Characteristics and spectrum changes of PICU cases during the COVID-19 pandemic: a retrospective analysis

Yufan Yang1, Yueqi He1, Jiaotian Huang1

  • 1Department of Intensive Care Unit, Affiliated School of Medicine of Central South University (Hunan Children's Hospital), Changsha, Hunan, China.

PubMed

Insights

The COVID-19 pandemic reduced pediatric intensive care unit admissions and respiratory illnesses, with lower mortality. Future PICU care should prioritize respiratory, neurological, and hematological oncology systems.

Area of Science:

  • Pediatric Intensive Care
  • Epidemiology
  • Infectious Diseases

Background:

  • The COVID-19 pandemic significantly altered healthcare delivery globally.
  • Understanding its impact on pediatric critical care is crucial for adapting medical strategies.

Purpose of the Study:

  • To compare the disease spectrum of children in Pediatric Intensive Care Units (PICUs) during the COVID-19 pandemic with the pre-pandemic period.
  • To analyze the pandemic's influence on PICU patient demographics and disease patterns.

Main Methods:

  • Retrospective analysis of critically ill children admitted to Hunan Children's Hospital PICU.
  • Comparison of data from the pandemic period (2020-2022) with the pre-pandemic period (2017-2019).
  • Analysis of general characteristics, age, gender, disease spectrum, mortality, length of stay, and hospitalization costs.

Main Results:

  • A 31.62% decrease in overall PICU admissions during the pandemic.
  • A 52.78% reduction in the proportion of respiratory system diseases.
  • An 87.81% decrease in overall mortality rate.
  • Significant differences in age and gender distribution; no significant change in hospital stay duration, but altered hospitalization costs.

Conclusions:

  • The COVID-19 pandemic influenced the disease spectrum in PICU admissions.
  • Pandemic-related measures helped reduce pediatric respiratory diseases.
  • Future PICU clinical strategies should prioritize respiratory, neurological, and hematological oncology systems based on observed changes.
Abstract

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