通讯作者: 袁琛, 1243660363@qq.com

DOI：10.12201/bmr.202409.00021

Risk factors of severe pneumonia in children with macrolide-resistant Mycoplasma pneumoniae pneumonia and the construction of prediction model

• 摘要：目的 探索早期预测大环内酯类耐药肺炎支原体肺炎（Macrolide-Resistant Mycoplasma Pneumoniae Pneumonia，MRMP）患儿发展为重症肺炎的方法。方法 回顾性分析2023年1月至2024年1月在我院住院治疗的117例MRMP患儿的临床资料，根据病情严重程度分为耐药重症组和耐药轻症组，比较两组间的临床特征，分析影响耐药患儿发生重症肺炎支原体肺炎（severe Mycoplasma pneumoniae pneumonia，SMPP）的危险因素。结果 纳入117例MRMP患儿，分为耐药重症组63例，男35例、女28例，年龄7.0 （5.0~8.0） 岁；耐药轻症组54例，男29例、女25例，年龄7.0（6.0~9.3）岁。耐药重症组患儿发热时间、咳嗽时间、白细胞计数（white blood cell，WBC）、C-反应蛋白（C-reactive protein，CRP）、乳酸脱氢酶（lactic dehydrogenase，LDH）均高于耐药轻症组，差异均有统计学意义(均P<0.05)。Logistic回归结果显示发热时间(OR=3.407，95%CI 1.821~6.374)、CRP(mg/L) (OR=1.258，95%CI 1.116~1.417)、LDH(U/L) (OR=1.04，95%CI 1.021~1.059)(均P<0.05)是MRMP发展为SMPP的独立危险因素，预测概率P=exp-23.916+1.226×发热时间(days)+0.229×CRP(mg/L)+0.039×LDH(U/L)/1+exp-23.916+1.226×发热时间(days)+0.229×CRP(mg/L)+0.039×LDH(U/L)，3项联合检测的ROC曲线下面积为0.963（95%CI 0.935~0.991，P＜0.01)。结论 可根据首次就诊时的发热时间、CRP、LDH水平计算大环内酯类耐药肺炎支原体肺炎进展为重症肺炎的预测概率，以期达到早期预测目的。

  关键词： 肺炎支原体; 耐药; 重症肺炎; 预测; 儿童

   

  Abstract: Objective To explore potential predictors of macrolide-resistant Mycoplasma pneumoniae pneumonia (MRMP) to severe pneumonia in early stage. Methods A retrospective analysis was conducted on 117 cases of macrolide-resistant Mycoplasma pneumoniae pneumonia hospitalized in our hospital from January 2023 to January 2024. According to the severity of the disease, the patients were divided into two groups, macrolide-resistant severe group and macrolide-resistant mild group. The clinical characteristics of the two groups were compared, and the risk factors affecting the occurrence of severe Mycoplasma pneumoniae pneumonia (SMPP) were analyzed. Results A total of 117 patients with MRMP finished the study and divided into two groups. There were 63 patients in the severe drug-resistant group, including 35 boys and 28 girls, aged 7.0 (5.0~8.0) years. There were 54 patients in the drug-resistant mild group, including 29 boys and 25 girls, aged 7.0(6.0~9.3) years. The duration of fever, cough, white blood cell count (WBC), C-reactive protein (CRP) and lactate dehydrogenase (LDH) in the macrolide-resistant severe group were higher than those in the macrolide-resistant mild group, and the differences were statistically significant (all P<0.05). Logistic regression analysis showed that the duration of fever (OR=3.407, 95% CI 1.821 to 6.374) and CRP(mg/L) (OR=1.258, 95% CI 1.116~1.417), LDH (U/L) (OR=1.04, 95%CI 1.021~1.059) (all P<0.05) were independent risk factors for the development of MRMP to SMPP. The prediction probability P=exp-23.916+1.226×duration of fever (days)+0.229×CRP(mg/L)+0.039×LDH(U/L)/1+exp-23.916+1.226×duration of fever (days)+0.229×CRP(mg/L)+0.039×LDH(U/L). The area under ROC curve of the three combined tests was 0.963 (95%CI 0.935~0.991, P<0.01). Conclusions The predictive probability of macrolide-resistant severe Mycoplasma pneumoniae pneumonia in children can be calculated according to the duration of fever, CRP and LDH levels at the first visit, to achieve the purpose of early prediction.

  Key words: Mycoplasma pneumoniae; Macrolide-resistant; Severe pneumonia; Forecasting; Child

  提交时间：2024-09-12

  版权声明：作者本人独立拥有该论文的版权，预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
• html

• 图表

• 罗自豪, 耿　刚, 李少军. 儿童肺炎支原体脑炎1例并文献复习. 2024. doi: 10.12201/bmr.202408.00042

  冀鹏磊, 髙崴崴, 李佳霖, 刘待见, 王昱林. 免疫炎症相关指数与重症肺炎转归相关性分析. 2024. doi: 10.12201/bmr.202409.00062

  胡丽娜, 钱爱兵. 新冠肺炎疫情的网络健康信息传播特征分析. 2021. doi: 10.12201/bmr.202101.00013

  刘燕, 李姣, 康宏宇, 李露琪, 张潇潇, 徐子犊, 侯丽. 新型冠状病毒(COVID-19)肺炎防控专题服务构建研究. 2020. doi: 10.12201/bmr.202005.00249

  李晓瑛, 蔡妙芝, 李军莲, 任慧玲, 冀玉静, 邓盼盼, 夏光辉. 面向文献组织的新冠肺炎知识图谱构建研究. 2020. doi: 10.12201/bmr.202010.00840

  李颖, 王晓妃, 陆圣威, 董丹妮, 张景峰, 郑建军. 免疫检查点抑制剂相关性肺炎CT表现与临床特点分析. 2024. doi: 10.12201/bmr.202407.00008

  张红伟, 郭莹, 陈玲, 任淑敏. 新冠肺炎疫情环境下多角色画像系统模型研究*. 2020. doi: 10.12201/bmr.202005.00241

  麻芳菲, 翟文康. 突发性公共卫生事件影响政策议程设置的内在逻辑 ——以新冠肺炎疫情为例. 2021. doi: 10.12201/bmr.202101.00020

  韦云师, 莫伟, 向娅, 廖秋姣, 何柳, 凌朝灵, 陆启祥, 刘芳印. 老年髋部骨折患者术后谵妄风险预测模型的研究进展. 2024. doi: 10.12201/bmr.202409.00029

  阮旭凌, 刘琦, 郭志恒, 晏峻峰. 基于LDA和XGBoost算法的乳腺癌预测模型构建研究. 2022. doi: 10.12201/bmr.202106.00007

• 序号	提交日期	编号	操作
  1	2024-05-30	bmr.202409.00021V1	下载

• 公开评论  匿名评论  仅发给作者 提交评论