Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients

Appendicitis Clinical Trial

— i-DETECT  

Official title:

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

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06395636
• Other study ID #: IRB 2024-6701
• Status: Not yet recruiting
• Phase: N/A
• Start date: May 2024
• Est. completion date: June 2028

Study information

• Verified date: April 2024
• Source: Ann & Robert H Lurie Children's Hospital of Chicago
• Contact: Fizan Abdullah, MD, PhD
• Phone: 312-227-4210
• Email: fabdullah[@]luriechildrens.org
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 380
• Est. completion date: June 2028
• Est. primary completion date: December 2027
• Accepts healthy volunteers: No
• Gender: All
• Age group: 3 Years to 18 Years

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 >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)

Related Conditions & MeSH terms

• Appendectomy
• Appendicitis
• Appendicitis Acute
• Infections

Intervention

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

Country	Name	City	State
United States	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

Sponsors (5)

Lead Sponsor	Collaborator
Ann & Robert H Lurie Children's Hospital of Chicago	Central DuPage Hospital, Loyola University Chicago, Northwestern University, University of Chicago

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Trends in Participant Fitbit Data (Physical Activity, Heart Rate, Sleep) during the Recovery Period post Complicated Appendectomy	Participant Fitbit data metrics (particularly PA, HR, Sleep) will be extracted from the app and analyzed using Machine Learning methods to eventually develop an algorithm to predict infection during the postoperative recovery period.	Fitbit data metrics will be collected for 30 days starting at date of enrollment.
Secondary	Number of Reported Symptoms and Complications during Recovery	Participants & Parents/Guardians will report any symptoms or complications that occur during the recovery period via a daily diary/survey.	Daily Diary/Survey Submissions will be asked to be completed daily for 30 days starting day of enrollment.
Secondary	Healthcare Utilizations during Recovery Period	The daily diary/survey will also ask Parents / Guardians of any trips to the ER, readmissions, or hospital visits relating to the participant's appendectomy.	The diary / survey will require a submission every day for 30 days starting at day of enrollment.
Secondary	Change in Clinician Decision Making from Algorithm Results	Clinicians of participants (Aim 2) will be asked if the results from the infection prediction algorithm had any impact on their clinical care decisions.	For 30 days starting at day of participant enrollment