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Predicting the Need for Phototherapy After Discharge.

Michael W Kuzniewicz1,2,3, Jina Park3, Hamid Niki4

  • 1Division of Research and michael.w.kuzniewicz@kp.org.

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|April 27, 2021
PubMed
Summary

New predictive models using the difference between bilirubin levels and phototherapy thresholds (Δ-TSB) show excellent ability to predict hyperbilirubinemia risk in newborns. These Δ-TSB models may be simpler and more effective than the Bhutani Nomogram for guiding infant care.

Keywords:
AAPAUCAmerican Academy of PediatricsDATKPNCKaiser PermanenteNorthern CaliforniaRORTSBarea under the receiver operating characteristic curvedirect antiglobulin testrate of risetotal serum bilirubin

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Area of Science:

  • Neonatal Medicine
  • Pediatric Healthcare
  • Medical Predictive Modeling

Background:

  • Neonatal hyperbilirubinemia screening before discharge identifies infants at risk.
  • The American Academy of Pediatrics (AAP) recommends the Bhutani Nomogram for follow-up and phototherapy guidance.
  • Current methods involve separate graphs, prompting research into unified predictive tools.

Purpose of the Study:

  • To evaluate predictive models incorporating the difference between last total serum bilirubin (TSB) and AAP phototherapy threshold (Δ-TSB).
  • To assess the models' ability to predict postdischarge TSB above phototherapy threshold using a single graph.
  • To compare the predictive accuracy of Δ-TSB models against the Bhutani Nomogram.

Main Methods:

  • Studied 148,162 infants born at ≥35 weeks' gestation (2012-2017).
  • Compared three logistic models: Δ-TSB, Δ-TSB-Plus (with additional variables), and Bhutani Nomogram.
  • Utilized the area under the receiver operating characteristic curve (AUC) on a 20% validation subset.

Main Results:

  • 2,623 infants (1.8%) exceeded phototherapy threshold postdischarge.
  • Δ-TSB models demonstrated superior discrimination: Δ-TSB (AUC 0.93) and Δ-TSB-Plus (AUC 0.95) vs. Bhutani Nomogram (AUC 0.88).
  • Predicted probability of exceeding threshold varied significantly based on predischarge Δ-TSB values.

Conclusions:

  • Δ-TSB models effectively predict postdischarge TSB levels exceeding phototherapy thresholds.
  • These models offer excellent predictive ability and may be simpler to implement than the Bhutani Nomogram.
  • The findings suggest a potential improvement in neonatal hyperbilirubinemia risk assessment and management.