Department of Respiratory, Tianjin Children's Hospital (Children's Hospital of Tianjin University), Tianjin, 300134, China.
Graduate School of Tianjin Medical University, Tianjin, 300134, China.
BMC Pulm Med. 2022 Jun 27;22(1):253. doi: 10.1186/s12890-022-02047-2.
Early identification of plastic bronchitis (PB) is of great importance and may aid in delivering appropriate treatment. This study aimed to develop and validate a nomogram for predicting PB in patients with refractory Mycoplasma pneumoniae pneumonia (RMPP).
A total of 547 consecutive children with RMPP who underwent fiberoptic bronchoscopy (FOB) intervention from January 2016 to June 2021 were enrolled in this study. Subsequently, 374 RMPP children (PB: 137, without PB: 237) from January 2016 to December 2019 were assigned to the development dataset to construct the nomogram to predict PB and 173 RMPP children from January 2020 to June 2021 were assigned to the validation dataset. The clinical, laboratory and radiological findings were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression was applied to construct a nomogram. The performance of the nomogram was evaluated by discrimination, calibration and clinical utility. Comparsion of ROC analysis and decision curve analysis (DCA) between nomogram and other models was performed to evaluate the discrimination ability and clinical utility.
The development dataset included 374 patients with a mean age of 6.6 years and 185(49.5%) were men. The validation dataset included 173 patients and the mean age of the dataset was 6.7 years and 86 (49.7%) were men. From 26 potential predictors, LASSO regression identified 6 variables as significant predictive factors to construct the nomogram for predicting PB, including peak body temperature, neutrophil ratio (N%), platelet counts (PLT), interleukin-6 (IL-6), actic dehydrogenase (LDH) and pulmonary atelectasis. The nomogram showed good discrimination, calibration and clinical value. The mean AUC of the nomogram was 0.813 (95% CI 0.769-0.856) in the development dataset and 0.895 (95% CI 0.847-0.943) in the validation dataset. Through calibration plot and Hosmer-Lemeshow test, the predicted probability had a good consistency with actual probability both in the development dataset (P = 0.217) and validation dataset (P = 0.183), and DCA showed good clinical utility. ROC analysis indicated that the nomogram showed better discrimination ability compared with model of peak body temperature + pulmonary atelactsis and another model of N% + PLT + IL-6 + LDH, both in development dataset (AUC 0.813 vs 0.757 vs 0.754) and validation dataset (AUC 0.895 vs 0.789 vs 0.842).
In this study, a nomogram for predicting PB among RMPP patients was developed and validated. It performs well on discrimination ability, calibration ability and clinical value and may have the potential for the early identification of PB that will help physicians take timely intervention and appropriate management.
早期识别塑型性支气管炎（PB）非常重要，有助于提供适当的治疗。本研究旨在开发和验证预测难治性肺炎支原体肺炎（RMPP）患者发生 PB 的列线图。
纳入了 2016 年 1 月至 2021 年 6 月期间因 RMPP 行纤维支气管镜（FOB）介入治疗的 547 例连续患儿。随后，将 2016 年 1 月至 2019 年 12 月的 374 例 RMPP 患儿（PB：137 例，无 PB：237 例）纳入开发数据集，以构建预测 PB 的列线图，并将 2020 年 1 月至 2021 年 6 月的 173 例 RMPP 患儿纳入验证数据集。采用最小绝对收缩和选择算子（LASSO）回归筛选临床、实验室和影像学发现，并应用逻辑回归构建列线图。通过区分度、校准和临床实用性评估列线图的性能。比较列线图和其他模型的 ROC 分析和决策曲线分析（DCA），以评估区分能力和临床实用性。
开发数据集中包括 374 例患儿，平均年龄为 6.6 岁，185 例（49.5%）为男性。验证数据集中包括 173 例患儿，平均年龄为 6.7 岁，86 例（49.7%）为男性。从 26 个潜在预测因子中，LASSO 回归确定了 6 个变量作为预测 PB 的重要预测因子，包括最高体温、中性粒细胞比例（N%）、血小板计数（PLT）、白细胞介素-6（IL-6）、肌酸激酶（LDH）和肺不张。列线图显示出良好的区分度、校准度和临床价值。在开发数据集和验证数据集中，列线图的平均 AUC 分别为 0.813（95%CI 0.769-0.856）和 0.895（95%CI 0.847-0.943）。通过校准图和 Hosmer-Lemeshow 检验，开发数据集（P=0.217）和验证数据集（P=0.183）中预测概率与实际概率均具有良好的一致性，DCA 显示出良好的临床实用性。ROC 分析表明，与最高体温+肺不张模型和另一个 N%+PLT+IL-6+LDH 模型相比，列线图在开发数据集（AUC 0.813 与 0.757 与 0.754）和验证数据集（AUC 0.895 与 0.789 与 0.842）中具有更好的区分能力。
本研究开发并验证了预测 RMPP 患者发生 PB 的列线图。该列线图在区分能力、校准能力和临床价值方面表现良好，可能具有早期识别 PB 的潜力，有助于医生及时进行干预和采取适当的治疗措施。
