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首页> 外文期刊>Frontiers in Pediatrics >Development and Validation of a Nomogram for Predicting Bronchopulmonary Dysplasia in Very-Low-Birth-Weight Infants
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Development and Validation of a Nomogram for Predicting Bronchopulmonary Dysplasia in Very-Low-Birth-Weight Infants

机译：在极低出生体重婴幼儿预测支气管扩张性发育不良的NOM图的开发和验证

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Background: Bronchopulmonary dysplasia is a common pulmonary disease in newborns and is one of the main causes of death. The aim of this study was to build a new simple-to-use nomogram to screen high-risk populations. Methods: In this single-center retrospective study performed from January 2017 to December 2020, we reviewed data on very-low-birth-weight infants whose gestational ages were below 32 weeks. LASSO regression was used to select variables for the risk model. Then, we used multivariable logistic regression to build the prediction model incorporating these selected features. Discrimination was assessed by the C-index, and and calibration of the model was assessed by and calibration curve and the Hosmer-Lemeshow test. Results: The LASSO regression identified gestational age, duration of ventilation and serum NT-proBNP in the 1st week as significant predictors of BPD. The nomogram-illustrated model showed good discrimination and calibration. The C-index was 0.853 (95% CI: 0.851–0.854) in the training set and 0.855 (95% CI: 0.77–0.94) in the validation set. The calibration curve and Hosmer-Lemeshow test results showed good calibration between the predictions of the nomogram and the actual observations. Conclusion: We demonstrated a simple-to-use nomogram for predicting BPD in the early stage. It may help clinicians recognize high-risk populations.
机译：背景：支气管扩张发育不良是新生儿常见的肺病，是死亡的主要原因之一。本研究的目的是建立一个新的简单富裕的墨水图，以筛选高风险的人群。方法：在这项单一中心回顾性研究中，从2017年1月到2020年12月进行，我们审查了孕代低于32周的低出生体重婴儿的数据。套索回归用于选择风险模型的变量。然后，我们使用多变量的逻辑回归来构建包含这些所选功能的预测模型。通过C折射评估歧视，并通过校准曲线和Hosmer-Lemeshow测试来评估模型的校准。结果：套索回归鉴定为妊娠年龄，第一周内通风持续时间，通风持续时间和血清NT-probnp作为BPD的重要预测因子。 NOMACHAG说明的模型显示出良好的歧视和校准。 C折射率为0.853（95％CI：0.851-0.854），在验证组中，0.855（95％CI：0.77-0.94）。校准曲线和Hosmer-Lemeshow测试结果表明，墨迹图的预测和实际观测之间的校准良好。结论：我们展示了一个简单易用的NOM图，用于预测早期的BPD。它可能有助于临床医生认识到高风险的人群。

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