NCT06395636

Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients

Study Contact:

Fizan Abdullah, MD, PhD - Role: CONTACT - Phone: 312-227-4210 - Email: fabdullah@luriechildrens.org
Arianna Edobor, CRC - Role: CONTACT - Phone: 312-227-2118 - Email: idetect@luriechildrens.org

Study Phase:

Recruitment Status:

RECRUITING

NCT ID:

NCT06395636

Principal Investigator:

Study Type:

INTERVENTIONAL

Official Title:

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

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.

Eligibility

Inclusion Criteria:

* children aged 3-18 years
* must be post-surgical laparoscopic appendectomy for complicated appendicitis (Appendicitis is categorized as complicated if perforation, phlegmon, or abscess was present at surgery.)

Exclusion Criteria:

* children who are non-ambulatory or have any pre-existing mobility limitations
* children who have a doctor-ordered physical activity limit \&amp;amp;gt;48 hours post-surgery
* children who have a comorbidity which will impact a patient's recovery
* children and/or parents who do not speak English or Spanish (Translation services beyond Spanish will not be available at this time)

Disease(s) and\or Condition(s)

Appendectomy

Appendicitis

Appendicitis Acute

Primary Purpose

DIAGNOSTIC

Intervention/Treatment

- Type: DEVICE
- Name: Infection-Prediction Algorithm
- Description: 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.
- Arm Group Labels: Aim 2 - Implementation of Algorithm

Sponsor

Ann & Robert H Lurie Children's Hospital of Chicago