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Comparison of two fetal growth curves in screening for high-risk neonates

Y Sakata1, H Nishida

  • 1Department of Pediatrics, Seibo International Catholic Hospital, Tokyo, Japan.

Acta Paediatrica Japonica : Overseas Edition
|December 1, 1996
PubMed

Insights

The mean bodyweight -1.5 standard deviation (SD) is a more effective screening tool for identifying high-risk small-for-gestational-age infants than the 10th percentile cutoff. This finding impacts neonatal screening protocols for light- and small-for-gestational-age infants.

Area of Science:

  • Neonatalogy
  • Perinatal Medicine
  • Public Health

Background:

  • The International Statistical Classification of Diseases and Related Health Problems (ICD-10) uses the 10th percentile for defining small-for-gestational-age (SGA) infants.
  • Japan has historically used the mean bodyweight -1.5 standard deviation (SD) as a screening criterion for SGA infants since 1983.

Purpose of the Study:

  • To evaluate the clinical utility of the 10th percentile versus the mean bodyweight -1.5 SD cutoff for screening high-risk SGA neonates.
  • To compare the morbidity rates associated with different screening criteria for SGA infants.

Main Methods:

  • Analysis of data from 5260 term neonates born between January 1993 and June 1995.
  • Comparison of morbidity rates between neonates identified as SGA by the 10th percentile cutoff and the mean bodyweight -1.5 SD cutoff.

Main Results:

  • Neonates below the mean bodyweight -1.5 SD cutoff exhibited a statistically significant higher morbidity rate compared to those below the 10th percentile cutoff.
  • No significant difference in morbidity was observed between neonates between the mean bodyweight -1.5 SD and 10th percentile cutoffs and those above the 10th percentile cutoff.

Conclusions:

  • The mean bodyweight -1.5 SD is a more effective screening criterion for identifying high-risk SGA infants than the 10th percentile cutoff.
  • This suggests a need to reconsider current screening guidelines for SGA neonates to improve risk identification and management.

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