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儿童难治性支原体肺炎风险因素评估 被引量:2

Risk factors assessment of refractory Mycoplasma pneumoniae pneumonia in children
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摘要 目的 分析难治性支原体肺炎的影响因素,预测其发生发展。方法 2018年1月—2021年6月安徽省濉溪县医院收治的300例支原体肺炎患儿,根据是否为难治性支原体肺炎分为难治性支原体肺炎(RMPP)组及普通支原体肺炎(GMPP)组,比较两组患儿的临床资料及白细胞、中性粒细胞百分比等指标;应用多因素Logistic回归模型分析影响难治性支原体肺炎发生的因素。结果 RMPP患儿的发热天数、喘息天数、病程均长于GMPP患儿,中性粒细胞百分比、CRP水平、合并肺实质改变、病毒共感染的比例均明显高于GMPP组(P<0.05);多因素Logistic回归分析显示喘息天数过长、中性粒细胞百分比及CRP水平过高是影响难治性支原体肺炎发生的独立危险因素,而没有病毒感染是防止难治性支原体肺炎发生的独立保护因素(P<0.05)。结论 喘息天数、中性粒细胞百分比等指标可有效预测难治性支原体肺炎发生。 Objective To analyze the influencing factors of refractory Mycoplasma pneumoniae pneumonia(RMPP),and predict its occurrence and development.Methods A total of 300 children with Mycoplasma pneumoniae admitted to Anhui Suixi County Hospital from January 2018 to June 2021 were included in this study.According to whether they were RMPP,they were divided into RMPP group and common Mycoplasma pneumoniae pneumonia(GMPP)group.The clinical data and percentage of leukocytes,neutrophil were compared.The influencing factors of RMPP were analyzed by using multiple Logistic regression model.Results The days of fever,panting and course of disease in children with RMPP were longer than those in children with GMPP,the percentage of neutrophil granutrophils,CRP,lung parenchyma changes and the proportions of virus co-infection were significantly higher than those in children with GMPP(P<0.05).Multivariate Logistic regression analysis showed that long panting days,high neutrophil percentage and CRP level were independent risk factors for RMPP,while no viral infection was independent protective factor against RMPP(P<0.05).Conclusion The number of panting days and percentage level of neutrophil could effectively predict the occurrence of RMPP.
作者 王颖 刘道路 张瑜 WANG Ying;LIU Daolu;ZHANG Yu(Second Department of Pediatrics,Suixi County Hospital,Anhui Province,Huaibei,Anhui 235100,China)
出处 《中国国境卫生检疫杂志》 CAS 2023年第6期563-566,共4页 Chinese Journal of Frontier Health and Quarantine
关键词 难治性支原体肺炎 病毒共感染 预测 列线图 Refractory Mycoplasma pneumoniae pneumonia Virus co-infection Predict Column diagram
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