OBJECTIVE The purpose of this study was to develop a model for predicting severe Mycoplasma pneumoniae pneumonia (SMPP) in pediatric patients with Mycoplasma pneumoniae pneumonia (MPP) on admission by laboratory indicators. METHODS Pediatric patients with MPP from January 2019 to December 2020 in our hospital were enrolled in this study. SMPP was diagnosed according to guideline for diagnosis and treatment of community-acquired pneumonia in children (2019 version). Prediction model was developed according to the admission laboratory indicators. Receiver operating characteristic curve and Goodness-of-fit test were analyzed for the predictive value. RESULTS A total of 233 MPP patients were included in the study, with 121 males and 112 females, aged 4.541 (1-14) years. Among them, 84 (36.1%, 95% CI 29.9-42.6%) pediatric patients were diagnosed as SMPP. Some admission laboratory indicators (immunoglobulins M (IgM), eosinophil proportion, eosinophil count, hemoglobin, erythrocyte sedimentation rate (ESR), total protein, albumin and prealbumin) were found statistically different (p < 0.05) between non-SMPP group and SMPP group. Logistic regress analysis showed IgM, eosinophil proportion, eosinophil count, ESR and prealbumin were independent risk factors for SMPP. According to these five admission laboratory indicators, the prediction model for SMPP in pediatric patients was developed. The area under curve of the prediction model was 0.777, and the goodness-of-fit test showed that the predicted SMPP incidence by the model was consistent with the actual incidence (χ2 = 244.51, p = 0.203). CONCLUSION We developed a model for predicting SMPP in pediatric patients by admission laboratory indicators. This model has good discrimination and calibration, which provides a basis for the early identification SMPP on admission. However, this model should be validated by multicenter studies with large sample.

中文翻译：

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入院实验室指标对儿科患者重症肺炎支原体肺炎的预测模型。

目的 本研究的目的是建立一种通过实验室指标预测儿科肺炎支原体肺炎 (MPP) 患者入院时重症肺炎支原体肺炎 (SMPP) 的模型。方法 2019年1月至2020年12月在我院收治的MPP儿科患者纳入本研究。SMPP根据《儿童社区获得性肺炎诊疗指南（2019版）》进行诊断。根据入院实验室指标建立预测模型。分析受试者工作特征曲线和拟合优度检验的预测值。结果本研究共纳入MPP患者233例，其中男121例，女112例，年龄4.541（1～14）岁。其中，84 (36.1%, 95% CI 29.9-42. 6%) 儿科患者被诊断为 SMPP。非SMPP组与SMPP组的入院实验室指标（免疫球蛋白M（IgM）、嗜酸性粒细胞比例、嗜酸性粒细胞计数、血红蛋白、红细胞沉降率（ESR）、总蛋白、白蛋白和前白蛋白）差异有统计学意义（p < 0.05） . Logistic回归分析显示IgM、嗜酸性粒细胞比例、嗜酸性粒细胞计数、ESR和前白蛋白是SMPP的独立危险因素。根据这五个入院实验室指标，开发了儿科患者 SMPP 的预测模型。预测模型的曲线下面积为0.777，拟合优度检验显示，模型预测的SMPP发病率与实际发病率一致（χ2=244.51，p=0.203）。结论 我们开发了一种通过入院实验室指标预测儿科患者 SMPP 的模型。该模型具有良好的判别性和校准性，为入院早期识别SMPP提供了依据。然而，该模型应通过大样本的多中心研究进行验证。