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

Status unconfirmed

Conditions studied: Drug Overdose, Opioid-Related Disorders

In brief

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.

Key facts

Study ID

NCT03845699

Run by

RTM Vital Signs, LLC

People needed

20

Starts

2019-05-15

Expected to finish

2020-05-14

Last updated by the study team

2019-05-09

Who can join

Age: 18 and older, up to 40. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• Healthy women/men between 18 and 40 years of age.
• Negative history of drug or alcohol abuse.
• Negative history of cigarette smoking in previous 6 months.
• Negative history of active cardiac, vascular, pulmonary, renal, hepatic, nervous, metabolic or immune disease.
• BMI < 30

You may not qualify if…

• Age < 18 years and > 40 years.
• Pregnant or planning to become pregnant.
• Positive history drug or alcohol abuse.
• Positive drug screen for opioids, benzodiazepines, hypnotics.
• Positive Drug Abuse Screening Test result (score of 6 or greater).
• BMI > 30
• History of sleep apnea.
• History of cigarette smoking in previous 6 months.
• History of difficult airway during anesthesia management.
• History of allergy or skin sensitivity to tape, silicone, fentanyl, chlorhexidine.

Where it is running

• Thomas Jefferson University — Philadelphia, Pennsylvania, United States (enrolling)

Full record on ClinicalTrials.gov

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