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Development and validation of a predictive model for readmission of major depressive disorder patients with suicide attempts.

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Title: Development and validation of a predictive model for readmission of major depressive disorder patients with suicide attempts.
Authors: Hao, Xinmei, Wang, Ligang, Dou, Liqiang, Huang, Yingying, Chen, Jun, Sun, Ping
Source: International Journal of Psychiatry in Clinical Practice. Jun2025, Vol. 29 Issue 2, p82-90. 9p.
Subjects: Risk assessment, Prediction models, Research funding, Patient readmissions, Hospital care, Drug addiction, Retrospective studies, Descriptive statistics, Multivariate analysis, Anxiety, Antipsychotic agents, Bilirubin, Suicidal behavior, Antidepressants, Medical records, Acquisition of data, Statistics, Data analysis software, Length of stay in hospitals, Psychoses, Mental depression
Abstract: The study aimed to investigate the determinants associated with readmission in first-hospitalised major depressive disorder (MDD) patients with suicide attempts. The study included a cohort of 3977 patients diagnosed with MDD, as retrieved from the hospital information system (HIS). The data were split into a training set and a validation set using R software. To develop a stepwise regression model, the multivariate logistic analysis included significant factors (p threshold <0.2 in univariate analysis).(1) There was a significant difference in the incidence of readmission between first-hospitalised MDD patients with suicide attempts and those without; (2) Length of stay, course of disease, somatic symptoms, psychosis symptoms, anxiety symptoms, alcohol/tobacco dependence, family history of psychiatric disease, continued use of antidepressants combined with antipsychotics or not after discharge, and total bilirubin (TBIL) were included in these variables to build a predictive model in R software; (3) The area under the curve (AUC) was 0.783 for the training set and 0.778 for the validation set. The Hosmer–Lemesho (H-L) test for calibration was p = 0.3521 for the training set and p = 0.8497 for the validation set. The study revealed a significantly increased risk of readmission in first-hospitalised MDD patients with suicide attempts compared to their counterparts. KEY POINTS: There was a significant difference in the incidence of readmission between first-hospitalised major depressive disorder (MDD) patients with suicide attempts and those without. Strengths and limitations of this study: Given that few previous studies have built models directly to predict the risk of readmission in first-hospitalised major depressive disorder (MDD) patients with suicide attempts, this study sought to build a novel model. It is a retrospective investigation, using an extensive dataset, to explore the determinants associated with recurrent hospitalisation in MDD patients with suicide attempts. Based on the results of the regression analysis, we developed and validated a model based primarily on non-enzymatic antioxidant metrics for individualised prediction of readmission risk among first-hospitalised MDD patients with suicide attempts. However, the results of this retrospective study have not been validated by a prospective cohort study. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Psychiatry in Clinical Practice is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: The study aimed to investigate the determinants associated with readmission in first-hospitalised major depressive disorder (MDD) patients with suicide attempts. The study included a cohort of 3977 patients diagnosed with MDD, as retrieved from the hospital information system (HIS). The data were split into a training set and a validation set using R software. To develop a stepwise regression model, the multivariate logistic analysis included significant factors (p threshold &lt;0.2 in univariate analysis).(1) There was a significant difference in the incidence of readmission between first-hospitalised MDD patients with suicide attempts and those without; (2) Length of stay, course of disease, somatic symptoms, psychosis symptoms, anxiety symptoms, alcohol/tobacco dependence, family history of psychiatric disease, continued use of antidepressants combined with antipsychotics or not after discharge, and total bilirubin (TBIL) were included in these variables to build a predictive model in R software; (3) The area under the curve (AUC) was 0.783 for the training set and 0.778 for the validation set. The Hosmer–Lemesho (H-L) test for calibration was p = 0.3521 for the training set and p = 0.8497 for the validation set. The study revealed a significantly increased risk of readmission in first-hospitalised MDD patients with suicide attempts compared to their counterparts. KEY POINTS: There was a significant difference in the incidence of readmission between first-hospitalised major depressive disorder (MDD) patients with suicide attempts and those without. Strengths and limitations of this study: Given that few previous studies have built models directly to predict the risk of readmission in first-hospitalised major depressive disorder (MDD) patients with suicide attempts, this study sought to build a novel model. It is a retrospective investigation, using an extensive dataset, to explore the determinants associated with recurrent hospitalisation in MDD patients with suicide attempts. Based on the results of the regression analysis, we developed and validated a model based primarily on non-enzymatic antioxidant metrics for individualised prediction of readmission risk among first-hospitalised MDD patients with suicide attempts. However, the results of this retrospective study have not been validated by a prospective cohort study. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of International Journal of Psychiatry in Clinical Practice is the property of Taylor &amp; Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=185860133
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/13651501.2025.2510244
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 82
    Subjects:
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Patient readmissions
        Type: general
      – SubjectFull: Hospital care
        Type: general
      – SubjectFull: Drug addiction
        Type: general
      – SubjectFull: Retrospective studies
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Multivariate analysis
        Type: general
      – SubjectFull: Anxiety
        Type: general
      – SubjectFull: Antipsychotic agents
        Type: general
      – SubjectFull: Bilirubin
        Type: general
      – SubjectFull: Suicidal behavior
        Type: general
      – SubjectFull: Antidepressants
        Type: general
      – SubjectFull: Medical records
        Type: general
      – SubjectFull: Acquisition of data
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      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Data analysis software
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      – SubjectFull: Length of stay in hospitals
        Type: general
      – SubjectFull: Psychoses
        Type: general
      – SubjectFull: Mental depression
        Type: general
    Titles:
      – TitleFull: Development and validation of a predictive model for readmission of major depressive disorder patients with suicide attempts.
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            NameFull: Hao, Xinmei
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            NameFull: Huang, Yingying
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            NameFull: Chen, Jun
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            – D: 01
              M: 06
              Text: Jun2025
              Type: published
              Y: 2025
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            – TitleFull: International Journal of Psychiatry in Clinical Practice
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