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

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ClinicalTrials.gov Identifier: NCT03845699
Recruitment Status : Unknown
Verified May 2019 by RTM Vital Signs, LLC.
Recruitment status was:  Recruiting
First Posted : February 19, 2019
Last Update Posted : May 9, 2019
Sponsor:
Collaborator:
Thomas Jefferson University
Information provided by (Responsible Party):
RTM Vital Signs, LLC

Brief 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.

Condition or disease Intervention/treatment
Drug Overdose Opioid-Related Disorders Device: Diagnostic algorithms that detects/predicts hypoventilation

Detailed Description:

More than 64,000 Americans died from a drug overdose in 2016 and drug overdose is now the most common cause of death for people under 50 years old in the United States. The purpose of this study is to design a wearable tracheal sound sensor and develop an experimental computer program (diagnostic algorithm) that can accurately detect and predict the onset of mild, moderate, and severe hypoventilation (slow and shallow breathing) due to an opioid (fentanyl) overdose

Opioid pain medications routinely cause a person's breathing to become slower and shallower, leading to an increased amount of carbon dioxide and decreased amount of oxygen in the bloodstream. Microphone trachea sound sensors will be used to measure and record sounds produced by air movement in and out of a person's trachea (windpipe) during inhalation and exhalation. Blood will be frequently sampled from a catheter placed within a wrist artery to measure the concentration of carbon dioxide and oxygen. An intravenous infusion of fentanyl will be used to decrease the person's respiratory rate and depth of breathing over a 1 to 3 hour period. Other sensors will be used to accurately measure and record the person's respiratory rate, tidal volume, hemoglobin oxygen saturation, electrocardiogram, blood pressure, temperature, body activity level, and body position. Each sensor's output signal will be processed and filtered to enhance the signal-to-noise ratio. The Trachea Sound Sensor and reference respiratory sensor information will be used to develop/validate risk-index algorithms that can recognize a significant change in an individual's "normal or baseline" pattern of respiratory rate, tidal volume, body activity, and body position. The hypoventilation monitoring system will not require previous knowledge of an individual's age, height, weight, model of the respiratory tract, or external calibration.

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Study Type : Observational
Estimated Enrollment : 20 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Development of an Algorithm That Predicts Hypoventilation Due to an Opioid Overdose
Estimated Study Start Date : May 15, 2019
Estimated Primary Completion Date : May 14, 2020
Estimated Study Completion Date : May 14, 2020

Resource links provided by the National Library of Medicine

Drug Information available for: Fentanyl


Intervention Details:
  • 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.
    Other Name: Infusion of fentanyl to induce hypoventilation


Primary Outcome Measures :
  1. Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Mild Hypoventilation due to an Opioid Overdose [ Time Frame: 1 to 3 hours ]
    The investigators will evaluate the risk-index algorithm's ability to detect/predict at which point during the standardized fentanyl infusion protocol does mild hypoventilation actually occur. Calculate the percent sensitivity and specificity of detecting/predicting the onset of mild hypoventilation (PaCO2- 45 to 50 mm Hg) due to a fentanyl overdose.

  2. Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Moderate Hypoventilation due to an Opioid Overdose [ Time Frame: 1 to 3 hours ]
    The investigators will evaluate the risk-index algorithm's ability to detect/predict at which point during the standardized fentanyl infusion protocol does moderate hypoventilation actually occur. Calculate the percent sensitivity and specificity of detecting/predicting the onset of mild hypoventilation (PaCO2- 51 to 60 mm Hg) due to a fentanyl overdose.

  3. Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Severe Hypoventilation due to an Opioid Overdose [ Time Frame: 1 to 3 hours ]
    The investigators will evaluate the risk-index algorithm's ability to detect/predict at which point during the standardized fentanyl infusion protocol does severe hypoventilation actually occur. Calculate the percent sensitivity and specificity of detecting/predicting the onset of severe hypoventilation (PaCO2 > 60 mm Hg) due to a fentanyl overdose.


Secondary Outcome Measures :
  1. Absolute Difference Between Trachea Sound Sensor's Measurements and Reference Sensor Measurements [ Time Frame: 1 to 3 hours ]
    Correlation between the trachea sound sensor's measurements and the reference sensor measurements of respiratory rate, tidal volume, activity level, and body position during an intravenous infusion of fentanyl (Bland-Altman plot of absolute difference).



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Ages Eligible for Study:   18 Years to 40 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
Healthy males/females of all ethnic backgrounds, 18 to 40 years of age
Criteria

Inclusion Criteria:

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

Exclusion Criteria:

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03845699


Contacts
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Contact: Stephen McNulty, DO 215-955-6161 Stephen.McNulty@Jefferson.edu
Contact: Jeffrey I Joseph, DO 215-620-9999 Jeffrey.Joseph@Jefferson.edu

Locations
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United States, Pennsylvania
Thomas Jefferson University Recruiting
Philadelphia, Pennsylvania, United States, 19107
Contact: Stephen McNulty, DO    215-955-6161    Stephen.McNulty@Jefferson.edu   
Contact: Jeffrey, DO    215-620-9999    Jeffrey.Joseph@Jefferson.edu   
Sponsors and Collaborators
RTM Vital Signs, LLC
Thomas Jefferson University
Investigators
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Principal Investigator: Stephen McNulty, DO Thomas Jefferson University
  Study Documents (Full-Text)

Documents provided by RTM Vital Signs, LLC:
Study Protocol  [PDF] February 13, 2019

Publications:
Jin F, Goh DY, Louis IM. An Enhanced Respiratory Rate Montoring Method for Real Tracheal Sound Recordings. 17 European Signal Processing Conference. 2009:642- 645.
Bureev AS, Dikman EY, Zhdanov DS, Zemlyakov IY, Kutsov MS. Mathematic Model for Spectral Characteristics of Respiratory Sounds Registered in Trachea Region. Global Journal of Pure and Applied Mathematics. 2016;12(5):4569-4578.
Lu BY. Unidirectional Microphone based Wireless Recorder for the Respiration Sound. J Bioengineer & Biomedical Sci. 2016;6(3).

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Responsible Party: RTM Vital Signs, LLC
ClinicalTrials.gov Identifier: NCT03845699    
Other Study ID Numbers: 20183438,18C.7
First Posted: February 19, 2019    Key Record Dates
Last Update Posted: May 9, 2019
Last Verified: May 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Product Manufactured in and Exported from the U.S.: No
Keywords provided by RTM Vital Signs, LLC:
Opioid Overdose
Diagnostic Algorithm
Wearable Trachea Sound Sensor
Respiratory Depression
Hypoventilation
Additional relevant MeSH terms:
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Hypoventilation
Opioid-Related Disorders
Drug Overdose
Substance-Related Disorders
Chemically-Induced Disorders
Mental Disorders
Respiratory Insufficiency
Respiration Disorders
Respiratory Tract Diseases
Signs and Symptoms, Respiratory
Fentanyl
Analgesics, Opioid
Narcotics
Central Nervous System Depressants
Physiological Effects of Drugs
Analgesics
Sensory System Agents
Peripheral Nervous System Agents
Adjuvants, Anesthesia
Anesthetics, Intravenous
Anesthetics, General
Anesthetics