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RECRUITING
NCT06395636
NA

Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients

Sponsor: Ann & Robert H Lurie Children's Hospital of Chicago

View on ClinicalTrials.gov

Summary

The purpose of this study is to analyze Fitbit data to predict infection after surgery for complicated appendicitis and the effect this prediction has on clinician decision making.

Official title: Using the Fitbit for Early Detection of Infection and Reduction of Healthcare Utilization After Discharge in Pediatric Surgical Patients

Key Details

Gender

All

Age Range

3 Years - 18 Years

Study Type

INTERVENTIONAL

Enrollment

500

Start Date

2025-01-07

Completion Date

2027-07-31

Last Updated

2026-03-19

Healthy Volunteers

No

Interventions

DEVICE

Infection-Prediction Algorithm

This machine learning algorithm will be developed(Aim1a) and validated(Aim 1b) using the participant Fitbit data and survey results collected during Aim 1. In Aim 2 the algorithm will be used in real time to predict postoperative infection.

Locations (4)

Ann & Robert H. Lurie Children's Hospital of Chicago

Chicago, Illinois, United States

Northwestern University (Feinberg School of Medicine, Shirley Ryan AbilityLab)

Chicago, Illinois, United States

Loyola University Medical Center

Maywood, Illinois, United States

Northwestern Medicine Central DuPage Hospital

Winfield, Illinois, United States