Prediction model for low birth weight and its validation. Indian J Pediatr 2014 Jan;81(1):24-8
Date
08/21/2013Pubmed ID
23949869DOI
10.1007/s12098-013-1161-1Scopus ID
2-s2.0-84898888856 (requires institutional sign-in at Scopus site) 13 CitationsAbstract
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.
Author List
Singh A, Arya S, Chellani H, Aggarwal KC, Pandey RMAuthor
Avantika Singh MBBS Assistant Professor in the Neurology department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Case-Control StudiesFemale
Forecasting
Humans
Infant, Low Birth Weight
Infant, Newborn
Male
Models, Statistical
Risk Assessment
