Predicting health decline in critically ill children on ventilators using detailed physiological data.

Predicting Clinical Deterioration in Mechanically Ventilated Children using High-Frequency Physiologic Data

NIH-funded research Lurie Children's Hospital of Chicago · NIH-10985894

This study is looking to help doctors spot critically ill children in the Pediatric Intensive Care Unit who might get worse, especially those on breathing machines, by using special heart and body data to predict when they need extra care, so they can get the right treatment sooner and feel better faster.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionLurie Children's Hospital of Chicago NIH-funded
Lab location1 site (Chicago, United States)
Project IDNIH-10985894 on NIH RePORTER

What this research studies

This research focuses on identifying critically ill children in the Pediatric Intensive Care Unit (PICU) who are at risk of clinical deterioration, particularly those on mechanical ventilation. By utilizing high-frequency physiological data, such as heart rate variability, alongside clinical variables, the study aims to develop a predictive model that can accurately forecast new or worsening cardiorespiratory dysfunction. This early identification could lead to timely interventions and personalized treatment plans, ultimately improving patient outcomes. The research will involve deriving and validating this prediction model to ensure its effectiveness and acceptance among healthcare providers.

Who could benefit from this research

Good fit: Ideal candidates for this research are children aged 0-11 years who are mechanically ventilated and admitted to the PICU.

Not a fit: Patients who are not critically ill or do not require mechanical ventilation may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could significantly enhance the ability to predict and prevent serious health declines in critically ill children, potentially reducing mortality and long-term disabilities.

How similar studies have performed: Previous research has shown promise in using physiological data for predicting clinical outcomes, but this specific approach leveraging high-frequency data is relatively novel.

Where this research is happening

Chicago, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.