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采用计数回归模型分析精神分裂症患者多项不良结局的影响因素:一项横断面研究。

Influencing factors of multiple adverse outcomes among schizophrenia patients using count regression models: a cross-sectional study.

机构信息

Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China.

Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.

出版信息

BMC Psychiatry. 2022 Jul 15;22(1):472. doi: 10.1186/s12888-022-04070-3.

Abstract

BACKGROUND

Schizophrenia patients have increased risks of adverse outcomes, including violent crime, aggressiveness, and suicide. However, studies of different adverse outcomes in schizophrenia patients are limited and the influencing factors for these outcomes need clarification by appropriate models. This study aimed to identify influencing factors of these adverse outcomes by examining and comparing different count regression models.

METHODS

This study included schizophrenia patients who had at least one follow-up record in the Guangdong Mental Health Center Network Medical System during 2020. Three types of adverse outcomes were included: a) aggressiveness with police dispatch or violent crime, b) aggressiveness without police dispatch, and c) self-harm or suicide attempts. The incidence density of these adverse outcomes was investigated using the Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models, accordingly. The best model was chosen based on goodness-of-fit tests. We further analyzed associations between the number of occurrences of adverse outcomes and sociodemographic, clinical factors with the best model.

RESULTS

A total of 130,474 schizophrenia patients were enrolled. Adverse outcomes rates were reported to be less than 1% for schizophrenia patients in 2020, in Guangdong. The NB model performed the best in terms of goodness-of-fit and interpretation when fitting for the number of occurrences of aggressiveness without police dispatch, whereas the ZINB models performed better for the other two outcomes. Age, sex, and history of adverse outcomes were influencing factors shared across these adverse outcomes. Higher education and employment were protective factors for aggressive and violent behaviors. Disease onset aged ≥ 18 years served as a significant risk factor for aggressiveness without police dispatch, and self-harm or suicide attempts. Family history of mental diseases was a risk factor for self-harm or suicide attempts individually.

CONCLUSIONS

NB and ZINB models were selected for fitting the number of occurrences of adverse outcomes among schizophrenia patients in our studies. Influencing factors for the incidence density of adverse outcomes included both those shared across different types and those individual to specific types. Therefore, comprehensive and customized tools in risk assessment and intervention might be necessary.

摘要

背景

精神分裂症患者发生不良结局的风险增加,包括暴力犯罪、攻击行为和自杀。然而,有关精神分裂症患者不同不良结局的研究有限,需要通过适当的模型来阐明这些结局的影响因素。本研究旨在通过检查和比较不同的计数回归模型来确定这些不良结局的影响因素。

方法

本研究纳入了 2020 年在广东省精神卫生中心网络医疗系统中至少有一次随访记录的精神分裂症患者。纳入了 3 种不良结局:a)有警察出警或暴力犯罪的攻击性,b)无警察出警的攻击性,c)自残或自杀未遂。使用泊松、负二项(NB)、零膨胀泊松(ZIP)和零膨胀负二项(ZINB)模型分别对这些不良结局的发生率密度进行了调查。根据拟合优度检验选择最佳模型。我们进一步分析了与不良结局发生次数相关的社会人口学和临床因素与最佳模型之间的关系。

结果

共纳入了 130474 例精神分裂症患者。2020 年,广东精神分裂症患者的不良结局发生率报告不足 1%。NB 模型在拟合无警察出警的攻击性发生次数方面表现最佳,而 ZIP 模型在其他两种结局方面表现更好。年龄、性别和不良结局史是这些不良结局共有的影响因素。较高的教育和就业是攻击性和暴力行为的保护因素。发病年龄≥18 岁是无警察出警的攻击性的显著危险因素,而自残或自杀未遂的危险因素是发病年龄≥18 岁。精神疾病家族史是单独发生自残或自杀未遂的危险因素。

结论

我们选择 NB 和 ZINB 模型来拟合本研究中精神分裂症患者不良结局的发生次数。不良结局发生率密度的影响因素包括不同类型之间的共同因素和特定类型的个体因素。因此,可能需要综合和定制的风险评估和干预工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/420e/9284775/da9cc28a1942/12888_2022_4070_Fig1_HTML.jpg

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