| 摘要: |
| 目的:探讨儿童重症百日咳危险因素,构建并评估预测模型以辅助临床决策。方法:回顾性分析2024 年芜湖市第二人民医院110 例≤6 岁百日咳患儿临床资料(重症22 例、非重症88 例)。采用单因素及多因素logistic 回归筛选危险因素并建立预测模型,通过受试者工作特征(ROC)曲线、校准曲线及决策曲线分析(DCA)评估效能。结果:单因素分析示7 项指标差异有统计学意义(P<0. 05),多因素分析显示阵发性青紫、合并感染、高白细胞(WBC)计数是危险因素,年龄为保护因素。预测模型曲线下面积(AUC)为0. 930,灵敏度95. 5%、特异度77. 3%。Bootstrap 法校验区分度良好,DCA 在阈值0. 03~1. 00 具有临床实用性;肺炎发生率95. 5%;相关抗菌药物使用率90. 9%,多数患儿预后良好。结论:阵发性青紫、合并感染、WBC 水平升高是儿童重症百日咳独立危险因素,年龄为保护因素;基于logistic 回归的预测模型判别良好,结合分层防治可提升临床重症管理效能。 |
| 关键词: 儿童 重症百日咳 危险因素 预测模型 防治策略 |
| DOI：doi:10.13407/j.cnki.jpp.1672-108X.2026.04.009 |
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| 基金项目: |
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| Construction of Graded Model and Prophylactic and Therapeutic Strategies Based on Risk Factors forSevere Pertussis in Children |
| Zhang Lu1, He Guohua2, Wang Bingsong3 |
| ((1. Graduate School of Bengbu Medical University, Anhui Bengbu 233000, China;2. the Second People’s Hospital of Wuhu, Anhui Wuhu 241000, China; 3. the First People’s Hospital of Wuhu, Anhui Wuhu 241000, China)) |
| Abstract: |
| Objective: To explore risk factors for severe pertussis in children, to construct and evaluate a predictive model to assist clinical decision-making. Methods: Clinical data of 110 children ⩽6 years with pertussis (22 severe cases, 88 non-severe cases) admitted into the Second People’ s Hospital of Wuhu in 2024 were analyzed retrospectively. Univariate and multivariate logistic regression analyses were used to identify risk factors and construct a predictive model. Model performance was assessed by using receiver operator characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA). Results: Univariate analysis identified seven variables with significant differences (P < 0. 05). Multivariate analysis showed that paroxysmal cyanosis, co-infection, and elevated white blood cell (WBC) were risk factors, while age was protective factors. The predictive model achieved an area under the curve (AUC) of 0. 930, with 95. 5% sensitivity and 77. 3% specificity. Bootstrap validation indicated good discrimination, and DCA demonstrated clinical utility for threshold probabilities from 0. 03 to 1. 00. Pneumonia occurred in 95. 5% of severe cases, and 90. 9% received relevant antibiotics. Most children had favorable outcomes. Conclusion: Paroxysmal cyanosis, co-infection, and elevated WBC are independent risk factors for severe pertussis in children, while age is protective factors. The logistic regression-based predictive model shows good discrimination, and the combination of stratified prevention and treatment can improve the efficiency of clinical intensive care management. |
| Key words: children severe pertussis risk factors prediction model prophylactic and therapeutic strategies |
