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.

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.

Lurasidone Efficacy in Mixed Depressive States: A Comparison of Standard Rating Scales to the Koukopoulos Mixed Depression Rating Scale.

INTRODUCTION: A new mood rating scale for mixed states of depression along with manic-like excitatory symptoms, the Koukopoulos Mixed Depression Rating Scale (KMDRS), was assessed in a post hoc analysis of a randomized clinical trial of lurasidone versus placebo in major depressive disorder (MDD) with mixed features. METHODS: The KMDRS was compared with the Montgomery Asberg Depression Rating Scale (MADRS) and the Young Mania Rating Scale (YMRS). Item weighting was performed and compared with an original KMDRS validation data set. Weighting was used to provide imputed KMDRS scores in the lurasidone study, based on observed MADRS and YMRS scores. RESULTS: Standardized effect sizes were larger for MADRS (0.61) and YMRS (0.79) than for KMDRS (0.44, Cohen d). CONCLUSIONS: This analysis did not find that the KMDRS produced a larger effect size than the MADRS in Diagnostic and Statistical Manual for Mental Disorder-5 (DSM-5) defined MDD with mixed features. The lower utility of KMDRS may be due to the imputed nature of this analysis, or also to the DSM-5 defined patient population, which may reflect mixed hypomania rather than mixed depression.

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.

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.

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.

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.