Related Experiment Video
Updated: May 8, 2026
04:18
Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice
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.
Indian Journal of Pediatrics
|August 17, 2013
Summary
Maternal factors like inadequate weight gain and poor diet, alongside a history of preterm or low birth weight (LBW) babies, are key predictors of LBW infants. A validated model can help predict the likelihood of having a LBW baby.
Area of Science:
- Obstetrics and Gynecology
- Neonatal Health
- Public Health
Background:
- Low birth weight (LBW) remains a significant global health concern.
- Identifying risk factors is crucial for targeted interventions.
Purpose of the Study:
- To identify factors associated with LBW.
- To develop a predictive scale for LBW infants.
Main Methods:
- Hospital-based case-control study in North India.
- 250 LBW neonates and 250 controls (birth weight ≥2,500 g).
- Data collected via maternal interviews and hospital records.
Main Results:
- Significant LBW predictors: inadequate maternal weight gain (<8.9 kg), low protein intake (<47 g/d), previous preterm/LBW baby, maternal anemia, passive smoking.
- Prediction model achieved 71.6% sensitivity and 67.0% specificity, validated at 72% sensitivity and 64% specificity.
Conclusions:
- A predictive model based on identified risk factors can effectively estimate the probability of LBW.
- This tool can aid in early identification and intervention strategies.
Related Concept Videos
01:52Regression Toward the Mean
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
01:17z Scores and Area Under the Curve
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of zero.
01:03Data Validation
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...