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Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients

NCT06395636 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 500

Last updated 2026-05-13

No results posted yet for this study

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.

Conditions

  • Appendectomy
  • Appendicitis
  • Appendicitis Acute

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.

Sponsors & Collaborators

  • Northwestern University

    collaborator OTHER

  • Central DuPage Hospital

    collaborator OTHER

  • University of Chicago

    collaborator OTHER

  • Loyola University Chicago

    collaborator OTHER

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

    lead OTHER

Principal Investigators

  • Fizan Abdullah, MD, PhD · Ann & Robert H Lurie Children's Hospital of Chicago

  • Hassan Ghomrawi, PhD, MPH · University of Alabama at Birmingham

  • Arun Jayaraman, PT, PhD · Shirley Ryan AbilityLab

Study Design

Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
SEQUENTIAL

Eligibility

Min Age
3 Years
Max Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-01-07
Primary Completion
2027-06-30
Completion
2027-06-30
FDA Device
Yes

Countries

  • United States

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06395636 on ClinicalTrials.gov