Gestational Age and Weight Conditions Clinical Trial
Official title:
Validation of a New Simplified Score for Assessing Gestational Age of Newborns in Community
A large number of mothers are uncertain of the date of their last menstrual period and where there is a high incidence of small-for-dates babies, there is a real need for a method of estimating gestational age that is both rapid and accurate for early referral and management of preterm newborns to reduce their mortality and morbidity. The National Family Health Survey 2005-06 reports that the proportion of low birth weight babies (LBW) in India is 22%. Of these LBW babies, the proportion of prematurity is not known in the survey as it is difficult to measure gestational age of the newborn due to lack of reliable and valid scores with ease of use at the primary health centers. Different scores to assess maturity have been developed namely New Ballard score, Dubowitz score and Meharban Singh score. It is not known whether these scores have regional, geographical, racial or ethnic robustness. It has also been found that these scores tend to overestimate newborns > 37 weeks and underestimate those >32 and < 37 weeks. The investigators conducted a cross sectional study to validate three neonatal gestational age (GA) assessment scores namely New Ballard, Dubowitz and Meharban Singh with the reference standard i.e. GA assessed by LMP using Naegeles rule and validated by gestational ages also assessed by at least one ultrasound (GA-LMP), in Indian newborns delivered at a tertiary hospital. The investigators derived a new "Simplified Gestational Age Score" (SGAS) using the best applicable items from the three validated scores and assessed its accuracy with the reference standard (GA-LMP). This score has only 4 items (posture, skin texture, breast and genital assessment) and community health workers can be trained in implementing SGAS due to its simplicity. The investigators propose a study in the GN sites to validate this simplified method of assessment of the GA using our SGAS protocol.
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Observational Model: Case-Only, Time Perspective: Cross-Sectional
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