Sociodemographic Factors and Survival of Infants With Congenital Heart Defects

Nelson D Pace1,2, Matthew E Oster3,4, Nina E Forestieri2

  • 1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; npace@exponent.com.

Pediatrics
|August 17, 2018
PubMed

Insights

First-year survival for infants with congenital heart defects (CHDs) varied by defect type and socioeconomic factors. Critical univentricular CHDs had better survival, influenced by paternal age, while biventricular CHDs showed disparities linked to maternal education and race.

Area of Science:

  • Pediatric Cardiology
  • Public Health
  • Genetics

Background:

  • Congenital heart defects (CHDs) are a significant cause of infant mortality.
  • Understanding factors influencing survival is crucial for improving outcomes.

Purpose of the Study:

  • To examine first-year survival rates in infants with CHDs.
  • To investigate the impact of socioeconomic and demographic factors on infant survival with CHDs.

Main Methods:

  • Analysis of 15,533 infants with CHDs born between 2004-2013.
  • Classification of CHDs into critical univentricular, critical biventricular, and noncritical biventricular groups.
  • Utilized state vital records and census data for survival and demographic analysis.

Main Results:

  • Overall first-year mortality was 8.3% (1289 deaths).
  • Survival for univentricular defects was 61.6%, influenced by paternal age.
  • Biventricular defect survival was associated with maternal education, race, marital status, and heart center delivery, with highest mortality among non-Hispanic African American mothers.

Conclusions:

  • Survival variability for CHDs differs by defect severity and sociodemographic factors.
  • Highlights the need for culturally effective pediatric care for at-risk infants with CHDs.
Abstract

Related Concept Videos

Factors Influencing Heart Rate01:30

Factors Influencing Heart Rate

The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
6.8K
Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
721
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
433
Lumber Defects01:23

Lumber Defects

Lumber defects, which can affect both the appearance and structural integrity of wood, include a variety of growth and manufacturing flaws. Growth defects such as knots and knotholes occur where branches were once attached to the tree trunk, with knotholes forming when these knots fall out. Other natural defects include decay and insect damage, which compromise the wood's strength and durability.
Shakes are minor fractures that run along or across the wood's annual rings, while wane is...
529
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
798
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
605