将常规血液参数作为儿童肺炎支原体感染的辅助诊断工具。

Chu Qiu-Ju, Gao Ling-Yu, Zhou Ting-Dong, Tong Yang, Han Ning, Wang Ai-Hua, Hu Huai-Lou, Zhou Qiang, Chen Bing
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引用次数: 0

摘要

导言。近年来,儿童肺炎支原体(M. pneumoniae)感染的发病率逐年上升。肺炎支原体感染的早期鉴别诊断不仅可以避免抗生素的滥用,而且对早期治疗和减少传播至关重要。血常规指标的变化可能对肺炎双球菌感染的诊断具有重要的临床意义,但至今尚未见报道。本研究旨在建立肺炎双球菌感染的预测模型,探讨肺炎双球菌感染患儿血常规指标的变化及临床价值,作为临床肺炎双球菌感染诊断和鉴别的辅助指标。本研究共纳入 770 例呼吸道感染的儿科患者,其中肺炎双球菌组 360 例,SARS-CoV-2 组 40 例,甲型流感病毒组 200 例,对照组 170 例。比较了各组间血常规指标的差异,并采用多变量物流分析法对危险因素进行了分析,同时采用 ROC 曲线对差异指标的诊断效果进行了分析。该研究显示,Mono%(OR:3.411;95% CI:1.638-7.102;P=0.001)是与肺炎双球菌感染相关的独立危险因素,Mono%(AUC=0.786,最佳临界值为 7.8%)在肺炎双球菌感染患者和健康人之间具有良好的鉴别能力。此外,Mono%(OR:0.424;95% CI:0.231-0.781;P=0.006)和Lymp%(OR:0.430;95% CI:0.246-0.753;P=0.003)是区分肺炎双球菌感染和甲型流感病毒感染的独立风险因素,Lymp%(AUC=0.786,最佳临界值为 22.1%)和 Net%(AUC=0.761,最佳临界值为 65.2%)在肺炎双球菌感染和甲型流感病毒感染之间具有良好的鉴别能力。此外,血小板分布宽度(OR:0.680;95% CI:0.538-0.858;P=0.001)是区分肺炎双球菌感染和 SARS-CoV-2 感染的独立危险因素。同时,ROC曲线显示,PDW(AUC=0.786,最佳临界值为15%)具有很好的区分肺炎双球菌感染和SARS-CoV-2感染的能力。本研究表明,血常规指标可作为肺炎双球菌感染的辅助诊断指标,为临床肺炎双球菌感染的诊断和鉴别提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Routine blood parameters as auxiliary diagnostic tools for Mycoplasma pneumoniae infection in children.

Introduction. Recently, the incidence of Mycoplasma pneumoniae (M. pneumoniae) infection in children has been increasing annually. Early differential diagnosis of M. pneumoniae infection can not only avoid the abuse of antibiotics, but also is essential for early treatment and reduction of transmission.Gap statement. The change of routine blood parameters may have important clinical significance for the diagnosis of M. pneumoniae infection, but it has not been reported so far.Aim. This study aims to establish a predictive model for M. pneumoniae infection and explore the changes and clinical value of routine blood parameters in children with M. pneumoniae infection, serving as auxiliary indicators for the diagnosis and differentiation of clinical M. pneumoniae infection.Methodology. A total of 770 paediatric patients with respiratory tract infections were enrolled in this study, including 360 in the M. pneumoniae group, 40 in the SARS-CoV-2 group, 200 in the influenza A virus group, and 170 in the control group. The differences of routine blood parameters among all groups were compared, and risk factors were analysed using multivariate logistics analysis, and the diagnostic efficacy of differential indicators using ROC curves.Results. This study revealed that Mono% (OR: 3.411; 95% CI: 1.638-7.102; P=0.001) was independent risk factor associated with M. pneumoniae infection, and Mono% (AUC=0.786, the optimal cutoff at 7.8%) had a good discriminative ability between patients with M. pneumoniae infection and healthy individuals. Additionally, Mono% (OR: 0.424; 95% CI: 0.231-0.781; P=0.006) and Lymp% (OR: 0.430; 95% CI: 0.246-0.753; P=0.003) were independent risk factors for distinguishing M. pneumoniae infection from influenza A virus infection, and the Lymp% (AUC=0.786, the optimal cutoff at 22.1%) and Net% (AUC=0.761, the optimal cutoff at 65.2%) had good discriminative abilities between M. pneumoniae infection and influenza A infection. Furthermore, platelet distribution width (OR: 0.680; 95% CI: 0.538-0.858; P=0.001) was independent risk factor for distinguishing M. pneumoniae infection from SARS-CoV-2 infection. Meanwhile, the ROC curve demonstrated that PDW (AUC=0.786, the optimal cutoff at 15%) has a good ability to differentiate between M. pneumoniae infection and SARS-CoV-2 infection.Conclusion. This study demonstrates that routine blood parameters can be used as auxiliary diagnostic indicators for M. pneumoniae infection and provide reference for the diagnosis and differentiation of clinical M. pneumoniae infection.

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