pharmacological treatment, several clinical differences were detected between the groups. The present study confirms most of the findings reported by Colom et al. [12]. Main differences, probably due to a larger study sample, involved gender, history of psychotic symptoms, substance use preceding first episode and seasonal pattern. Other findings were consistent, as expected with data from our group [35, 39], but also from independent samples from other areas, countries, and continents [15, 38, 40, 41]. An issue raised during this research is whether it was the PP to determine the different prescribing pattern. Analysis of potential confounding factors, such as age, gender and bipolar disorder subtype has detected no statistically significant influence of age, gender, or bipolar disorder subtype. Antidepressant prescription correlated with the PP, DPP patients being significantly more likely to receive antidepressants.

In summary, MPP was associated with male gender, younger age, younger age at illness onset and younger age of first hospitalization, higher hospitalization rate, and more manic and hypomanic episodes. Regarding clinical features, MPP was associated with bipolar disorder I primary substance abuse and psychotic symptoms. Factors associated with DPP were bipolar disorder II, depressive onset, more depressive episodes, stressful events preceding illness onset, more suicide attempts, and melancholic features. These data are mostly in accordance with recently reported findings by Baldessarini et al. [41] who detected that predominant depression was associated with depressive or mixed onset, more mixed-states, and higher suicidal risk and that predominant mania was associated with initial mania or psychosis and more family history.

Limitations of the present study include the tertiary-center nature of the Barcelona Bipolar Program at Hospital Clinic, which includes a high percentage of difficult-to-treat patients, as well as issues regarding polarity index metric. Id est, polarity index could not be calculated for all drugs used in treatment of bipolar disorder as long-term trials were not conduced for all the agents. In some cases, as for valproate and oxcarbazepine, polarity index may not be reliable due to the failure to separate from placebo during the pivotal maintenance treatment studies, thus we have excluded them from the analysis. Polarity index was retrieved from results of clinical trials; thus, issues related to trial design itself (adjunctive vs. monotherapy design, enrollment of enriched populations of patients who were mainly currently or recently manic or mixed) may have biased the results as discussed in the primary paper on polarity index [13]. Another limitation of the metric is that it is a continuously evolving concept, apace with the ongoing research; studies published subsequently to the original paper as well as eventual future studies might influence polarity index values, especially for agents assessed in a small number of trials [13]. One also has to bear in mind that the calculation of the mean polarity index could not reflect the pharmacokinetic and pharmacodynamic interactions of drugs in combination therapy, nor the doses of medicaments that patients were assuming.

On another matter, an interesting issue is that most maintenance trials assessed samples enriched for efficacy; however, lamotrigine trials were unique in sense that they included study sample enriched for tolerability, and not efficacy, which may have accounted for to the high NNT detected for lamotrigine (50.4 for mania prevention and 20.2 for prevention of depression) [21, 31, 32, 42, 43]. It is important to remember that polarity index is not a measure of the absolute efficacy of a drug, but it rather describes the drug profile; polarity index is a ratio, which does not provide information on NNT of each treatment, but rather tells us how balanced an intervention is. For example, in the case of lamotrigine, although the trial design may have influenced the efficacy reflected in NNT calculation, it is not reflected in polarity index which, with the value of 0.40, indicates that lamotrigine is more antidepressant than antimanic.

Predominant polarity, proposed as a course specifier of particular relevance for long-term therapeutic decision-making process and outcome predictor [44] in DSM-V [45], finds its clinical expression in polarity index. The present study not only provides further evidence to the importance of considering patients' PP, but also examines the actual use of the polarity index in routine clinical practice.

The results of the present naturalistic study confirm the usefulness of polarity index metric in maintenance treatment of BD. Important clinical differences between predominantly manic and predominantly depressed patients emerged and justify the need for differentiated therapeutic approach in the two groups.

Our study shows that the treatment of patients with MPP was oriented mostly toward mania prevention, as evidenced by higher polarity index, while treatment of DPP patients was characterized by lower mean polarity index, thus directed toward preventing depression. Likewise, the choice of the specific drug, even within the same class, varied in accordance with patients' PP; second-generation antipsychotics with stronger antimanic vs. antidepressant properties were prescribed more often in the manic polarity group, and vice versa; mood stabilizers with lower polarity index were prescribed more frequently in depressive polarity patients. Assuming that specialized care centers may provide higher standards of care and better outcomes than non-specialized settings [46], the polarity index may be helpful as a tool to assess the quality of maintenance prescription for bipolar patients; hence, if MPP patients receive higher PI regimens than DPP patients, the treatment is likely to be evidence based.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

The authors of this study would like to thank the support of the Spanish Ministry of Economy and Competitiveness, Instituto de Salud Carlos III, CIBERSAM ‘Cofinanciado por FEDER. Unión Europea’. ‘Una manera de hacer Europa’ and the Generalitat de Catalunya to the Bipolar Disorders Group (2009 SGR 1022).

Declaration of interests

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References

The authors of this paper do not have any commercial associations that might pose a conflict of interest in connection with this manuscript. Dr. Dina Popovic has served as speaker for Bristol-Myers-Squibb and Merck Sharp & Dohme. Dr. Carla Torrent has served as speaker for Bristol-Myers-Squibb. Dr. Jose Manuel Goikolea has served as consultant for Bristol-Myers-Squibb and MSD-Merck. He has been speaker for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo-Smith-Kline, Janssen-Cilag, Lundbeck, Otsuka, Pfizer, and Sanofi-Aventis. Prof. Eduard Vieta has received research grants and served as consultant, advisor, or speaker for the companies: Almirall, Astra-Zeneca, Bristol-Myers Squibb, Eli Lilly, Forest Research Institute, Geodon Richter, Glaxo-Smith-Kline, Janssen-Cilag, Jazz, Lundbeck, Merck Sharp & Dohme, Novartis, Organon, Otsuka, Pfizer Inc, Sanofi-Aventis, Servier, Solvay, Schering-Plough, Takeda, United Biosource Corporation, and Wyeth, research funding from the Spanish Ministry of Science and Innovation, the Stanley Medical Research Institute and the 7th Framework program of the European Union. Prof. Ana González-Pinto has received research grants and served as consultant, advisor, or speaker for the companies: Almirall, Astra-Zeneca, Bristol-Myers Squibb, Eli Lilly, Glaxo-Smith-Kline, Janssen-Cilag, Jazz, Lundbeck, Roche, Novartis, Otsuka, Pfizer Inc, Sanofi-Aventis, Servier, Solvay, Schering-Plough, Takeda, research funding from the Spanish Ministry y of Science and Innovation, the Stanley Medical Research Institute and the Basque Government. Dr. Jose Sanchez-Moreno and Dr. Nuria Cruz declare no conflict of interests.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Study sample
  6. Results
  7. Discussion
  8. Acknowledgements
  9. Declaration of interests
  10. References
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