Prediction of Congenital Portosystemic Shunt in Neonatal Hypergalactosemia Using Gal-1-P/Gal Ratio, Bile Acid, and Ammonia

Congenital portosystemic shunts (CPSSs) are often associated with life-threatening systemic complications, which may be detected by identifying hypergalactosemia in newborn screening (NBS). However, diagnosing CPSS at an early stage is not easy. The purpose of this study was to predict CPSS early us...

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Published inInternational journal of neonatal screening Vol. 11; no. 3; p. 61
Main Authors Suzuki-Ajihara, Sayaka, Musha, Ikuma, Arao, Masato, Mori, Koki, Fujibayashi, Shunsuke, Ryo, Ihiro, Kono, Tomotaka, Tajima, Asako, Mochizuki, Hiroshi, Imai-Okazaki, Atsuko, Araki, Ryuichiro, Numakura, Chikahiko, Ohtake, Akira
Format Journal Article
LanguageEnglish
Published Switzerland MDPI 07.08.2025
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ISSN2409-515X
2409-515X
DOI10.3390/ijns11030061

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Summary:Congenital portosystemic shunts (CPSSs) are often associated with life-threatening systemic complications, which may be detected by identifying hypergalactosemia in newborn screening (NBS). However, diagnosing CPSS at an early stage is not easy. The purpose of this study was to predict CPSS early using screening values and general blood tests. The medical records of 153 patients with hypergalactosemia who underwent NBS in Saitama Prefecture between 1 December 1997 and 31 October 2023 were retrospectively analyzed. We provided the final diagnosis of the analyzed patients. Of the 153 patients, 44 (29%) were in the CPSS group and 83 (54%) were in the transient galactosemia group. Using the initial screening items and the six blood test items, we attempted to extract a CPSS group from the transient galactosemia group. Finally, a model for CPSS prediction was established. From multiple logistic regression analysis, filtered blood galactose-1 phosphate/galactose, serum total bile acid, and ammonia were adopted as explanatory variables for the prediction model. If the cut-off value for predicted disease probability value (P) was >0.357, CPSS was identified with 86.4% sensitivity (95%CI 72.6–94.8%) and 81.9% specificity (95%CI 72.0–89.5%). This predictive model might allow prediction of CPSS and early intervention.
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ISSN:2409-515X
2409-515X
DOI:10.3390/ijns11030061