Initial and relapse prodromes in adult patients with episodes of bipolar disorder: A systematic review

• Published in: European psychiatry Vol. 63; no. 1; p. e12
• Main Authors: Andrade-González, Nelson, Álvarez-Cadenas, Laura, Saiz-Ruiz, Jerónimo, Lahera, Guillermo
• Format: Journal Article
• Language: English
• Published: England Cambridge University Press 12-02-2020
• Subjects: Adult; bipolar disorder; Bipolar Disorder - diagnosis; Bipolar Disorder - psychology; Humans; Prodromal Symptoms; prodrome; Recurrence; Review/Meta-analyses; systematic review; systematic review; bipolar disorder; prodrome
• ISSN: 0924-9338; 1778-3585
• DOI: 10.1192/j.eurpsy.2019.18

Distinguishing prodromes of bipolar disorder (BD) specific to children/adolescents, adults, and elderly patients is essential. The primary objective of this systematic review was to determine initial and relapse prodromes identifying adult patients with BD.
PubMed, PsycINFO, and Web of Science databases were searched using a predetermined strategy. A controlled process of study selection and data extraction was performed.
The 22 articles selected included 1,809 adult patients with BD. Initial prodromes cited most frequently in these studies showed low specificity. Among relapse prodromes cited most frequently, more talkative than usual, increased energy/more goal-directed behavior, thoughts start to race, increased self-esteem, strong interest in sex, increase in activity, and spending too much were identified exclusively before a manic/hypomanic episode, while loss of interest and hypersomnia were detected only before a depressive episode. Initial prodromal phases lasted longer than prodromal relapse phases. In the selected studies, the most used prodrome identification procedure was the clinical interview.
For adult patients with BD, initial and relapse prodromes of manic, hypomanic, and depressive episodes were identified. It is proposed that the most frequent prodromes found in this review be incorporated into a smartphone app that monitors the functioning of people at risk of BD and patients who have already been diagnosed. Data from this app would constitute a relevant source of big data.