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ORIGINAL RESEARCH article

Front. Psychiatry
Sec. Adolescent and Young Adult Psychiatry
Volume 15 - 2024 | doi: 10.3389/fpsyt.2024.1500892

Establishment and validation a relapse prediction model for bipolar disorder

Provisionally accepted
Xiaoqian Zhang Xiaoqian Zhang 1,2*minghao wu minghao wu 3daojin wang daojin wang 4Long Wang Long Wang 1Wen Xie Wen Xie 1
  • 1 Hefei Fourth People's Hospital, Hefei, China
  • 2 School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, China
  • 3 Fourth People's Hospital of Wuhu, Wuhu, Anhui Province, China
  • 4 fourth people's hospital of wuhu, wuhu city, China

The final, formatted version of the article will be published soon.

    The recurrence rate of bipolar disorder (BD) is relatively high. Assessing the risk of relapse in patients with BD can assist in identifying populations at high risk for recurrence, and early feasible interventions can improve patient' prognoses.Therefore, it is important to establish and validate predictive models for relapse risk in patients with BD.We used 303 patients with BD admitted to the Anhui Mental Health Center as a retrospective training cohort and 81 patients from the Wuhu Fourth People's Hospital as an external validation cohort. We collected a multidimensional assessment of the characteristics of patients eligible for enrollment, including general demographic characteristics, medical history, treatment, and assessment of selected scales. At the same time, they were followed up for 1 year after reaching the recovery standard after treatment. Depending on whether their symptoms returned within a year, patients with BD were divided into recurrent and non-recurrent groups. Recurrence risk factors for BD were selected using univariate and binary logistic regression analyses based on the clinical data of the patients and other pertinent information. A nomogram model was developed to predict the incidence of BD relapse. To further assess the model fit and dependability, calibration curves, working curves of subject attributes, and decision curves were also employed.Result： A total of 384 patients with BD were enrolled in this study, of whom 250(65.1%) had non-recurrent episodes and 134(34.9%) had recurrent episodes. Of these, 96 (31.7 %) had relapses at the Anhui Mental Health Centre and 38 (46.9 %) at the Fourth People's Hospital of Wuhu City. According to the results of univariate and multivariate logistic regression analyses, the number of prior episodes (odds ratio [OR]: 1.38, 95%

    Keywords: ：Bipolar disorder, Recurrence, Risk factors, nomogram, Prediction model

    Received: 24 Sep 2024; Accepted: 24 Dec 2024.

    Copyright: © 2024 Zhang, wu, wang, Wang and Xie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xiaoqian Zhang, Hefei Fourth People's Hospital, Hefei, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.