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Published on: October 10, 2025
Prediction model for low birth weight and its validation
Avantika Singh1, Sugandha Arya, Harish Chellani
1Division of Neonatology, Department of Pediatrics, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, 110029, India.
Objective:
To evaluate the factors associated with low birth weight (LBW) and to formulate a scale to predict the probability of having a LBW infant.
Methods:
This hospital based case-control study was conducted in a tertiary care university hospital in North India. The study included 250 LBW neonates and 250 neonates with birth weight ≥2,500 g. Data were collected by interviewing mothers using pre-designed structured questionnaire and from hospital records.
Results:
Factors significantly associated with LBW were inadequate weight gain by the mother during pregnancy (<8.9 kg), inadequate proteins in diet (<47 g/d), previous preterm baby, previous LBW baby, anemic mother and passive smoking. The prediction model made on these six variables has a sensitivity of 71.6 %, specificity 67.0 %, positive LR 2.17 and negative LR of 0.42 for a cut-off score of ≥29.25. On validation, it has a sensitivity of 72 % and specificity of 64 %.
Conclusions:
It is possible to predict LBW using a prediction model based on significant risk factors associated with LBW.
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