Long-Term Survival of Children Discharged From Pediatric Intensive Care: A Linked Data Cohort Study

Anthony Slater1,2,3, Shaila Chavan4, Elizabeth Croston5

  • 1Department of Paediatric Intensive Care Medicine, Queensland Children's Hospital, Children's Health Queensland Hospital and Health Service, South Brisbane, QLD, Australia.

Insights

Long-term survival for children discharged from pediatric intensive care units (PICUs) has improved, with a 40% reduction in mortality risk over time. Underlying conditions and geographic location impact post-discharge survival rates.

Area of Science:

  • Pediatric critical care medicine
  • Public health
  • Epidemiology

Background:

  • Long-term survival outcomes for children after pediatric intensive care unit (PICU) discharge are not well-established.
  • Factors influencing mortality post-PICU discharge require systematic investigation.

Purpose of the Study:

  • To describe the long-term survival of children discharged alive from Australian PICUs.
  • To identify factors associated with mortality following PICU discharge.

Main Methods:

  • A cohort data linkage study utilizing the Australian and New Zealand Paediatric Intensive Care Registry and the Australian National Death Index.
  • Analysis included 96,743 children discharged from Australian PICUs between 1997 and 2018.
  • Multivariable Cox proportional hazards models and Kaplan-Meier survival curves were employed.

Main Results:

  • Overall risk of death post-discharge decreased significantly over time, with a 40% reduction observed from 1997-2002 to 2014-2018.
  • Children with low-risk conditions (e.g., asthma) had a 70% lower risk of death, while those with very-high-risk conditions (e.g., malignancy) had a seven-fold increased risk.
  • Residence in outer regional and very remote areas was associated with a higher risk of death.

Conclusions:

  • Survival rates for children discharged from Australian PICUs have improved demonstrably.
  • Key factors influencing post-discharge survival include the nature of underlying diseases, patient age, and geographic location, particularly areas with limited healthcare access.
Abstract

Related Concept Videos

Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
140
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...
409
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
458
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
200
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.5K
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
256