Polypharmacy as maintenance treatment in bipolar illness: A systematic review

OBJECTIVES

Polypharmacy is common in maintenance treatment of bipolar illness, but proof of greater efficacy compared to monotherapy is assumed rather than well known. We systematically reviewed the evidence from the literature to provide recommendations for clinical management and future research.

METHOD

A systematic review was conducted on the use of polypharmacy in bipolar prophylaxis. Relevant papers published in English through 31 December 2019 were identified searching the electronic databases MEDLINE, Embase, PsycINFO, and the Cochrane Library.

RESULTS

Twelve studies matched inclusion criteria, including 10 randomized controlled trials (RCTs). The best drug combination in prevention is represented by lithium + valproic acid which showed a significant effect on time to mood relapses (HR = 0.57) compared to valproic acid monotherapy, especially for manic episodes (HR = 0.51). The effect was significant in terms of time to new drug treatment (HR = 0.51) and time to hospitalization (HR = 0.57). A significant reduction in the frequency of mood relapses was also reported for lithium + valproic acid vs. lithium monotherapy (RR=0.12); however, the trial had a small sample size. Lamotrigine + valproic acid reported significant efficacy in prevention of depressive episodes compared to lamotrigine alone.

CONCLUSIONS

The literature to support a generally greater efficacy with polypharmacy in bipolar illness is scant and heterogeneous. Within that limited evidence base, the best drug combination in bipolar prevention is represented by lithium + valproic acid for manic, but not depressive episodes. Clinical practice should focus more on adequate monotherapy before considering polypharmacy.

Citalopram for Acute and Preventive Efficacy in Bipolar Depression (CAPE-BD): A Randomized, Double-Blind, Placebo-Controlled Trial

OBJECTIVE

To assess the efficacy and safety of citalopram in the acute and maintenance phases of bipolar depression in a randomized, double-blind, placebo-controlled trial.

METHODS

Between 2007 and 2014, 119 subjects with acute major depressive episodes diagnosed with DSM-IV bipolar disorder, type I or type II, were randomized blindly to citalopram or placebo, added to standard mood stabilizers. They were followed for 6 weeks for acute efficacy (primary outcome) and up to 1 year for maintenance efficacy (secondary outcome) using scores on the Montgomery-Asberg Depression Rating Scale (MADRS) and the Mania Rating Scale of the Schedule for Affective Disorders and Schizophrenia (MRS-SADS). The study was powered for a clinically meaningful effect size.

RESULTS

Mean ± SD MADRS scores changed from a baseline value of 27.4 ± 9.1 to 13.1 ± 8.4 at the end of the acute phase for citalopram versus a change from 27.4 ± 7.3 to 15.2 ± 9.9 for placebo, a clinically and statistically nonsignificant difference. Maintenance efficacy also was not better with citalopram than with placebo. Acute manic/hypomanic episodes were similar in both groups, and subjects with type II illness did not have better outcomes than subjects with type I illness. In maintenance treatment, MRS-SADS scores were greater overall, especially in subjects with a rapid-cycling illness course, with citalopram versus placebo.

CONCLUSIONS

Citalopram, added to standard mood stabilizers, did not have clinically meaningful benefit versus placebo for either acute or maintenance treatment of bipolar depression. Acute mania did not worsen with citalopram, but maintenance treatment led to worsened manic symptoms, especially in subjects with a rapid-cycling course.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT00562861.

Predicting change in diagnosis from major depression to bipolar disorder after antidepressant initiation

We aimed to develop and validate classification models able to identify individuals at high risk for transition from a diagnosis of depressive disorder to one of bipolar disorder. This retrospective health records cohort study applied outpatient clinical data from psychiatry and nonpsychiatry practice networks affiliated with two large academic medical centers between March 2008 and December 2017. Participants included 67,807 individuals with a diagnosis of major depressive disorder or depressive disorder not otherwise specified and no prior diagnosis of bipolar disorder, who received at least one of the nine antidepressant medications. The main outcome was at least one diagnostic code reflective of a bipolar disorder diagnosis within 3 months of index antidepressant prescription. Logistic regression and random forests using diagnostic and procedure codes as well as sociodemographic features were used to predict this outcome, with discrimination and calibration assessed in a held-out test set and then a second academic medical center. Among 67,807 individuals who received at least one antidepressant medication, 925 (1.36%) subsequently received a diagnosis of bipolar disorder within 3 months. Models incorporating coded diagnoses and procedures yielded a mean area under the receiver operating characteristic curve of 0.76 (ranging from 0.73 to 0.80). Standard supervised machine learning methods enabled development of discriminative and transferable models to predict transition to bipolar disorder. With further validation, these scores may enable physicians to more precisely calibrate follow-up intensity for high-risk patients after antidepressant initiation.

Characterizing DSM-5 and ICD-11 personality disorder features in psychiatric inpatients at scale using electronic health records

BACKGROUND

Investigation of personality traits and pathology in large, generalizable clinical cohorts has been hindered by inconsistent assessment and failure to consider a range of personality disorders (PDs) simultaneously.

METHODS

We applied natural language processing (NLP) of electronic health record notes to characterize a psychiatric inpatient cohort. A set of terms reflecting personality trait domains were derived, expanded, and then refined based on expert consensus. Latent Dirichlet allocation was used to score notes to estimate the extent to which any given note reflected PD topics. Regression models were used to examine the relationship of these estimates with sociodemographic features and length of stay.

RESULTS

Among 3623 patients with 4702 admissions, being male, non-white, having a low burden of medical comorbidity, being admitted through the emergency department, and having public insurance were independently associated with greater levels of disinhibition, detachment, and psychoticism. Being female, white, and having private insurance were independently associated with greater levels of negative affectivity. The presence of disinhibition, psychoticism, and negative affectivity were each significantly associated with a longer stay, while detachment was associated with a shorter stay.

CONCLUSIONS

Personality features can be systematically and scalably measured using NLP in the inpatient setting, and some of these features associate with length of stay. Developing treatment strategies for patients scoring high in certain personality dimensions may facilitate more efficient, targeted interventions, and may help reduce the impact of personality features on mental health service utilization.

When and how to use lithium

BACKGROUND

Lithium is an old proven medication, but it is infrequently used in current practice. This review examines evidence for its benefits and risks and provides clinical guidance to its use.

METHOD

Narrative review.

RESULTS

Besides its benefit in bipolar illness, lithium has important underappreciated proven benefits in prevention of unipolar depression and suicide. Emerging data support neurobiological benefits for cognition and possible dementia prevention. Likely benefits also exist in low doses for mood temperaments (cyclothymia and hyperthymia). High doses (over 1.0 mmol/L) should be avoided since they increase side effects, complications associated with long-term use, and risk of toxicity. Conversely, low dosing can be legitimate, especially for suicide and dementia prevention. Nuisance side effects of lithium may affect adherence, and medically serious side-effects can occur. Managing strategies are available for side effects.

CONCLUSION

Lithium is the most effective medication in psychiatry, because it has disease-modifying, not just symptomatic, effects. It is effective not only for bipolar illness but also for prevention of suicide, episodes of unipolar depression, mood temperaments, and possibly dementia. Its many benefits need better appreciation, while lowered dosing can reduce risks.

Psychopathology of Mixed States

Mixed states are frequent clinical pictures in psychiatric practice but are not well described in nosologic systems. Debate exists as to defining mixed states. We review factor and cluster analytical studies and prominent clinical/conceptual models of mixed states. While mania involves standard manic symptoms and depression involves standard depressive symptoms, core additional features of the mixed state are, primarily, psychomotor activation and, secondarily, dysphoria. Those features are more pronounced in mixed mania than in mixed depression but are present in both.

Association between DSM-5 and ICD-11 personality dimensional traits in a general medical cohort and readmission and mortality

BACKGROUND

Personality has long been studied as a factor associated with health outcomes. Investigations of large, generalizable clinical cohorts are limited by variations in personality diagnostic methodologies and difficulties with long-term follow-up.

METHODS

Electronic health records of a cohort of patients admitted to a general hospital were characterized using a previously developed natural language processing tool for extracting DSM-5 and ICD-11 personality domains. We used Cox regression and Fine-Gray competing risk survival to analyze the relationships between these personality estimates, sociodemographic features, and risk of readmission and mortality.

RESULTS

Among 12,274 patients, 2379 deaths occurred in the course of 61,761 patient-years at risk, with 19,985 admissions during follow-up. Detachment was the most common personality feature. Presence of disinhibition was independently associated with a higher mortality risk, while anankastic traits were associated with a lower mortality risk. Increased likelihood of readmission was predicted by detachment, while decreased likelihood of readmission was associated with disinhibition and psychoticism traits.

CONCLUSIONS

Personality features can be identified from electronic health records and are associated with readmission and mortality risk. Developing treatment strategies that target patients with higher personality symptom burden in specific dimensions could enable more efficient and focused interventions.

The Koukopoulos Mixed Depression Rating Scale (KMDRS): An International Mood Network (IMN) validation study of a new mixed mood rating scale

BACKGROUND

It has been proposed that the broad major depressive disorder (MDD) construct is heterogenous. Koukopoulos has provided diagnostic criteria for an important subtype within that construct, "mixed depression" (MxD), which encompasses clinical pictures characterized by marked psychomotor or inner excitation and rage/anger, along with severe depression. This study provides psychometric validation for the first rating scale specifically designed to assess MxD symptoms cross-sectionally, the Koukopoulos Mixed Depression Rating Scale (KMDRS).

METHODS

350 patients from the international mood network (IMN) completed three rating scales: the KMDRS, Montgomery-Asberg Depression Rating Scale (MADRS) and Young Mania Rating Scale (YMRS). KMDRS' psychometric properties assessed included Cronbach's alpha, inter-rater reliability, factor analysis, predictive validity, and Receiver Operator Curve analysis.

RESULTS

Internal consistency (Cronbach's alpha = 0.76; 95% CI 0.57, 0.94) and interrater reliability (kappa = 0.73) were adequate. Confirmatory factor analysis identified 2 components: anger and psychomotor excitation (80% of total variance). Good predictive validity was seen (C-statistic = 0.82 95% CI 0.68, 0.93). Severity cut-off scores identified were as follows: none (0-4), possible (5-9), mild (10-15), moderate (16-20) and severe (> 21) MxD.

LIMITATIONS

Non DSM-based diagnosis of MxD may pose some difficulties in the initial use and interpretation of the scoring of the scale. Moreover, the cross-sectional nature of the evaluation does not verify the long-term stability of the scale.

CONCLUSIONS

KMDRS was a reliable and valid instrument to assess MxD symptoms.

The International Mood Network (IMN) Nosology Project: differentiating borderline personality from bipolar illness

OBJECTIVE

The differential diagnosis of bipolar illness vs. borderline personality is controversial. Both conditions manifest impulsive behavior, unstable interpersonal relationships, and mood symptoms. This study examines whether and which mood clinical features can differentiate between both conditions.

METHOD

A total of 260 patients (mean ± standard deviation age 41 ± 13 years, 68% female) attending to a mood clinic were examined for diagnosis of bipolar illness and borderline personality disorder using SCID-I, SCID-II, and clinical mood criteria extracted from Mood Disorder Questionnaire (MDQ). They were analyzed using diagnoses as dependent variables. Predictors of bipolar and borderline diagnoses were identified by multivariable logistic regressions, and predictive validity of models was assessed using ROC curve analysis.

RESULTS

Bipolar illness was strongly predicted by elevated mood (OR = 4.02, 95% CI: 1.80-9.15), increased goal-directed activities (OR = 3.90, 95% CI: 1.73-8.96), and episodicity of mood symptoms (OR = 3.48, 95% CI 1.49-8.39). This triad model predicted bipolar illness with 88.7% sensitivity, 81.4% specificity, and obtained an auROC of 0.91 (95% CI: 0.76-0.96) and a positive predictive value of 85.1%. For borderline personality disorder, only female gender was a statistically significant predictor (OR = 3.41, 95% CI: 1.29-13.7), and the predictive model obtained an auROC of 0.67 (95% CI: 0.53-0.74).

CONCLUSION

In a mood disorder clinic setting, manic criteria and episodic mood course distinguished bipolar illness from borderline personality disorder.

A clinical predictive score for mood disorder risk in low-income primary care settings

BACKGROUND

Despite availability of validated screening tests for mood disorders, busy general practitioners (GPs) often lack the time to use them routinely. This study aimed to develop a simplified clinical predictive score to help screen for presence of current mood disorder in low-income primary care settings.

METHODS

In a cross-sectional study, 197 patients seen at 10 primary care centers in Santiago, Chile completed self-administered screening tools for mood disorders: the Patient Health questionnaire (PHQ-9) and the Mood Disorder Questionnaire (MDQ). To determine participants' current-point mood disorder status, trained clinicians applied a gold-standard diagnostic interview (SCID-I). A simplified clinical predictive model (CM) was developed based on clinical features and selected questions from the screening tools. Using CM, a clinical predictive score (PS) was developed. Full PHQ-9 and GP assessment were compared with PS.

RESULTS

Using multivariate logistic regression, clinical and demographic variables predictive of current mood disorder were identified for a simplified 8-point predictive score (PS). PS had better discrimination than GP assessment (auROC-statistic=0.80 [95% CI 0.72, 0.85] vs. 0.58 [95% CI 0.52, 0.62] p-value <0.0001), but not as good as the full PHQ-9 (0.89 [95% CI 0.85, 0.93], p-value=0.03). Compared with GP assessment, PS increased sensitivity by 50% at a fixed specificity of 90%. Administered in a typical primary care clinical population, it correctly predicted almost 80% of cases.

LIMITATIONS

Further research must verify external validity of the PS.

CONCLUSION

An easily administered clinical predictive score determined, with reasonable accuracy, the current risk of mood disorders in low-income primary care settings.

Detecting Mood Disorder in Resource-Limited Primary Care Settings: Comparison of a self-administered screening tool to general practitioner assessment

Objectives

Although efficacious treatments for mood disorders are available in primary care, under-diagnosis is associated with under-treatment and poorer outcomes. This study compares the accuracy of self-administered screening tests with routine general practitioner (GP) assessment for detection of current mood disorder.

Methods

197 consecutive patients attending primary care centres in Santiago, Chile enrolled in this cross-sectional study, filling out the Patients Health Questionnaire-9 (PHQ-9) for depression and the Mood Disorder Questionnaire (MDQ) for bipolar disorder, after routine GP assessment. Diagnostic accuracy of these self-administered tools was compared with GP assessment, with gold standard diagnosis established by a structured diagnostic interview with trained clinicians (SCID-I).

Results

The sample was 75% female, with a mean age of 48.5 (SD 16.8); 37% had a current mood disorder (positive SCID-I result for depression or bipolar disorder). Sensitivity of the screening instruments (SI) was substantially higher than GP assessment (SI: 0.8, [95% CI 0.71, 0.81], versus GP: 0.2, [95% CI 0.12, 0.25]: p-value < 0.0001), without sacrifice in specificity (SI: 0.9, [95% CI 0.86, 0.96], versus GP: 0.9, [95% CI 0.88, 0.97]: p-value = 0.7). This led to improvement in both positive predictive value (SI: 0.8, [95% CI 0.82, 0.90], versus GP: 0.6, [95% CI 0.50, 0.64]: p-value < 0.001) and negative predictive value (SI: 0.9, [95% CI 0.78, 0.91] versus GP: 0.7, [95% CI 0.56, 0.72]: p-value < 0.01).

Conclusion

Self-administered screening tools are more accurate than GP assessment in detecting current mood disorder in low-income primary care. Such screening tests may improve detection of current mood disorder if implemented in primary care settings.

Cognitive impairment in bipolar disorder and schizophrenia: a systematic review

AIMS

Previous comparisons of cognitive decline among patients with bipolar disorder (BD) and schizophrenia (SZ) have found somehow quite similar profiles of deficits, but results have varied between studies. Therefore an extensive and thoughtful systematic review of the matter is warranted.

METHODS

Studies were found through systematic search (PubMed) following PRISMA guidelines. To be included, studies must have assessed the following cognitive functions: executive functions, memory, IQ, attention-concentration, and perceptuomotor function. In order to make comparison between the two entities, studies should include BD patients with operationally defined euthymia, schizophrenic patients in remission, and third group of healthy control patients. Comparisons were made after controlling for years of schooling and residual affective symptoms.

RESULTS

We found that overall both SZ and BD patients present deficits on all neurocognitive measures compared to healthy controls. In particular, SZ patients show more severe and pervasive cognitive deficits while BD patients present a milder and more confined impairment. In addition, evidence from the literature suggests that SZ and BD patients share a similar cognitive impairment profile with different degrees of deficits. Therefore, the difference between the two groups seems to be more quantitative (degree of deficit) rather than qualitative (profile), supporting a dimensional approach to the two clinical entities. Limitations of the present review includes the impossibility to control for effects of medication, varying time required for assessment across studies, illness diagnosis reliability, and course severity.

CONCLUSION

Patients with BD might exhibit a cognitive impairment that could be similar to SZ in terms of their profile, although patients with SZ may have more severe and widespread impairments.