Objective: Currently available gestational age scoring systems are complex and inaccurate for wider use in low- and middle-income countries (LMIC), particularly in infants with neonatal encephalopathy. Here, we aimed to develop a scoring system based on physical characteristics for identifying late preterm infants from term infants.
Study design: This was a prospective observational study conducted in 2 phases- the discovery phase and validation phase. In the first phase, we examined the accuracy of 10 objective physical characteristics in a prospective cohort of 1,006 infants recruited from three hospitals in South India. A weighted scoring system and a photo card were then developed based on the six best performing characteristics which were validated in another prospective cohort of 1,004 infants.
Results: The final score had a sensitivity of 66.0% (95% confidence intervals [CIs], 58.4-73.8%), specificity of 80.0% (95% CI, 77.2-82.7%), and a negative predictive value of 93.0% (95% CI, 90.5-94.5%).
Conclusion: This scoring system may have wider applications in LMIC, particularly in community settings and in infants with neonatal encephalopathy.
Key points: · This is an easily administered scoring system using physical characters to identify late preterm infants.. · The scoring is not affected by neurological injury and can be used in encephalopathic infants.. · Overall accuracy is better than previous scores encompassing the physical criteria alone..
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