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| 支气管扩张症患者1年内再发加重的预测模型构建与验证 |
| Construction and validation of a predictive model for re-exacerbation within one year in bronchiectasis patients |
| 投稿时间：2025-08-28 |
| DOI：10.3969/j.issn.1000-0399.2025.12.005 |
| 中文关键词: 支气管扩张症 急性加重 纤维蛋白原 列线图 预测模型 |
| 英文关键词: Bronchiectasis Exacerbation Fibrinogen Nomogram Predictive model |
| 基金项目:2023年安徽省临床医学研究转化专项项目(编号:202304295107020044) |
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| 中文摘要: |
| 目的 分析支气管扩张症患者出现急性加重后1年内再发的影响因素并构建预测模型。方法 回顾性分析2023年1月至2024年8月因支气管扩张急性加重于安徽医科大学第一附属医院治疗的218例的患者临床资料，根据1年内是否再发急性加重分为再发组（n=81例）和非再发组（n=137例），比较两组患者临床资料差异，采用多因素logistic回归分析明确支气管扩张急性加重的独立危险因素，构建预测模型并绘制列线图。通过绘制受试者工作特征（ROC）曲线并计算曲线下面积（AUC）评价模型的区分度，Hosmer-Lemeshow检验及校准图评价模型的校准度，决策曲线（DCA）评价模型在临床中的应用价值。结果 单因素分析结果显示，两组患者过去1年内急性加重次数、是否患有糖尿病、清蛋白、病原学、单核细胞与淋巴细胞比值（MLR）、纤维蛋白原（FIB）、黏液栓有无、第1秒用力呼气容积占预计值百分比（FEV1%pred）、第1秒用力呼气容积占用力肺活量比值（FEV1/FVC）比较，差异有统计学意义（P<0.05）；两组患者既往急性加重总次数、支气管扩张症总病程比较，差异有边缘统计学意义（P<0.10）。多因素logistic回归分析结果提示，FIB（OR=2.251,95%CI:1.376～3.682,P<0.001），过去1年内加重次数（OR=2.996,95%CI 1.668～5.274,P<0.001），黏液栓存在（OR=2.393,95%CI:1.116～5.129,P=0.025）,FEV1%pred（OR=0.969,95%CI:0.941～0.997,P=0.028）,MLR（OR=11.651,95%CI:1.254～108.272,P=0.031），铜绿假单胞菌阳性（OR=3.332,95%CI:1.267～8.765,P=0.015）为支气管扩张症患者再发急性加重的独立危险因素。列线图模型在训练集和验证集中AUC分别为0.856（95%CI:0.792～0.921）、0.782（95%CI:0.667～0.896），校准曲线拟合度良好（P>0.05）,DCA曲线提示在低阈值和高阈值下净收益均较高。结论 在支气管扩张症急性加重患者中，FIB、过去1年内加重次数、黏液栓有无、FEV1%pred、MLR、铜绿假单胞菌阳性与否均有助于判断患者再发急性加重风险，为临床医生制定个性化治疗方案提供参考。 |
| 英文摘要: |
| Objective To identify the risk factors for recurrent acute exacerbation within one year in patients with bronchiectasis and to develop a predictive model. Methods A retrospective analysis was conducted on 218 patients hospitalized for acute exacerbation of bronchiectasis at the First Affiliated Hospital of Anhui Medical University between January 2023 and August 2024. Patients were classified into a recurrence group（n=81） and a non-recurrence group（n=137） based on whether exacerbation reoccurred within one year. Univariate analysis was used to compare clinical characteristics between groups. Multivariate logistic regression was employed to identify independent risk factors, and a nomogram prediction model was constructed. The model’s discriminative ability was evaluated using the receiver operating characteristic（ROC） curve and area under the curve（AUC）. Calibration was assessed with the Hosmer-Lemeshow test and calibration plot, while clinical utility was evaluated using decision curve analysis（DCA）. Results Univariate analysis showed significant differences（P ＜0.05） in the number of acute exacerbations in the past year, presence of diabetes, albumin level, microbiology, monocyte-to-lymphocyte ratio（MLR）, fibrinogen（FIB）, presence of mucus plugs, percent predicted forced expiratory volume in 1 second（FEV1%pred）, and forced expiratory volume in 1 second to forced vital capacity ratio（FEV1/FVC）. The total number of previous exacerbations and total duration of bronchiectasis showed borderline significance（P ＜0.10）. Multivariate analysis identified fibrinogen（FIB）（OR=2.251, 95%CI:1.376～3.682, P ＜0.001）, exacerbation frequency in the preceding year（OR=2.996, 95%CI:1.668～5.274,, P ＜0.001）, mucus plug presence（OR=2.393, 95%CI:1.116～5.129, P ＜0.025）, FEV1%pred（OR=0.969, 95%CI:0.941～0.997, P ＜0.028）, monocyte-to-lymphocyte ratio（MLR）（OR=11.651, 95%CI:1.254～108.272, P ＜0.031）, and Pseudomonas aeruginosa positivity（OR=3.332, 95%CI:1.267～8.765, P ＜0.015） as independent risk factors for recurrent exacerbations. The nomogram demonstrated excellent discrimination（training set AUC=0.856, 95%CI:0.792～0.921; validation set AUC=0.782, 95%CI:0.667～0.896）, good calibration（P＞0.05）, and high net benefit across threshold probabilities in DCA. Conclusions FIB, number of exacerbations in the past year, presence of mucus plugs, FEV1%pred, MLR, and Pseudomonas aeruginosa status are useful indicators for predicting recurrent acute exacerbation risk in bronchiectasis patients, which provides valuable reference for developing individualized treatment strategies. |
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