Development and validation of risk prediction model for aggressive behaviors of community patients with schizophrenia
10.19428/j.cnki.sjpm.2022.21677
- VernacularTitle:社区不同性别精神分裂症患者危险行为发生风险预测模型的建立与验证
- Author:
Yizhou JIANG
1
;
Chunmei CHEN
2
;
Youwei ZHU
2
;
Siyuan HE
2
;
Jun CAI
2
;
Bin XIE
2
;
Weibo ZHANG
2
;
Na WANG
1
Author Information
1. Key Laboratory of Public Health and Safety of Ministry of Education，School of Public Health， Fudan University， Shanghai 200032， China
2. Shanghai Merital Health Center， Shanghai Jiao Tong University School of Medicine， Shanghai200030， China
- Publication Type:Journal Article
- Keywords:
schizophrenia;
aggressive behavior;
cohort study;
prediction model;
gender
- From:
Shanghai Journal of Preventive Medicine
2022;34(10):948-954
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo determine the factors associated with aggressive behaviors of patients with schizophrenia by gender in communities in Shanghai， and further develop and validate the prediction model. MethodsA total of 7 955 community patients with schizophrenia were investigated in Xuhui District， Hongkou District and Jiading District of Shanghai. Baseline information was collected from April 2018 and follow-up was conducted every 3 months for 6 months. Multivariate logistic regression was used to calculate the odd ratio （OR） and 95% CI， and determine the factors associated with aggressive behaviors of patients. The risk score for each patient was developed based on the β coefficient， and the best cut-off value was determined by the Youden index. For the models， predictive ability was determined using area under the curve （AUC） of receiver operator characteristic curve （ROC curve）， and internal validation ability was evaluated by the ten-fold cross validation method. ResultsThere were 3 563 males in this study with an average age of （54.83±13.72） years old， and the incidence of aggressive behaviors was 2.55%.There were 4 392 females with an average age of （57.20±14.98） years， and the incidence of aggressive behaviors was 2.64%. For male patients with schizophrenia， single/divorced status （OR=2.04， 95%CI： 1.15‒3.61）， low economic status （OR=2.79， 95%CI： 1.71‒4.54）， irregular medication （OR=4.35， 95%CI：2.23‒8.47）， no medication （OR=1.83， 95%CI：1.03‒3.26）， incomplete/no insight （OR=1.97， 95%CI：0.99‒3.94）， adverse drug reaction （OR=2.61， 95%CI：1.27‒5.37）， psychiatric symptoms involving violence （OR=2.06， 95%CI：1.01‒4.18）， history of aggression （OR=5.29， 95%CI：2.33‒11.98） and recent stress events （OR=8.36， 95%CI：4.13‒16.92） were associated with aggressive behaviors. In contrast， for female patients， age less than 60 years （50‒59 years， OR=2.09， 95%CI： 1.13‒3.87； 40‒49 years， OR=2.74， 95%CI： 1.46‒5.17； 30‒39 years，OR=2.88， 95%CI： 1.48‒5.60； 18‒29 years， OR=5.71， 95%CI： 2.44‒13.37）， educational level of high school and above （senior high school， OR=3.30， 95%CI： 1.46‒7.49； college and university， OR=2.88， 95%CI： 1.21‒6.82）， unemployed status （OR=1.81， 95%CI=1.17‒2.82）， irregular medication （OR=7.87， 95%CI：4.75‒13.05）， no medication （OR=2.11， 95%CI：1.24‒3.62）， adverse drug reaction （OR=2.75， 95%CI：1.50‒5.04）， psychiatric symptoms involving violence （OR=3.08， 95%CI：1.77‒5.37）， social function （OR=3.51， 95%CI：2.07‒5.94） and recent stress events （OR=5.92， 95%CI： 2.82‒12.44） were risk factors. In both male and female， the prediction models for aggressive behaviors of community patients with schizophrenia had strong predictive ability （AUC=0.779， 95%CI： 0.725‒0.834； AUC=0.822， 95%CI： 0.780‒0.863）. ConclusionThis study suggests that diverse risk factors should be considered for community patients with schizophrenia by gender to prevent the aggressive behaviors.
