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Risk constellations prior to the development of bipolar disorders: rationale of a new risk assessment tool
Karolina Leopold1, Philipp Ritter, Christoph U Correll
1Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany.
Background:
The precise characterisation of a high risk status for the development of a psychiatric disorder and the question of how well this predicts disease manifestation is of major importance as negative consequences of late diagnosis and treatment have been well demonstrated. In the absence of well defined and disease specific biological markers for bipolar disorder, the recognition of premature stages must rely on combinations of risk factors that have been associated with later disease manifestation.
Methods:
A review of the literature and our experience from the Early Recognition Centre led us to identify symptom constellations.
Results:
Individual categories defined and grouped included: (I) genetic risk, (II) substance use, misuse or dependence, (III) diagnosis/suspected diagnosis of attention deficit hyperactivity disorder, (IV) pronounced creativity, (V) impairment in psychosocial functioning, (VI) subthreshold affective symptoms, and (VII) early symptomatology including (a) changes in sleep and circadian rhythm, (b) changes in mood, mood swings/affective lability, (c) fearfulness/anxiety, and (d) dissociative symptoms. These risk constellations were operationalised and a new risk assessment instrument, the Early Phase Inventory for Bipolar Disorders (EPIbipolar) was developed.
Limitations:
Challenges regarding the validity of the data on which the instrument is based, specificity of and correlations between risk categories, and ethical considerations were encountered.
Conclusions:
Further use of EPIbipolar in research should help to refine prodromal features and narrow these down to a less cumbersome core that can be used to develop a shortened tool for use in clinical care. Prospective longitudinal research is needed to establish the predictive validity of this novel bipolar disorder risk assessment tool.
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