A new approach to estimating weight change and its reference intervals during the first 96 hours of life

M J Fonseca1,2, M Severo1,2, A C Santos1,2

  • 1EPIUnit - Institute of Public Health, University of Porto, Porto, Portugal.

Insights

A new model accurately estimates newborn weight change within the first 96 hours of life. It identified the weight nadir at 52.3 hours, with a mean weight ratio of 0.933.

Area of Science:

  • Neonatal research
  • Pediatric growth monitoring
  • Biostatistics

Background:

  • Accurate tracking of infant weight change is crucial for assessing health and development.
  • Existing methods may lack precision in estimating weight nadir and reference intervals during the early postnatal period.

Purpose of the Study:

  • To apply a novel longitudinal model for estimating weight change and its reference intervals in newborns up to 96 hours of life.
  • To determine the precise time of weight nadir and associated weight loss in term infants.

Main Methods:

  • Utilized data from 1288 full-term singletons in the Generation XXI birth cohort.
  • Employed longitudinal models to analyze birthweight and subsequent anthropometric measurements.
  • Calculated the weight ratio (weight at time t / birthweight) to standardize weight changes.

Main Results:

  • The developed model accurately estimated newborn weight dynamics.
  • The estimated weight nadir occurred at 52.3 hours of life, with a mean weight ratio of 0.933 (218g loss).
  • Reference intervals for weight ratios at 6, 12, 24, and 36 hours were established.

Conclusions:

  • The novel model provides a more accurate estimation of newborn weight change and reference intervals.
  • The study precisely identified the weight nadir at 52.3 hours, offering valuable clinical insights.
Abstract

Related Concept Videos

Pharmacokinetics in Pediatric Patients: Drug Distribution01:17

Pharmacokinetics in Pediatric Patients: Drug Distribution

Drug distribution in the pediatric population exhibits unique challenges and considerations due to the physiological differences between children, particularly neonates and infants, and adults. A crucial aspect of pediatric pharmacology is understanding how these differences impact the pharmacokinetics of various drugs, necessitating age-specific dosing strategies to ensure efficacy and safety.Neonates and infants have a higher total body water content, ~75%–90% of their body weight,...
513
Drug Dosing: Obese Patients01:21

Drug Dosing: Obese Patients

In the United States, obesity is a prominent concern. It is linked to heightened mortality rates due to increased occurrences of conditions such as hypertension, atherosclerosis, coronary artery disease, and diabetes compared to nonobese individuals. A patient is classified as obese if their actual body weight surpasses the ideal or desirable body weight by 20%, based on Metropolitan Life Insurance Company data. Ideal body weights consider average weights and heights for males and females...
351
Drug Dosing: Infants and Children01:29

Drug Dosing: Infants and Children

Pediatric patient dosages diverge from adults due to disparities in body surface area, total body water, and extracellular fluid per kilogram of body weight. The dosing regimen considers the variations in pharmacokinetics and pharmacology across distinct age groups, encompassing preterm newborns, infants, young children, older children, and adolescents. Calculation of pediatric patient doses is predicated on determining body surface area, which exhibits a superior correlation with the child's...
935
z Scores and Area Under the Curve01:17

z 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...
20.3K
Regression Toward the Mean01:52

Regression 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...
7.3K