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Antenatal Risk Scoring Scale for Predication of Low Birth Weight and Its Validity

Avinash Hindurao Salunkhe1, Asha K Pratinidhi2, Jyoti A Salunkhe1

  • 1Krishna Institute of Nursing Sciences, Karad, Maharashtra, India.

Indian Journal of Community Medicine : Official Publication of Indian Association of Preventive & Social Medicine
|July 24, 2019
PubMed

Insights

A new antenatal risk score helps predict low birth weight (LBW) in pregnant women. This tool aids early identification and intervention for better maternal and infant outcomes.

Area of Science:

  • Obstetrics and Gynecology
  • Public Health
  • Maternal-Fetal Medicine

Background:

  • Early prediction of low birth weight (LBW) is crucial for timely interventions.
  • Identifying at-risk pregnancies can significantly improve neonatal outcomes.

Purpose of the Study:

  • To develop and validate an antenatal risk scoring scale for predicting LBW.
  • To establish a tool for early identification of pregnancies at risk for LBW.

Main Methods:

  • Collected data on diet, occupation, and rest from 1876 pregnant women (cohort) and a subset of 380.
  • Utilized multivariate analysis and relative risks (RRs) via SPSS v16.
  • Validated the scoring system on an independent set of 251 mothers using ROC curve analysis.

Main Results:

  • Identified risk factors: infrequent meals, hard work, insufficient sleep, illiteracy, antenatal morbidity, low weight gain, low maternal weight, and anemia.
  • Developed a scoring system with a cutoff of 12 (98.6% sensitivity, 41.1% specificity).
  • A second cutoff of 15 was identified based on LBW prevalence.

Conclusions:

  • The developed antenatal risk score effectively categorizes pregnancies into low (<12), moderate (12-15), and high (>15) risk for LBW.
  • The scoring system demonstrates good sensitivity and specificity for LBW prediction.
  • This tool can aid healthcare providers in targeted interventions for high-risk pregnancies.
Abstract

Keywords:
Antenatal risk scoresattributable risklow birth weightpopulation attributable riskrelative risk

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