CClinicalTrials.gg
Status unknownNCT03845699Updated May 9, 2019

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

An observational study in Drug Overdose and Opioid-Related Disorders, sponsored by RTM Vital Signs, LLC. Status unknown at 1 site in United States. Open to participants aged 18 Years to 40 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2019-05-09.

Sponsored by RTM Vital Signs, LLC · Observational

The sponsor has not verified this record recently (last verified May 2019), so the status shown — last known as Recruiting — may be out of date.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
20
Ages
18 Years to 40 Years
Sex
All
01

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.

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.

02

Conditions studied

  • Drug Overdose
  • Opioid-Related Disorders

Keywords

  • Opioid Overdose
  • Diagnostic Algorithm
  • Wearable Trachea Sound Sensor
  • Respiratory Depression
  • Hypoventilation
03

In context

Hypoventilation

161 studies on the registry are indexed under Hypoventilation; 28 are open to participants now.

This study's planned enrollment of 20 is below the median of 53 across 52 observational studies indexed under Hypoventilation.

Browse Hypoventilation studies →

Lead sponsor

RTM Vital Signs, LLC is the lead sponsor of 2 studies on the registry; none are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 40 Years
Sexes eligible
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

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

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.
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Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
20 participants (estimated)
Patient registry
No

Interventions

  • DeviceDiagnostic 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.

    Also known as: Infusion of fentanyl to induce hypoventilation

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What researchers measure

Primary outcomes

  1. 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.

    Time frame: 1 to 3 hours

  2. 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.

    Time frame: 1 to 3 hours

  3. 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.

    Time frame: 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).

    Time frame: 1 to 3 hours

07

Study locations

1 of 1 sites recruiting
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References and documents

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 11574361 ↗
  • Boyer 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 22784117 ↗
  • Volkow 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 28564549 ↗
  • Yadollahi 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 17278773 ↗
  • Chen 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 25570253 ↗
  • Ramsay 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 23632055 ↗
  • Reyes BA, Reljin N, Chon KH. Tracheal sounds acquisition using smartphones. Sensors (Basel). 2014 Jul 30;14(8):13830-50. doi: 10.3390/s140813830. PubMed 25196108 ↗
  • Stuth 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 23720250 ↗
  • O'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 15693984 ↗
  • Vannucci 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 11385141 ↗
  • Yu 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 23407106 ↗
  • Penzel 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 29184596 ↗
  • 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.
  • 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 12617519 ↗
  • 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.
  • Kraman SS, Wodicka GR, Pressler GA, Pasterkamp H. Comparison of lung sound transducers using a bioacoustic transducer testing system. J Appl Physiol (1985). 2006 Aug;101(2):469-76. doi: 10.1152/japplphysiol.00273.2006. Epub 2006 Apr 20. PubMed 16627681 ↗
  • Lu BY. Unidirectional Microphone based Wireless Recorder for the Respiration Sound. J Bioengineer & Biomedical Sci. 2016;6(3).
  • Perus O, Marsot A, Ramain E, Dahman M, Paci A, Raucoules-Aime M, Simon N. Performance of alfentanil target-controlled infusion in normal and morbidly obese female patients. Br J Anaesth. 2012 Oct;109(4):551-60. doi: 10.1093/bja/aes211. Epub 2012 Jun 24. PubMed 22732112 ↗
  • Shafer SL, Varvel JR, Aziz N, Scott JC. Pharmacokinetics of fentanyl administered by computer-controlled infusion pump. Anesthesiology. 1990 Dec;73(6):1091-102. doi: 10.1097/00000542-199012000-00005. PubMed 2248388 ↗

Study documents

  • Study protocol · Feb 13, 2019

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 9, 2019, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT03845699
Lead sponsor
RTM Vital Signs, LLC
Collaborators
Thomas Jefferson University
Responsible party
Sponsor
First posted
Feb 19, 2019
Start date
May 15, 2019 (estimated)
Primary completion
May 14, 2020 (estimated)
Completion
May 14, 2020 (estimated)
Last update
May 9, 2019

Study contacts

Stephen McNulty, DO
Contact
Stephen.McNulty@Jefferson.edu
215-955-6161
Jeffrey I Joseph, DO
Contact
Jeffrey.Joseph@Jefferson.edu
215-620-9999
Stephen McNulty, DO
principal investigator · Thomas Jefferson University

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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