Department of Respiratory Medicine, Zhejiang Hospital, Hangzhou, China.
The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.
Ann Med. 2022 Dec;54(1):2181-2190. doi: 10.1080/07853890.2022.2105394.
Anxiety and depression are important risk factors for chronic obstructive pulmonary disease (COPD). The aim of this study was to develop a prediction model to predict anxiety or depression in COPD patients. The retrospective study was conducted in COPD patients receiving stable treatment between 2018 and 2020 to develop prediction model. The variables, were readily available in clinical practice, were analysed. After data preprocessing, model training and performance evaluation were performed. Validity of the prediction model was verified in 3 comparative model training. Between 2018 and 2020, 375 eligible patients were analysed. Thirteen variables were included into the final model: gender, age, marital status, education level, long-term residence, per capita annual household income, payment method of medical expenses, direct economic costs of treating COPD in the past year, smoking, COPD progression, number of acute exacerbation of COPD in the last year, regular treatment with inhalants and family oxygen therapy. Risk score threshold in each sample in the training set was 1.414. The area under the curve value was respectively 0.763 and 0.702 in the training set and test set, which were higher than three comparative models. The simple prediction model to predict anxiety or depression in patients with COPD has been developed. Based on 13 available data in clinical indicators, the model may serve as an instrument for clinical decision-making for COPD patients who may have anxiety or depression.Key messagesThirteen variables were included into the prediction model.The AUC value was, respectively, 0.763 and 0.702 in the training set and test set, which were higher than three comparative models.The simple prediction model to predict anxiety or depression in patients with COPD has been developed.
焦虑和抑郁是慢性阻塞性肺疾病(COPD)的重要危险因素。本研究旨在开发一种预测模型,以预测 COPD 患者的焦虑或抑郁。该回顾性研究在 2018 年至 2020 年期间接受稳定治疗的 COPD 患者中进行,以开发预测模型。分析了易于在临床实践中获得的变量。在进行数据预处理、模型训练和性能评估后。在 3 个比较模型训练中验证了预测模型的有效性。2018 年至 2020 年间,共分析了 375 名符合条件的患者。最终模型纳入了 13 个变量:性别、年龄、婚姻状况、教育水平、长期居住、人均年家庭收入、医疗费用支付方式、过去一年治疗 COPD 的直接经济成本、吸烟、COPD 进展、过去一年 COPD 急性加重次数、定期使用吸入剂和家庭氧疗。训练集中每个样本的风险评分阈值为 1.414。在训练集和测试集中,曲线下面积值分别为 0.763 和 0.702,均高于 3 个比较模型。已经开发出一种简单的预测模型来预测 COPD 患者的焦虑或抑郁。该模型基于临床指标中 13 个可用数据,可能成为 COPD 患者临床决策的工具,这些患者可能有焦虑或抑郁。关键信息预测模型纳入了 13 个变量。在训练集和测试集中,AUC 值分别为 0.763 和 0.702,均高于 3 个比较模型。已经开发出一种简单的预测模型来预测 COPD 患者的焦虑或抑郁。