التفاصيل البيبلوغرافية
| العنوان: |
An interpretable machine-learning model for predicting the efficacy of nonsteroidal anti-inflammatory drugs for closing hemodynamically significant patent ductus arteriosus in preterm infants |
| المؤلفون: |
Tai-Xiang Liu, Jin-Xin Zheng, Zheng Chen, Zi-Chen Zhang, Dan Li, Li-Ping Shi |
| المصدر: |
Frontiers in Pediatrics, Vol 11 (2023) |
| بيانات النشر: |
Frontiers Media S.A., 2023. |
| سنة النشر: |
2023 |
| المجموعة: |
LCC:Pediatrics |
| مصطلحات موضوعية: |
patent ductus arteriosus, nonsteroidal anti-inflammatory drugs, interpretable machine learning, preterm infant, predictive model, Pediatrics, RJ1-570 |
| الوصف: |
BackgroundNonsteroidal anti-inflammatory drugs (NSAIDs) have been widely used in the closure of ductus arteriosus in premature infants. We aimed to develop and validate an interpretable machine-learning model for predicting the efficacy of NSAIDs for closing hemodynamically significant patent ductus arteriosus (hsPDA) in preterm infants.MethodsWe assessed 182 preterm infants ≤ 30 weeks of gestational age first treated with NSAIDs to close hsPDA. According to the treatment outcome, patients were divided into a “success” group and “failure” group. Variables for analysis were demographic features, clinical features, as well as laboratory and echocardiographic parameters within 72 h before medication use. We developed the machine-learning model using random forests. Model performance was assessed by the area under the receiver operating characteristic curve (AUC). Variable-importance and marginal-effect plots were constructed to explain the predictive model. The model was validated using an external cohort of two preterm infants who received ibuprofen (p.o.) to treat hsPDA.ResultsEighty-three cases (45.6%) were in the success group and 99 (54.4%) in the failure group. Infants in the success group were associated with maternal chorioamnionitis (p = 0.002), multiple births (p = 0.007), gestational age at birth (p = 0.020), use of indometacin (p = 0.007), use of inotropic agents (p |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2296-2360 |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fped.2023.1097950/full; https://doaj.org/toc/2296-2360 |
| DOI: |
10.3389/fped.2023.1097950 |
| URL الوصول: |
https://doaj.org/article/6138e031a90449fb97a819342bed73ae |
| رقم الانضمام: |
edsdoj.6138e031a90449fb97a819342bed73ae |
| قاعدة البيانات: |
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