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Age-specific reference intervals for routine biochemical parameters in healthy neonates, infants, and young children in Iran.

Niloufar AbdollahianHamideh GhazizadehMaryam Mohammadi-BajgiranMehran PashirzadMahdiyeh Yaghooti KhorasaniMary Kathryn BohnShannon SteeleFatemeh RoudiAtieh Kamel KhodabandehSara Ghazi ZadehIman Alami-AraniSeyede Negin BadakhshanHabibollah EsmailyGordon A FernsReza Assaran-DarbanKhosrow AdeliMajid Ghayour Mobarhan
Published in: Journal of cellular and molecular medicine (2022)
Age and sex need to be considered in the establishment of reference intervals (RIs), especially in early life when there are dynamic physiological changes. Since data for important biomarkers in healthy neonates and infants are limited, particularly in Iranian populations, we have determined age-specific RIs for 7 laboratory biochemical parameters. This cross-sectional study comprised a total of 344 paediatric participants (males: 158, females: 186) between the ages of 3 days and 30 months (mean age: 12.91 ± 7.15 months). Serum levels of creatinine, urea, uric acid, calcium, phosphate, vitamin D and high-sensitivity C-reactive protein (hs-CRP) were measured using an Alpha classic-AT plus auto-analyser. We determined age-specific RIs using CLSI Ep28-A3 and C28-A3 guidelines. No sex partitioning was required for any of the biomarkers. Age partitioning was required for kidney function tests and phosphate. The serum concentration of urea and creatinine increased with age, while phosphate and uric acid decreased with age. Age partitioning was not required for serum calcium, vitamin D, and hs-CRP, which remained relatively constant throughout the age range. Age-specific RIs for 7 routine biochemical markers were determined to address critical gaps in RIs in early life to help improve clinical interpretation of blood test results in young children, including neonates. Established age partitions demonstrate the biochemical changes that take place during child growth and development. These novel data will ultimately better disease management in the Iranian paediatric population and can be of value to clinical and hospital laboratories with similar populations.
Keyphrases
  • uric acid
  • early life
  • metabolic syndrome
  • emergency department
  • healthcare
  • machine learning
  • clinical practice
  • artificial intelligence
  • adverse drug