Drug OverdoseNCT03845699
Development of an Algorithm That Predicts Hypoventilation Due to an Opioid Overdose
An observational study of Drug Overdose and Opioid-Related Disorders, run by RTM Vital Signs, LLC at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 40 yearsHealthy volunteers can take part
- Conditions the study is for
- Drug Overdose, Opioid-Related Disorders
- What is being tested?
- Diagnostic algorithms that detects/predicts hypoventilation
- Type of treatment
- Injection or infusion, Medical device
- How many people
- 20 participants
- Where
- 1 siteUnited States
- Study dates
- 15 May 2019to 14 May 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 40 years
- All sexes
- Healthy volunteers accepted
- Adult
Study population: Healthy males/females of all ethnic backgrounds, 18 to 40 years of age
Who may be able to join
- 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
Who cannot join
- 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
Show all 10Show fewer
- 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.
Trial locations and contacts
1 site in 1 country.
United States1 site, 1 recruiting
- Recruiting
Thomas Jefferson University
Philadelphia, Pennsylvania, 19107
Stephen McNulty, DO, 215-955-6161, Stephen.McNulty@Jefferson.edu
Jeffrey, DO, 215-620-9999, Jeffrey.Joseph@Jefferson.edu
About this study
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.
Read the 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.
- Conditions
- Drug Overdose, Opioid-Related Disorders
- Being tested
- Diagnostic algorithms that detects/predicts hypoventilation
- Keywords
- Opioid Overdose, Diagnostic Algorithm, Wearable Trachea Sound Sensor, Respiratory Depression, Hypoventilation
- Medical subject headings
- Drug Overdose, Opioid-Related Disorders, Opiate Overdose, Respiratory Insufficiency, Hypoventilation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diagnostic algorithms that detects/predicts hypoventilationDevice
Also called Infusion of fentanyl to induce 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.
What is being measured
The primary outcome is the main question the study is designed to answer.
Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Mild Hypoventilation due to an Opioid Overdose
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.
Measured: 1 to 3 hours
Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Moderate Hypoventilation due to an Opioid Overdose
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.
Measured: 1 to 3 hours
Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Severe Hypoventilation due to an Opioid Overdose
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.
Measured: 1 to 3 hours
Secondary outcomes (1)
Absolute Difference Between Trachea Sound Sensor's Measurements and Reference Sensor Measurements
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).
Measured: 1 to 3 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Feb 2019
- Study start15 May 2019 (estimated)
- Primary completion14 May 2020 (estimated)
- Study completion14 May 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (19)Papers the sponsor has linked to this study.
- Other trials for Drug OverdoseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 20 participants (estimated)
Sponsor and investigators
- Lead sponsor
- RTM Vital Signs, LLC
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Thomas Jefferson University
- Responsible party
- Sponsor
- Investigators
- Stephen McNulty, DO, Principal investigator, Thomas Jefferson University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03845699
- Sponsor's protocol ID
- 20183438,18C.7
- Status last verified
- May 2019
- First submitted
- 16 Feb 2019
- Last updated
- 9 May 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Mildh LH, Scheinin H, Kirvela OA. The concentration-effect relationship of the respiratory depressant effects of alfentanil and fentanyl. Anesth Analg. 2001 Oct;93(4):939-46. doi: 10.1097/00000539-200110000-00028.
PubMed 11574361Boyer EW. Management of opioid analgesic overdose. N Engl J Med. 2012 Jul 12;367(2):146-55. doi: 10.1056/NEJMra1202561. No abstract available.
PubMed 22784117Volkow ND, Collins FS. The Role of Science in Addressing the Opioid Crisis. N Engl J Med. 2017 Jul 27;377(4):391-394. doi: 10.1056/NEJMsr1706626. Epub 2017 May 31. No abstract available.
PubMed 28564549Yadollahi A, Moussavi ZM. Acoustical respiratory flow. A review of reliable methods for measuring air flow. IEEE Eng Med Biol Mag. 2007 Jan-Feb;26(1):56-61. doi: 10.1109/memb.2007.289122. No abstract available.
PubMed 17278773Chen G, de la Cruz I, Rodriguez-Villegas E. Automatic lung tidal volumes estimation from tracheal sounds. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:1497-500. doi: 10.1109/EMBC.2014.6943885.
PubMed 25570253Ramsay MA, Usman M, Lagow E, Mendoza M, Untalan E, De Vol E. The accuracy, precision and reliability of measuring ventilatory rate and detecting ventilatory pause by rainbow acoustic monitoring and capnometry. Anesth Analg. 2013 Jul;117(1):69-75. doi: 10.1213/ANE.0b013e318290c798. Epub 2013 Apr 30.
PubMed 23632055Reyes BA, Reljin N, Chon KH. Tracheal sounds acquisition using smartphones. Sensors (Basel). 2014 Jul 30;14(8):13830-50. doi: 10.3390/s140813830.
PubMed 25196108Stuth EA, Stucke AG, Zuperku EJ. Effects of anesthetics, sedatives, and opioids on ventilatory control. Compr Physiol. 2012 Oct;2(4):2281-367. doi: 10.1002/cphy.c100061.
PubMed 23720250O'Croinin D, Ni Chonghaile M, Higgins B, Laffey JG. Bench-to-bedside review: Permissive hypercapnia. Crit Care. 2005 Feb;9(1):51-9. doi: 10.1186/cc2918. Epub 2004 Aug 5.
PubMed 15693984Vannucci RC, Towfighi J, Brucklacher RM, Vannucci SJ. Effect of extreme hypercapnia on hypoxic-ischemic brain damage in the immature rat. Pediatr Res. 2001 Jun;49(6):799-803. doi: 10.1203/00006450-200106000-00015.
PubMed 11385141Yu L, Ting CK, Hill BE, Orr JA, Brewer LM, Johnson KB, Egan TD, Westenskow DR. Using the entropy of tracheal sounds to detect apnea during sedation in healthy nonobese volunteers. Anesthesiology. 2013 Jun;118(6):1341-9. doi: 10.1097/ALN.0b013e318289bb30.
PubMed 23407106Penzel T, Sabil A. The use of tracheal sounds for the diagnosis of sleep apnoea. Breathe (Sheff). 2017 Jun;13(2):e37-e45. doi: 10.1183/20734735.008817.
PubMed 29184596Jin F, Goh DY, Louis IM. An Enhanced Respiratory Rate Montoring Method for Real Tracheal Sound Recordings. 17 European Signal Processing Conference. 2009:642- 645.
Harper VP, Pasterkamp H, Kiyokawa H, Wodicka GR. Modeling and measurement of flow effects on tracheal sounds. IEEE Trans Biomed Eng. 2003 Jan;50(1):1-10. doi: 10.1109/TBME.2002.807327.
PubMed 12617519Bureev 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.
Study at a glance
From the registry record, last updated by the sponsor on 9 May 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of an Algorithm That Predicts Hypoventilation Due to an Opioid Overdose
- ClinicalTrials.gov ID
- NCT03845699
- Acronym / sponsor ID
- 20183438,18C.7
- Conditions
- Drug Overdose, Opioid-Related Disorders
- Keywords
- Opioid Overdose, Diagnostic Algorithm, Wearable Trachea Sound Sensor, Respiratory Depression, Hypoventilation
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 20 participants (estimated)
- Lead sponsor
- RTM Vital Signs, LLCIndustry (pharma, biotech, devices)
- Collaborators
- Thomas Jefferson University
- Study start
- 15 May 2019 (estimated)
- Primary completion
- 14 May 2020 (estimated)
- Study completion
- 14 May 2020 (estimated)
- First posted
- 19 Feb 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 40 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- Healthy males/females of all ethnic backgrounds, 18 to 40 years of age
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (10 listed)
- 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).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Diagnostic algorithms that detects/predicts hypoventilationAlso: Infusion of fentanyl to induce hypoventilationProduce 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. | Device | – |
Primary outcome
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.
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.
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.
1 secondary outcome
Absolute Difference Between Trachea Sound Sensor's Measurements and Reference Sensor Measurements
Time frame: 1 to 3 hours
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 May 2019.
- Background: PubMed 11574361Mildh LH, Scheinin H, Kirvela OA. The concentration-effect relationship of the respiratory depressant effects of alfentanil and fentanyl. Anesth Analg. 2001 Oct;93(4):939-46. doi: 10.1097/00000539-200110000-00028.
- Background: PubMed 22784117Boyer EW. Management of opioid analgesic overdose. N Engl J Med. 2012 Jul 12;367(2):146-55. doi: 10.1056/NEJMra1202561. No abstract available.
- Background: PubMed 28564549Volkow ND, Collins FS. The Role of Science in Addressing the Opioid Crisis. N Engl J Med. 2017 Jul 27;377(4):391-394. doi: 10.1056/NEJMsr1706626. Epub 2017 May 31. No abstract available.
- Background: PubMed 17278773Yadollahi A, Moussavi ZM. Acoustical respiratory flow. A review of reliable methods for measuring air flow. IEEE Eng Med Biol Mag. 2007 Jan-Feb;26(1):56-61. doi: 10.1109/memb.2007.289122. No abstract available.
- Background: PubMed 25570253Chen G, de la Cruz I, Rodriguez-Villegas E. Automatic lung tidal volumes estimation from tracheal sounds. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:1497-500. doi: 10.1109/EMBC.2014.6943885.
- Background: PubMed 23632055Ramsay MA, Usman M, Lagow E, Mendoza M, Untalan E, De Vol E. The accuracy, precision and reliability of measuring ventilatory rate and detecting ventilatory pause by rainbow acoustic monitoring and capnometry. Anesth Analg. 2013 Jul;117(1):69-75. doi: 10.1213/ANE.0b013e318290c798. Epub 2013 Apr 30.
- Background: PubMed 25196108Reyes BA, Reljin N, Chon KH. Tracheal sounds acquisition using smartphones. Sensors (Basel). 2014 Jul 30;14(8):13830-50. doi: 10.3390/s140813830.
- Background: PubMed 23720250Stuth EA, Stucke AG, Zuperku EJ. Effects of anesthetics, sedatives, and opioids on ventilatory control. Compr Physiol. 2012 Oct;2(4):2281-367. doi: 10.1002/cphy.c100061.
- Background: PubMed 15693984O'Croinin D, Ni Chonghaile M, Higgins B, Laffey JG. Bench-to-bedside review: Permissive hypercapnia. Crit Care. 2005 Feb;9(1):51-9. doi: 10.1186/cc2918. Epub 2004 Aug 5.
- Background: PubMed 11385141Vannucci RC, Towfighi J, Brucklacher RM, Vannucci SJ. Effect of extreme hypercapnia on hypoxic-ischemic brain damage in the immature rat. Pediatr Res. 2001 Jun;49(6):799-803. doi: 10.1203/00006450-200106000-00015.
- Background: PubMed 23407106Yu L, Ting CK, Hill BE, Orr JA, Brewer LM, Johnson KB, Egan TD, Westenskow DR. Using the entropy of tracheal sounds to detect apnea during sedation in healthy nonobese volunteers. Anesthesiology. 2013 Jun;118(6):1341-9. doi: 10.1097/ALN.0b013e318289bb30.
- Background: PubMed 29184596Penzel T, Sabil A. The use of tracheal sounds for the diagnosis of sleep apnoea. Breathe (Sheff). 2017 Jun;13(2):e37-e45. doi: 10.1183/20734735.008817.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Stephen McNulty, DO principal investigator
Thomas Jefferson University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Drug Overdose and Opioid-Related Disorders, run by RTM Vital Signs, LLC at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 9 May 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Stephen McNulty, DO (215-955-6161, Stephen.McNulty@Jefferson.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Percent Sensitivity and Specificity of Detecting/Predicting the Onset of Mild Hypoventilation due to an Opioid Overdose (time frame: 1 to 3 hours). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03845699, which also lists 19 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 May 2019; AzTrials last refreshed its copy on 30 Oct 2026.