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

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 <i>p</i> = 0.3521 for the training set and <i>p</i> = 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. There was a significant difference in the incidence of readmission between first-hospitalised major depressive disorder (MDD) patients with suicide attempts and those without.<b>Strengths and limitations of this study:</b> 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. There was a significant difference in the incidence of readmission between first-hospitalised major depressive disorder (MDD) patients with suicide attempts and those without.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29163602.v1
Primary Topic
Suicide and Self-Harm Studies
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article
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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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Suicide and Self-Harm Studies
article

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

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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 &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 <i>p</i> = 0.3521 for the training set and <i>p</i> = 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. There was a significant difference in the incidence of readmission between first-hospitalised major depressive disorder (MDD) patients with suicide attempts and those without.<b>Strengths and limitations of this study:</b> 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. There was a significant difference in the incidence of readmission between first-hospitalised major depressive disorder (MDD) patients with suicide attempts and those without.

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