MedTrace Logo

Development of an Algorithm That Predicts Hypoventilation Due to an Opioid Overdose

NCT03845699 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 20

Last updated 2019-05-09

No results posted yet for this study

Summary

RTM Vital Signs, LLC is developing a miniature wearable tracheal sound sensor that communicates with a cell phone containing a machine-learning diagnostic algorithm designed to detect and predict the onset of mild, moderate, and severe hypoventilation (respiratory depression) due to an opioid overdose. The purpose of this clinical trial is to develop/validate diagnostic algorithms capable of detecting/predicting the onset of hypoventilation induced by a controlled intravenous infusion of fentanyl. The wearable sensor and algorithms will provide a series of alerts and alarms to the person, caregiver, and/or emergency personnel.

Conditions

  • Drug Overdose
  • Opioid-Related Disorders

Interventions

DEVICE

Diagnostic algorithms that detects/predicts hypoventilation

Produce mild and moderate respiratory depression (hypoventilation) using a controlled intravenous infusion of fentanyl while measuring/recording respiratory rate, tidal volume, body activity, and body position.

Sponsors & Collaborators

  • Thomas Jefferson University

    collaborator OTHER

  • RTM Vital Signs, LLC

    lead INDUSTRY

Principal Investigators

  • Stephen McNulty, DO · Thomas Jefferson University

Eligibility

Min Age
18 Years
Max Age
40 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2019-05-15
Primary Completion
2020-05-14
Completion
2020-05-14

Countries

  • United States

Study Locations

More Related Trials

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 NCT03845699 on ClinicalTrials.gov