INTRODUCTION Accurate assessment of the risk for bronchopulmonary dysplasia (BPD) is critical to determine the prognosis and identify infants who will benefit from preventive therapies. Clinical prediction models can support the identification of high-risk patients. In this study, we investigated the potential risk factors for BPD and compared machine learning models for predicting the outcome of BPD/death on days 1, 7, 14, and 28 in preterm infants. We also developed a local BPD estimator. METHODS This study involved 124 infants. We evaluated the composite outcome of BPD/death at a postmenstrual age of 36 weeks and identified risk factors that would improve BPD/death prediction. SPSS for Windows Version 11.5 and Weka 3.9 software were used for the data analysis. RESULTS To evaluate the combined effect of all variables, all risk factors were taken into consideration. Gestational age, birth weight, mode of respiratory support, intraventricular hemorrhage, necrotizing enterocolitis, surfactant requirement, and late-onset sepsis were risk factors on postnatal days 7, 14, and 28. In a comparison of four different time points (postnatal days 1, 7, 14, and 28), the day 7 model provided the best prediction. According to this model, when a patient was diagnosed with BPD/death, the accuracy rate was 89.5%. CONCLUSION The postnatal day 7 model was the best predictor of BPD or death. Future validation studies will help identify infants who may benefit from preventive therapies and develop individualized care.

中文翻译：

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评估早产儿支气管肺发育不良的早期预测模型。

简介 准确评估支气管肺发育不良 (BPD) 的风险对于确定预后和确定可从预防性治疗中受益的婴儿至关重要。临床预测模型可以支持高危患者的识别。在这项研究中，我们调查了 BPD 的潜在危险因素，并比较了预测早产儿第 1、7、14 和 28 天 BPD/死亡结果的机器学习模型。我们还开发了本地 BPD 估计器。方法 这项研究涉及 124 名婴儿。我们评估了月经后 36 周时 BPD/死亡的综合结果，并确定了可以改善 BPD/死亡预测的风险因素。SPSS for Windows Version 11.5和Weka 3.9软件用于数据分析。结果 为了评估所有变量的综合效应，所有风险因素均被考虑在内。胎龄、出生体重、呼吸支持方式、脑室内出血、坏死性小肠结肠炎、表面活性剂需求和迟发性败血症是出生后第 7、14 和 28 天的危险因素。在四个不同时间点（出生后第 1 天）的比较中， 、7、14 和 28），第 7 天的模型提供了最佳预测。根据这个模型，当患者被诊断为 BPD/死亡时，准确率为 89.5%。结论 出生后第 7 天模型是 BPD 或死亡的最佳预测因子。未来的验证研究将有助于确定哪些婴儿可能受益于预防性治疗并制定个性化护理。