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儿童难治性肺炎早期诊断列线图的构建。

Construction of a nomogram for early diagnosis of refractory pneumonia in children.

作者信息

Shen Wenna, Sun Xinrong

机构信息

The 1st Department of Respiratory Medicine, Xi'an Children's Hospital, Xi'an, China.

出版信息

Transl Pediatr. 2024 Jul 31;13(7):1119-1129. doi: 10.21037/tp-24-16. Epub 2024 Jul 29.

DOI:10.21037/tp-24-16
PMID:39144443
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11320014/
Abstract

BACKGROUND

Refractory pneumonia (RMPP) has a serious, rapid progression that can easily cause a variety of extra-pulmonary complications. Therefore, the early identification of RMPP is crucial. This study aimed to construct and validate a risk prediction model based on clinical manifestations, laboratory blood indicators, and radiological findings to help clinicians identify patients who are at high risk of RMPP.

METHODS

We retrospectively analyzed the medical records of 369 children with pneumonia (MPP) admitted to Xi'an Children's Hospital, China. The demographics, clinical features, laboratory data, and radiological findings between the RMPP group and the general pneumonia (GMPP) group were compared and subjected to univariate and multivariate logistic regression analyses.

RESULTS

The fever peak and duration of the children in the RMPP group (n=86) were higher and longer compared with those in the GMPP group (n=283) (P<0.05). There was a significant difference in the incidence of lobar pneumonia and pleural effusion in pulmonary imaging between the two groups (P<0.05). Laboratory tests showed that the children with RMPP had lower serum uric acid (SUA) and albumin (ALB) as compared with the GMPP group (P<0.05). White blood cells (WBCs), neutrophil count (NEP), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), C-reactive protein (CRP), and neutrophil-to-lymphocyte ratio (NLR) were higher in the RMPP group (P<0.05). Binary logistic regression analysis showed that the fever duration, pleural effusion, WBC, NEP, lactate dehydrogenase (LDH), CRP, NLR, and SUA levels were independent predictors of RMPP (P<0.05). The receiver operator characteristic (ROC) curve results showed fever duration, WBC, NEP, CRP, LDH, SUA, and NLR had good predictive value. The areas under the curve (AUCs) were 0.861, 0.730, 0.758, 0.837, 0.868, 0.744, and 0.713 and the best cutoff values were 10.50, 10.13, 6.43, 29.45, 370.50, 170.50, and 3.47, respectively. Finally, fever duration of more than 10.5 days, pleural effusion, WBC >10.13×10/L, NEP >6.43×10/L, CRP >29.45 mg/L, LDH >370.50 U/L, NLR >3.47, and SUA <170.5 µmol/mL constructed a prediction model of RMPP. According to internal validation, the mean AUC of the nomogram based on the development dataset was 0.956 [95% confidence interval (CI): 0.937-0.974] with good discrimination ability for predicting RMPP patients. The calibration plot and Hosmer-Lemeshow test (P=0.70) of the prediction model showed good consistency between the predicted probability and actual probability. Decision curve analysis (DCA) showed that the nomogram is clinically useful.

CONCLUSIONS

The simple and easy-to-use nomogram can help clinicians, especially primary doctors, to make early diagnoses of RMPP.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11f/11320014/c38e15957e03/tp-13-07-1119-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11f/11320014/c38e15957e03/tp-13-07-1119-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11f/11320014/c38e15957e03/tp-13-07-1119-f1.jpg
摘要

背景

难治性支原体肺炎(RMPP)病情严重、进展迅速,易引发多种肺外并发症。因此,早期识别RMPP至关重要。本研究旨在构建并验证基于临床表现、实验室血液指标及影像学表现的风险预测模型,以帮助临床医生识别RMPP高危患者。

方法

我们回顾性分析了中国西安市儿童医院收治的369例支原体肺炎(MPP)患儿的病历。比较了RMPP组和普通肺炎(GMPP)组的人口统计学、临床特征、实验室数据及影像学表现,并进行单因素和多因素逻辑回归分析。

结果

RMPP组(n = 86)患儿的发热峰值及持续时间高于GMPP组(n = 283)(P < 0.05)。两组肺部影像学中叶肺炎及胸腔积液的发生率存在显著差异(P < 0.05)。实验室检查显示,RMPP患儿的血清尿酸(SUA)和白蛋白(ALB)水平低于GMPP组(P < 0.05)。RMPP组的白细胞(WBC)、中性粒细胞计数(NEP)、红细胞沉降率(ESR)、降钙素原(PCT)、C反应蛋白(CRP)及中性粒细胞与淋巴细胞比值(NLR)更高(P < 0.05)。二元逻辑回归分析显示,发热持续时间、胸腔积液、WBC、NEP、乳酸脱氢酶(LDH)、CRP、NLR及SUA水平是RMPP的独立预测因素(P < 0.05)。受试者工作特征(ROC)曲线结果显示,发热持续时间、WBC、NEP、CRP、LDH、SUA及NLR具有良好的预测价值。曲线下面积(AUC)分别为0.861、0.730、0.758、0.837、0.868、0.744及0.713,最佳截断值分别为10.50、10.13、6.43、29.45、370.50、170.50及3.47。最终,发热持续时间超过10.5天、胸腔积液、WBC > 10.13×10⁹/L、NEP > 6.43×10⁹/L、CRP > 29.45 mg/L、LDH > 370.50 U/L、NLR > 3.47及SUA < 170.5 µmol/mL构建了RMPP预测模型。根据内部验证,基于开发数据集的列线图平均AUC为0.956 [95%置信区间(CI):0.937 - 0.974],对预测RMPP患者具有良好的区分能力。预测模型的校准图和Hosmer - Lemeshow检验(P = 0.70)显示预测概率与实际概率之间具有良好的一致性。决策曲线分析(DCA)表明列线图具有临床实用性。

结论

简单易用的列线图可帮助临床医生,尤其是基层医生早期诊断RMPP。

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