主管:国家卫生健康委员会
主办:国家卫生健康委医院管理研究所
中国科技核心期刊(中国科技论文统计源期刊)
中国科学引文数据库(CSCD)核心库期刊
《中文核心期刊要目总览》核心期刊

中国护理管理 ›› 2023, Vol. 23 ›› Issue (3): 380-385.doi: 10.3969/j.issn.1672-1756.2023.03.012

• 恶性肿瘤护理专题 • 上一篇    下一篇

癌症患者失志综合征风险预测模型的构建与验证

宫轩禹 宋甜田 李菲菲 刘彩玲 张善红   

  1. 大连医科大学附属第二医院护理部,116023 辽宁省大连市
  • 出版日期:2023-03-15 发布日期:2023-03-15
  • 通讯作者: 张善红,硕士,主任护师,科护士长,E-mail:shiffer@sina.com
  • 作者简介:宫轩禹,硕士在读

Construction and validation of a risk prediction model for demoralization syndrome in cancer patients

GONG Xuanyu, SONG Tiantian, LI Feifei, LIU Cailing, ZHANG Shanhong   

  1. Nursing Department, The Second Hospital of Dalian Medical University, Dalian, Liaoning province, 116023, China
  • Online:2023-03-15 Published:2023-03-15
  • Contact: E-mail:shiffer@sina.com

摘要: 目的:构建癌症患者失志综合征发生风险预测模型,为预防失志综合征提供依据。方法:采用便利抽样法,选择2021年11月—2022年6月大连市某三级甲等医院住院的376例癌症患者作为研究对象,通过Logistic回归分析癌症患者失志综合征的危险因素,并绘制列线图,应用受试者操作特征曲线和校准曲线检验模型预测效果。结果:癌症患者失志综合征发生率为44.9%,回归分析筛选出6项失志综合征独立风险因素。模型的ROC曲线下面积为0.973(P<0.001),最大约登指数为0.850,灵敏度为0.891,特异度为0.959,绘制校准曲线斜率接近1,模型预测值与实际观测值有较好一致性。结论:本研究构建的列线图模型具有较好的区分度和准确度,可为肿瘤科医护人员早期识别失志综合征患者提供依据。

关键词: 癌症;失志综合征;相关因素;风险预测模型;列线图

Abstract: Objective: To develop a risk prediction model of demoralization syndrome, and to provide a basis for its prevention. Methods: A total of 376 inpatients with cancer were included from the oncology department of a tertiary grade A hospital in Dalian from November 2021 to June 2022 by convenience sampling, multivariate Logistic regression analysis was used to analyze the risk factors of demoralization syndrome, a nomogram was constructed for visual display, and a receiver operating characteristic curve was used to test the prediction effects of the model. Results: The incidence of demoralization syndrome in cancer patients was 44.9%, and a total of 6 independent risk factors were screened for demoralization syndrome by multivariate Logistic regression analysis. The area under the predicted ROC curve was 0.973 (P<0.001). The maximum Youden index was 0.850, the sensitivity was 0.891, the specificity was 0.959, the slope of the drawn calibration curve was close to 1, and the predicted value of the model was in good agreement with the actual observed value consistency. Conclusion: The constructed model in this study is with good differentiation and accuracy, which can provide evidence for medical staff in oncology department to identify patients with demoralization syndrome in an early stage.

Key words: cancer; demoralization syndrome; correlative factors; risk prediction model; nomogram

中图分类号:  R47;R197