Literature DB >> 29601801

The accuracy of transcutaneous bilirubinometer measurements to identify the hyperbilirubinemia in outpatient newborn population.

Şerif Ercan1, Günay Özgün2.   

Abstract

OBJECTIVES: To assess the ability of transcutaneous bilirubinometer for prediction total serum bilirubin levels in newborn infants after hospital discharge.
METHODS: Newborn infants requiring total serum bilirubin (TSB) level measurement during an outpatient follow-up visit were included into the study. Transcutaneous bilirubin (TcB) measurement was carried out using JH20-1C (Ningbo David, China) transcutaneous jaundice detector and total serum bilirubin was simultaneously determined by direct spectrophotometry. The agreement between paired TSB and TcB measurements were assessed by Bland-Altman plot and Deming regression analysis. Predictive indices were also identified in different TcB cut-off values for TSB levels of 222, 256 and 291 μmol/L.
RESULTS: A total of 271 paired TcB and TSB measurements were obtained from 218 newborn infants. 40.2% had an age of above 7 days at measurement time. The mean difference (95% CI) between TcB and TSB values was -1.7 (-5.4 to 2.1) μmol/L. For TSB levels of at least 256 and 291 μmol/L, a TcB cut-off of 222 μmol/L shows sensitivity of 90.6% and 100%, respectively. It was also determined that 39.4% of TSB measurements could be avoided when using TcB cut-off value of 222 μmol/L.
CONCLUSION: The measurement of TcB with JH20-1C seems to be a reliable screening method for hyperbilirubinemia in the outpatient population when used a TcB cut-off of 222 μmol/L. The use of transcutaneous bilirubinometer could reduce the number of invasive blood sampling for the determination serum bilirubin.
Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Hyperbilirubinemia; Neonatal jaundice; Total serum bilirubin; Transcutaneous bilirubin

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Year:  2018        PMID: 29601801     DOI: 10.1016/j.clinbiochem.2018.03.018

Source DB:  PubMed          Journal:  Clin Biochem        ISSN: 0009-9120            Impact factor:   3.281


  1 in total

1.  The application of artificial intelligence to support biliary atresia screening by ultrasound images: A study based on deep learning models.

Authors:  Fang-Rong Hsu; Sheng-Tong Dai; Chia-Man Chou; Sheng-Yang Huang
Journal:  PLoS One       Date:  2022-10-19       Impact factor: 3.752

  1 in total

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