JMIR Publications

ABSTRACT

Background:

Although rates of preterm birth continue to increase globally, identification of preterm from low birth weight infants (LBW) remains a challenge. The burden of LBW vs. preterm is greatest in low resource settings, where gestational age (GA) prior to delivery is frequently not known because ultrasound in early pregnancy is not available and estimates of the date of the last menstrual period (LMP) may not be reliable. An alternative is to assess GA at birth to optimize referral and care of preterm newborns. We had previously developed and pilot tested a simplified gestational age scoring system (SGAS) based on 4 easily observable neonatal characteristics.

Objective:

The objective of this study is to adapt the scoring system as a tablet app (potentially scalable approach), to assess feasibility of use and to validate whether it accurately predicts prematurity by itself, over and above birth weight in a large sample of newborns.

Methods:

The study is based in Nagpur, India, at the Research Unit of the National Institute of Child Health and Human Development’s Global Network for Women’s and Children’s Health Research. The android Tablet app for SGAS (T-SGAS) displays de-identified photographs of skin, breasts and genitalia across a range of GAs and line drawings of infant posture, each item associated with a score. The user is trained to choose the photograph or line drawing that most closely matches a newborn being evaluated and the app determines the neonate’s GA category (preterm or term) from the cumulative score. The validation study will be conducted in 3 secondary care hospitals (most deliveries in India occur in hospitals, and women known to be at risk of preterm birth are referred to secondary facilities). Within 24 hours of delivery, women and their babies who are stable will be enrolled in the study. Two Auxiliary Nurse Midwives (ANM) blinded to prior GA assessments will use T-SGAS to estimate the GA status of the newborn. An independent data collector will abstract the GA from the ultrasound recorded in the hospital chart and record the date of the mother’s LMP. Eligibility for analysis is determined by the ultrasound and LMP data being within 1 week of each other to have a rigorous assessment of true GA.

Results:

Publication of the results of the study is anticipated in 2018.

Conclusions:

Until GA dating by ultrasound is universally available and easy to use in resource limited settings and where use of ultrasound is restricted due to use of ultrasound for sex determination and abortion of female fetuses, this study will determine whether the T-SGAS app can accurately assess GA in risk categories at birth. Clinical Trial: NCT02408783