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Accurate prediction of gestational age using newborn screening analyte data
Kumanan Wilson1, Steven Hawken2, Beth K Potter3
1Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; Institute for Clinical Evaluative Sciences, University of Ottawa, Ottawa, Ontario, Canada; School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, Canada; Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada; Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada.
Newborn screening metabolites can accurately estimate infant gestational age, offering a valuable tool for preterm birth identification, especially in low-resource settings.
Area of Science:
- Biochemistry
- Neonatal Medicine
- Public Health
Background:
- Accurate gestational age estimation is crucial for neonatal care.
- Estimating gestational age is challenging in developing countries.
- Newborn screening metabolites vary by gestational age and can potentially estimate it.
Purpose of the Study:
- To develop an algorithm for estimating gestational age at birth.
- The algorithm is based on analytes from newborn infant screening.
Main Methods:
- Population-based cross-sectional study of 249,700 infants.
- Used multivariable regression analyses to predict gestational age.
- Incorporated newborn screening metabolite measurements and physical characteristics (birthweight, sex).
Main Results:
- The metabolic gestational dating algorithm showed excellent predictive ability (R-square 0.65, RMSE 1.06 weeks).
- Average deviation between observed and expected gestational age was approximately 1 week.
- The model accurately predicted gestational age within ±1 week for two-thirds of infants and discriminated well between term and premature infants (c-statistic >0.99).
Conclusions:
- Metabolic gestational dating provides accurate gestational age prediction.
- This method holds significant potential value in low-resource settings for guiding neonatal care.
