A downscaled practical measure of mood lability as a screening tool for bipolar II.
ABSTRACT Current data indicate a strong association between Cyclothymic temperament (and its more ultradian counterpart of mood lability) and Bipolar II (BPII). Administration of elaborate measures of temperament are cumbersome in routine practice. Accordingly, the aim of the present analyses was to test if a practical measure of mood lability was unique to BPII, in comparison with major depressive disorder (MDD).
Using the Structured Clinical Interview for DSM-IV Axis I Disorders, Clinician Version as modified by us [J. Affect. Disord. 73 (2003) 33; Curr. Opin. Psychiatry 16 (2003) S71], we interviewed 62 consecutive BPII outpatients, as well as their 59 MDD counterparts during a major depressive episode (MDE). Hypomanic symptoms during MDE were systematically assessed: three or more such symptoms defined depressive mixed state (DMX3) on the basis of previous work by us [J. Affect. Disord. 73 (2003) 113]. A downscaled definition of trait mood lability was adapted from Akiskal et al. [Arch. Gen. Psychiatry 52 (1995) 114] and Angst et al. [J. Affect. Disord. 73 (2003) 133], requiring a positive response to one of two queries on whether one is a person with frequent "ups and downs" in mood, and whether such mood swings occur for no reason. The patients selected for inclusion had not received neuroleptics and antidepressants for at least 2 weeks prior to the index episode, they were free of substance and alcohol abuse, and did not meet the DSM-IV criteria for borderline personality disorder (BPD). Associations between mood swings and clinical variables were tested by logistic regression (STATA 7).
Mood swings were endorsed by 50.4% of the entire sample: 62.9% of BPII and 37.2% of MDD (p = 0.0047). This practical measure of mood lability was significantly associated with BPII, lower age at onset, high depressive recurrences, atypical features, and DMX3. When controlled for number of major affective episodes, mood swings were still significantly associated with BP-II. Sensitivity and specificity of mood swings for predicting BPII were 62.9% and 62.7%, respectively.
The low specificity of trait mood lability for BPII diagnosis is probably due to the fact that we used a downscaled simplified measure of this trait.
On the other hand, the relatively high sensitivity of our downscaled measure of mood lability for predicting BPII supports its usefulness as a screening tool for this diagnosis. The lack of association between self-reported mood lability and number of major mood episodes indicates that such lability does not reflect the perception of history of frequent episodes, and that it has some validity as a trait indicator. Given that our sample excluded patients meeting the DSM-IV criteria for BPD, contradicts the opinion of the latter manual that such mood lability represents its pathognomonic characteristic that distinguishes it from BPII. The bipolar nature of mood lability is further supported by significant associations with external validating criteria for bipolarity. Overall, these data indicate that in the differential diagnosis between MDD and BPII, trait mood lability favors the latter at a significant statistical level.
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ABSTRACT: Affective instability (AI) is poorly defined but considered clinically important. The aim of this study was to examine definitions and measures of AI employed in clinical populations. This study was a systematic review using the PRISMA guidelines. MEDLINE, Embase, PsycINFO, PsycArticles and Web of Science databases were searched. Also five journals were hand searched. Primary empirical studies involving randomized controlled trials (RCTs), non-RCTs, controlled before and after, and observational investigations were included. Studies were selected, data extracted and quality appraised. A narrative synthesis was completed. A total of 11 443 abstracts were screened and 37 studies selected for final analysis on the basis that they provided a definition and measure of AI. Numbers of definitions for each of the terms employed in included studies were: AI (n = 7), affective lability (n = 6), affective dysregulation (n = 1), emotional dysregulation (n = 4), emotion regulation (n = 2), emotional lability (n = 1), mood instability (n = 2), mood lability (n = 1) and mood swings (n = 1); however, these concepts showed considerable overlap in features. A total of 24 distinct measures were identified that could be categorized as primarily measuring one of four facets of AI (oscillation, intensity, ability to regulate and affect change triggered by environment) or as measuring general emotional regulation. A clearer definition of AI is required. We propose AI be defined as 'rapid oscillations of intense affect, with a difficulty in regulating these oscillations or their behavioural consequences'. No single measure comprehensively assesses AI and a combination of current measures is required for assessment. A new short measure of AI that is reliable and validated against external criteria is needed.Psychological Medicine 09/2013; 44(9):1-16. DOI:10.1017/S0033291713002407 · 5.43 Impact Factor
Journal of Cardiac Failure 09/2011; 17(9). DOI:10.1016/j.cardfail.2011.06.410 · 3.07 Impact Factor
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ABSTRACT: Direct numerical simulation (DNS) of the near-field of a three-dimensional spatially-developing turbulent ethylene jet flame in highly-heated coflow is performed with a reduced mechanism to determine the stabilization mechanism. The DNS was performed at a jet Reynolds number of 10,000 with over 1.29 billion grid points. The results show that auto-ignition in a fuel-lean mixture at the flame base is the main source of stabilization of the lifted jet flame. The Damköhler number and chemical explosive mode (CEM) analysis also verify that auto-ignition occurs at the flame base. In addition to auto-ignition, Lagrangian tracking of the flame base reveals the passage of large-scale flow structures and their correlation with the fluctuations of the flame base similar to a previous study (Yoo et al., J. Fluid Mech. 640 (2009) 453–481) with hydrogen/air jet flames. It is also observed that the present lifted flame base exhibits a cyclic ‘saw-tooth’ shaped movement marked by rapid movement upstream and slower movement downstream. This is a consequence of the lifted flame being stabilized by a balance between consecutive auto-ignition events in hot fuel-lean mixtures and convection induced by the high-speed jet and coflow velocities. This is confirmed by Lagrangian tracking of key variables including the flame-normal velocity, displacement speed, scalar dissipation rate, and mixture fraction at the stabilization point.Proceedings of the Combustion Institute 01/2011; 33(1):1619-1627. DOI:10.1016/j.proci.2010.06.147 · 3.83 Impact Factor