Development of a simplified model and nomogram for the prediction of pulmonary hemorrhage in respiratory distress syndrome in extremely preterm infants.

Journal: BMC pediatrics
PMID: 39574081

Abstract

BACKGROUND: Pulmonary hemorrhage (PH) in respiratory distress syndrome (RDS) in extremely preterm infants exhibits a high mortality rate and poor long-term outcomes. The aim of the present study was to develop a machine learning (ML) predictive model for RDS with PH in extremely preterm infants.

Authors

  • Yu-Qi Liu
    Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.
  • Yue Tao
    Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.
  • Tian-Na Cai
    Department of Radiology, Children's Hospital of Soochow University, Suzhou, 215025, China.
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Hui-Min Mao
    Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.
  • Shi-Jin Zhong
    Department of Radiology, Children's Hospital of Soochow University, Suzhou, 215025, China.
  • Wan-Liang Guo
    Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.

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