Respiratory Monitoring System That Detects & Predicts OIRD

Summary

This study is being conducted to evaluate the ability of the Respiratory Monitoring System (RMS) to detect and predict opioid induced respiratory depression (OIRD) in post-operative surgical patients managed with opioid medications. The ability of the RMS to detect OIRD will be compared to the detection of OIRD using a commercial capnometer, pulse oximeter, airflow monitor, and breathing volume monitor .

We hypothesize the RMS will detect the onset and progression of a true OIRD event with high sensitivity, specificity, positive predictive value, and negative predictive value. A true OIRD event will be determined by the reference device trend data.

RTM Vital Signs, LLC is developing a Respiratory Monitoring System (RMS) that consists of a wearable Trachea Sound Sensor (TSS) and a software application that measures the sounds of air flow within the trachea during inhalation and exhalation and cardiovascular sounds. The sounds of airflow in the trachea are used to continuously monitor a patient's respiratory rate (RR), relative tidal volume (TV), relative minute ventilation (MV), pattern of breathing, duration of apnea in a healthcare setting. The cardiovascular sounds are used to continuously monitor pulse rate and PR variability.

Once commercialized, clinicians will observe the RMS trend data on a smart phone, bedside display, or electronic medical record to determine whether the patient is breathing within their normal range, breathing more than their normal range (hyperventilation), breathing less than their normal range (hypoventilation), or not breathing (apnea). Real-time alerts and alarms will be based upon trends in a patient's rate and depth of breathing, number and duration of apnea events, RTM's Risk-Index-Score, and RTM's machine learning/artificial intelligence methods.

Conditions

• Respiration Disorders

Interventions

DEVICE

Study to evaluate a Respiratory Monitoring System (RMS) with a Tracheal Sound Sensor (TSS) for detecting and predicting opioid induced respiratory Depression (OIRD).

Expert clinicians will evaluate the ability of the RMS sensor and diagnostic algorithms to detect and predict true OIRD events in post-operative patients routinely managed with opioid medications. Expert clinicians will adjudicate detailed reference data and EMR data to identify a true OIRD event. The definition of a true OIRD event will be based upon the PRODIGY Study definition and RTM definition of a true event. Performance of the RMS will be based upon the sensitivity, specificity, positive predictive value, and negative predictive value for detecting true OIRD events.

Sponsors & Collaborators

• RTM Vital Signs, LLC

  collaborator INDUSTRY

• National Institute on Drug Abuse (NIDA)

  collaborator NIH

• Thomas Jefferson University

  lead OTHER

Principal Investigators

• Marc C Torjman, PhD · Thomas Jefferson University

• Jeffrey I Joseph, DO · Thomas Jefferson University

Study Design

Allocation

NA

Purpose

DIAGNOSTIC

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-01-20

Primary Completion

2026-11-30

Completion

2026-11-30

FDA Device

Yes

Countries

• United States

Study Locations