Diagnostic Accuracy of Cord Blood Bilirubin in Predicting Neonatal Hyperbilirubinemia, Taking Neonatal Hyperbilirubinemia within One Week of Birth as Gold Standard
Abstract
Objective: To determine the diagnostic accuracy of cord blood bilirubin in predicting neonatal
hyperbilirubinemia, taking neonatal hyperbilirubinemia within one week of birth as the gold standard.
Study Design: Across-sectional study.
Place and Duration of Study: The Study was conducted at the Department of Pediatric Medicine, Sheikh
Zayed Hospital, Rahim Yar Khan, Pakistan from 7 September 2020 to 6 March 2021.
Methods: A total of 366 term neonates of both gendersgenders were included. Neonates with congenital
hypothyroidism, neonatal hepatitis, biliary atresia, and sepsis were excluded. After getting informed consent
from parents, a cord blood sample was taken and sent to the institutional laboratory for measuring total
bilirubin levels, and neonatal hyperbilirubinemia (yes/no) was noted. All neonates were followed by the
researcher for one week and neonatal hyperbilirubinemia was noted.
Results: The study yielded 193 true positive and 14 false positive cases, along with 7 false negative and 152 true
negative cases, with a statistically significant p-value of 0.0001. Overall, the diagnostic accuracy of cord blood
bilirubin in predicting neonatal hyperbilirubinemia, using neonatal hyperbilirubinemia within one week of birth
as the gold standard, was found to be 96.50% for sensitivity, 91.57% for specificity, 93.24% for positive
predictive value, 95.60% for negative predictive value, and 94.26% for diagnostic accuracy.
Conclusion: This study has shown that cord blood bilirubin has a rather good diagnostic accuracy for predicting
newborn hyperbilirubinemia.
How to cite this: Majeed M, Ahmed D, Hanif D, Khaliq H, Ahmad A, Khan ZA. Diagnostic Accuracy of Cord Blood Bilirubin in Predicting Neonatal Hyperbilirubinemia, Taking Neonatal Hyperbilirubinemia within One Week of Birth as Gold Standard. Life and Science. 2023; 4(4): 401-409. doi: http://doi.org/10.37185/LnS.1.1.347
Copyright (c) 2023 Maryam Majeed, Daniyal Ahmed, Danish Hanif, Hamna Khaliq, Ali Ahmad, Zunaira Asghar Awan
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.