Despite the large number of treatments available for bipolar disorder (BD), more than one half of patients have a recurrence within 2 years, and over 90% experience at least one additional affective episode during their lifetime.
The aim of this study was to test the impact of a number of demographic and clinical features on the risk to recurrence in a real- word representative sample of 266 outpatients with BD-I or II treated in a naturalistic setting during a 4-years-follow-up period.
We found that the number of episodes per year after study entry, compared to the number of episodes per year before study entry,significantly decreased and that about one third of patients had no recurrences during the observation period. The length of follow-up and the number of previous episodes, mainly depressive, predicted the risk of recurrence, while female gender, higher age at intake, and a higher frequency of past mixed episodes predicted a higher frequency of recurrences.
The study had some limitations to consider: i.e. the risk of poor reliability of information on the previous course of illness or the naturalistic treatment during the follow-up.
Our study suggests that (a) an evidence-based long-term treatment, with regular follow-up visits could improve the course of disease and prognosis; (b) clinicians should carefully consider the presence of a high number of mixed episodes, to provide more targeted treatment strategies; (c) an appropriate use of antidepressants in selected patients did not worsen the course of illness.

BACKGROUND: Until recently, actigraphy studies in bipolar disorders focused on sleep rather than daytime activity in mania or depression, and have failed to analyse mixed episodes separately. Furthermore, even those studies that assessed activity parameters reported only mean levels rather than complexity or predictability of activity. We identified cases presenting in one of three acute phases of bipolar disorder and examined whether the application of non-linear dynamic models to the description of objectively measured activity can be used to predict case classification.
METHODS: The sample comprised 34 adults who were hospitalized with an acute episode of mania (n = 16), bipolar depression (n = 12), or a mixed state (n = 6), who agreed to wear an actiwatch for a continuous period of 24 h. Mean level, variability, regularity, entropy, and predictability of activity were recorded for a defined 64-min active morning and active evening period. Discriminant function analysis was used to determine the combination of variables that best classified cases based on phase of illness.
RESULTS: The model identified two discriminant functions: the first was statistically significant and correlated with intra-individual fluctuation in activity and regularity of activity (sample entropy) in the active morning period; the second correlated with several measures of activity from the evening period (e.g. Fourier analysis, autocorrelation, sample entropy). A classification table generated from both functions correctly classified 79% of all cases based on phase of illness (χ 2 = 36.21; df 4; p = 0.001). However, 42% of bipolar depression cases were misclassified as being in manic phase.
CONCLUSIONS: The findings should be treated with caution as this was a small-scale pilot study and we did not control for prescribed treatments, medication adherence, etc. However, the insights gained should encourage more widespread adoption of statistical approaches to the classification of cases alongside the application of more sophisticated modelling of activity patterns. The difficulty of accurately classifying cases of bipolar depression requires further research, as it is unclear whether the lower prediction rate reflects weaknesses in a model based only on actigraphy data, or if it reflects clinical reality i.e. the possibility that there may be more than one subtype of bipolar depression.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) has shown efficacy in resistant unipolar depression, but its efficacy in bipolar disorders has not yet been extensively investigated. Mixed episodes are reported in up to 40% of acute bipolar admissions and are associated with severe psychopathology, comorbidity, high risk of suicide and poor treatment response. Right low-frequency rTMS (LF-rTMS) as an augmentation treatment might be effective for mixed states.
METHODS: Forty patients were treated during a 4-week period with a mood stabilizer and subsequent rTMS (low frequency stimulation - 1Hz - applied to the right Dorso-Lateral Prefrontal Cortex (DLPFC)) as add-on treatment for 3 weeks. Response to LF-rTMS was assessed by the Hamilton Depression Rating Scale (HAM-D), the Young Mania Rating Scale (YMRS) and the Clinical Global Impressions-Bipolar Version (CGIBP) subscales. ANOVA with repeated measures performed on HAM-D, YMRS and CGI-BP subscales \"change from the preceding phase\" and \"severity of illness\" showed a statistically significant time effect from the baseline to the endpoint.
RESULTS: For the HAM-D there was a 46.6% responder rate, of which 28.6% was remitted, while for the YMRS there was a 15% responder rate, all of which was remitted.
CONCLUSIONS: The open label-design of our study and the lack of a sham-controlled group represent a methodological limitation.
CONCLUSIONS: The results suggest that LF-rTMS on the right DLFC might be a potential augmentation strategy in the treatment of both depressive and manic symptoms in mixed states.