Scholarlink

Objectives <p>To identify clinical variables and indicators associated with pulmonary hemorrhage in preterm infants.</p> Methods <p>This case-control study included inborn infants &lt;32 weeks. Data were collected in 12-h epochs from birth until hemorrhage onset or up to 72 h for controls. Machine learning used the Random Forest algorithm. Statistical analysis included <i>T</i> test and Mann–Whitney U test.</p> Results <p>Among 1133 screened infants, 35 had hemorrhage. Mean gestational age was 25.6 ± 1.6 weeks, birth weight 753 ± 224 g, and median onset of hemorrhage was 44.5 h. Affected infants more often required chest compressions and invasive ventilation. Machine learning (accuracy = 83%, AUC = 90%) identified repeated surfactant dosing and postnatal hypotension in the first 12 h of life as top predictors, along with maternal and gestational age. Mortality was higher in cases than controls (19% vs. 3%, <i>p</i> = 0.005).</p> Conclusion <p>Repeated surfactant dosing and early postnatal hypotension are key predictors for pulmonary hemorrhage in preterm infants.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Leveraging artificial intelligence for prediction of pulmonary hemorrhage in preterm infants

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月20日

查看全文
  • Hany Aly,
  • Vanishree Nandakumar,
  • Hasan Cetin,
  • Hatem Eltaly,
  • Tetyana Nesterenko,
  • Mohamed A. Mohamed

摘要

Objectives

To identify clinical variables and indicators associated with pulmonary hemorrhage in preterm infants.

Methods

This case-control study included inborn infants <32 weeks. Data were collected in 12-h epochs from birth until hemorrhage onset or up to 72 h for controls. Machine learning used the Random Forest algorithm. Statistical analysis included T test and Mann–Whitney U test.

Results

Among 1133 screened infants, 35 had hemorrhage. Mean gestational age was 25.6 ± 1.6 weeks, birth weight 753 ± 224 g, and median onset of hemorrhage was 44.5 h. Affected infants more often required chest compressions and invasive ventilation. Machine learning (accuracy = 83%, AUC = 90%) identified repeated surfactant dosing and postnatal hypotension in the first 12 h of life as top predictors, along with maternal and gestational age. Mortality was higher in cases than controls (19% vs. 3%, p = 0.005).

Conclusion

Repeated surfactant dosing and early postnatal hypotension are key predictors for pulmonary hemorrhage in preterm infants.