2022 年第 10 期 第 17 卷

精神分裂症患者并发精神残疾的危险因素分析及列线图预测模型构建  

Risk factors analysis of schizophrenia patients complicated with mental disability and construction of nomogram prediction model

作者：李佳1林荫2康延海1李飞燕1吉训琦3

英文作者：Li Jia1 Lin Yin2 Kang Yanhai1 Li Feiyan1 Ji Xunqi3

单位：1海南省人民医院海南医学院附属海南医院精神心理科，海口570311；2海南省安宁医院精神三科，海口570207；3海南省人民医院海南医学院附属海南医院儿科，海口570311

英文单位：1Department of Psychiatry Hainan General Hospital Hainan Affiliated Hospital of Hainan Medical University Haikou 570311 China; 2the 3rd Department of Psychiatry Hainan Provincial Anning Hospital Haikou 570207 China; 3Department of Pediatrics Hainan General Hospital Hainan Affiliated Hospital of Hainan Medical University Haikou 570311 China

关键词：精神分裂症；精神残疾；危险因素；列线图预测模型

英文关键词：Schizophrenia;Mentaldisability;Riskfactors;Nomogrampredictionmodel

• 摘要：

• 目的 分析精神分裂症患者并发精神残疾的危险因素，并构建列线图预测模型。方法 收集2019年5月至2021年10月在海南省人民医院和海南省安宁医院进行治疗的263例精神分裂症患者的临床资料，根据是否并发精神残疾分为精神残疾组（217例）和非精神残疾组（46例）。比较2组临床资料，采用受试者工作特征(ROC)曲线分析组间差异有统计学意义的指标诊断精神残疾的最佳截断值。采用Logistic回归模型分析精神分裂症患者并发精神残疾的危险因素。构建预测精神分裂症患者并发精神残疾的列线图模型，采用校正曲线对列线图模型进行内部验证和性能评价，决策曲线对列线图模型的预测效能进行临床净收益评估。结果 精神残疾组病程、复发次数、阴性症状量表（SANS）评分均高于非精神残疾组［（9±3）年比（6±4）年、（4.3±2.4）次比（2.4±1.7）次、（69±18）分比（53±13）分］，受教育年限、月收入均低于非精神残疾组［（10±3）年比（13±3）年、（1 796±306）元比（2 067±271）元］（均P＜0.05）。2组患者婚姻状况、家庭氛围、疾病分型、精神状况等方面比较差异有统计学意义（均P＜0.05）。病程、复发次数、受教育年限、月收入、SANS评分诊断精神分裂症患者并发精神残疾的曲线下面积分别为0.680、0.741、0.746、0.756、0.758，最佳截断值分别为4年、3次、11年、1 960元、66分。病程＞4年、复发次数＞3次、家庭氛围不和谐、月收入≤1 960元、SANS评分＞66分是精神分裂症患者并发精神残疾的危险因素，婚姻状况为已婚是精神分裂症患者并发精神残疾的保护因素（均P＜0.05）。将上述因素作为构建列线图模型的预测因子，内部验证结果显示，列线图模型预测精神分裂症患者并发精神残疾的C指数为0.772（95%置信区间：0.653～0.964）。校准曲线显示观测值与预测值之间保持较好一致性。列线图模型预测精神分裂症患者并发精神残疾的阈值＞0.17，列线图模型提供临床净收益。结论 病程、复发次数、婚姻状况、家庭氛围、月收入、SANS评分是精神分裂症患者并发精神残疾的危险因素。基于上述危险因素构建的预测精神分裂症患者并发精神残疾的列线图模型有较好的预测价值，可用于识别并发精神残疾的高危患者。

• Objective  To analyze the risk factors of mental disability in patients with schizophrenia, and to construct a nomogram prediction model. Methods The clinical data of 263 patients with schizophrenia admitted to Hainan General Hospital and Hainan Provincial Anning Hospital from May 2019 to October 2021 were collected. Patients were divided into mental disability group (217 cases) and non mental disability group (46 cases). The clinical data of the two groups were compared. Optimal cut-off values for statistically significant indicators diagnosing mental disability were obtained by receiver operating characteristic (ROC) curve analysis. Multivariate Logistic regression model was used to analyze the risk factors of schizophrenia complicated with mental disability. A nomogram model for predicting schizophrenia patients complicated with mental disability was constructed. The calibration curve was used to conduct internal validation and performance evaluation of the nomogram model, and the decision curve was used to evaluate the clinical net benefit of the nomogram model. Results The course of disease, recurrence times and the scale for assessment of negative symptom (SANS) score in the mental disability group were higher than those in the non mental disability group［（9±3）years vs （6±4）years,（4.3±2.4）times vs （2.4±1.7）times,（69±18） vs （53±13）］, and the years of education and monthly income were lower than those in the non mental disability group［（10±3）years vs （13±3）years,（1 796±306）yuan vs （2 067±271）yuan］(all P＜0.05). There were significant differences in marital status, family atmosphere, disease type and mental status between the two groups (all P＜0.05). The area under the curve of course of disease, recurrence times, years of education, monthly income, and SANS score in diagnosing mental disability in patients with schizophrenia were 0.680, 0.741, 0.746, 0.756, and 0.758, respectively; the optimal cut-off values were 4 years, 3 times, 11 years, 1 960 yuan, and 66, respectively. Course of disease＞4 years, recurrence＞3 times, disharmonious family atmosphere, monthly income≤1 960 yuan, SANS score＞66 were risk factors for schizophrenia complicated with mental disability, and married status  was the a protective factor（all P＜0.05）. Above factors were enrolled into a nomogram model, and internal validation showed that the C-index of the nomogram model for predicting concurrent mental disability in patients with schizophrenia was 0.772 (95% confidence interval: 0.653-0.964). The calibration curve showed good agreement between the observed and predicted values. The threshold value of the nomogram model for predicting the concurrent mental disability of schizophrenia patients is greater than 0.17, and the nomogram model provided clinical net benefit. Conclusions The course of disease, recurrence times, marital status, family atmosphere, monthly income and SANS score are the risk factors of schizophrenia complicated with mental disability. Based on the above risk factors, the model has good predictive value for schizophrenia patients with mental disability, and can be used to identify high-risk patients with mental disability.