Background: Chronic cough after pulmonary resection is one of the most common complications, which seriously affects the quality of life of patients after surgery. Therefore, the aim of this study is to explore the risk factors of chronic cough after pulmonary resection and construct a prediction model.
Methods: The clinical data and postoperative cough of 499 patients who underwent pneumonectomy or pulmonary resection in The First Affiliated Hospital of University of Science and Technology of China from January 2021 to June 2023 were retrospectively analyzed. The patients were randomly divided into training set (n=348) and validation set (n=151) according to the principle of 7:3 randomization. According to whether the patients in the training set had chronic cough after surgery, they were divided into cough group and non-cough group. The Mandarin Chinese version of Leicester cough questionnare (LCQ-MC) was used to assess the severity of cough and its impact on patients' quality of life before and after surgery. The visual analog scale (VAS) and the self-designed numerical rating scale (NRS) were used to evaluate the postoperative chronic cough. Univariate and multivariate Logistic regression analysis were used to analyze the independent risk factors and construct a model. Receiver operator characteristic (ROC) curve was used to evaluate the discrimination of the model, and calibration curve was used to evaluate the consistency of the model. The clinical application value of the model was evaluated by decision curve analysis (DCA).
Results: Multivariate Logistic analysis screened out that preoperative forced expiratory volume in the first second/forced vital capacity (FEV1/FVC), surgical procedure, upper mediastinal lymph node dissection, subcarinal lymph node dissection, and postoperative closed thoracic drainage time were independent risk factors for postoperative chronic cough. Based on the results of multivariate analysis, a Nomogram prediction model was constructed. The area under the ROC curve was 0.954 (95%CI: 0.930-0.978), and the cut-off value corresponding to the maximum Youden index was 0.171, with a sensitivity of 94.7% and a specificity of 86.6%. With a Bootstrap sample of 1000 times, the predicted risk of chronic cough after pulmonary resection by the calibration curve was highly consistent with the actual risk. DCA showed that when the preprobability of the prediction model probability was between 0.1 and 0.9, patients showed a positive net benefit.
Conclusions: Chronic cough after pulmonary resection seriously affects the quality of life of patients. The visual presentation form of the Nomogram is helpful to accurately predict chronic cough after pulmonary resection and provide support for clinical decision-making.
【中文题目：肺部切除术后慢性咳嗽预测模型的建立与验证】 【中文摘要：背景与目的 肺部切除术后慢性咳嗽是最常见的并发症之一，严重影响患者术后生活质量，目前国内尚无关于肺部切除术后慢性咳嗽预测模型。因此，本研究旨在探讨肺部切除术后慢性咳嗽相关危险因素，构建预测模型并进行验证。方法 回顾性分析2021年1月至2023年6月于中国科学技术大学附属第一医院接受肺部切除术的499例患者的临床资料和术后咳嗽情况，按7:3随机分配原则分为训练集（n=348）和验证集（n=151），根据训练集患者术后是否慢性咳嗽分为咳嗽组和非咳嗽组。使用中文版莱斯特咳嗽问卷（The Mandarin-Chinese version of Leicester cough questionnare, LCQ-MC）评估术前、术后咳嗽的严重程度及其对患者生活质量的影响，采用咳嗽视觉模拟量表（visual analog scale, VAS）和自拟的数字评分法（numerical rating scale, NRS）评估术后慢性咳嗽，采用单因素和多因素Logistic回归分析独立危险因素和模型构建，受试者工作特征（receiver operator characteristic, ROC）曲线评估模型区分度，校准曲线评估模型的一致性，绘制决策曲线分析（decision curve analysis, DCA）评估模型的临床应用价值。结果 多因素Logistic分析筛选出术前用力呼气第1秒呼气量与用力肺活量比（forced expiratory volume in the first second/forced vital capacity, FEV1/FVC）、手术方式、行上纵隔淋巴结清扫、行隆突下淋巴结清扫、术后胸腔闭式引流时间是术后慢性咳嗽的独立危险因素，基于多因素分析结果构建列线图预测模型。ROC曲线下面积为0.954（95%CI: 0.930-0.978），最大约登指数所对应的临界值为0.171，此时敏感度为94.7%，特异度为86.6%。Bootstrap法抽样1000次，校准曲线图预测的肺部切除术后慢性咳嗽与实际发生风险高度一致。DCA显示当预测模型概率的预概率为0.1-0.9之间，患者表现为正的净收益。结论 肺部切除术后慢性咳嗽严重影响患者生活质量。列线图的可视化展现形式有助于准确预测肺部切除术后慢性咳嗽，为临床决策提供支持。 】 【中文关键词：肺部切除术；术后慢性咳嗽；中文版莱斯特咳嗽问卷；预测模型；列线图；决策曲线分析】.
Keywords: Chronic cough; Decision curve analysis; Nomogram; Prediction model; Pulmonary resection; The Mandarin-Chinese version of Leicester cough questionnare.