Using machine learning to predict withdrawal symptoms in critically-ill children

A Machine Learning Approach to Predicting Iatrogenic Withdrawal in Critically-ill Children

NIH-funded research Children's Research Institute · NIH-10888283

This study is looking at how to spot kids in the ICU who might have withdrawal symptoms from medications they’ve been given, so doctors can help them feel better sooner.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionChildren's Research Institute NIH-funded
Lab location1 site (Washington, United States)
Project IDNIH-10888283 on NIH RePORTER

What this research studies

This research investigates how to identify children in pediatric intensive care units (ICUs) who are at risk of experiencing withdrawal symptoms from sedative and analgesic medications. By analyzing a large database of over 200,000 pediatric ICU patients, the study aims to uncover various risk factors and patient profiles associated with iatrogenic withdrawal. The researchers will employ advanced machine learning techniques to develop a predictive model that can help healthcare providers identify at-risk children early in their treatment. This proactive approach could lead to better management and care for these vulnerable patients.

Who could benefit from this research

Good fit: Ideal candidates for this research are critically-ill children aged 0-11 years who are receiving sedative and analgesic medications in a pediatric ICU.

Not a fit: Patients who are not receiving sedative or analgesic medications in the ICU may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could significantly reduce the incidence of withdrawal symptoms in critically-ill children, leading to faster recovery and improved overall patient outcomes.

How similar studies have performed: Previous research has shown promise in using machine learning for predictive modeling in healthcare, suggesting that this approach could be effective in this context as well.

Where this research is happening

Washington, 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.