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Prevention of Airway Obstruction Events

NCT04873024 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 15

Last updated 2024-04-19

No results posted yet for this study

Summary

The standard for treatment for people suffering from obstructive sleep apnea (OSA) syndrome involves the use of Continuous, or Automatic Positive Airway Pressure (CPAP, APAP) machines, which work by delivering air via tubing and mask to a patient at pressures of up to 20cmH2O. This increased pressure is meant to stabilize the airway to reduce obstruction events. APAP machines are generally more effective and more comfortable for patients than CPAP machines because these devices automatically adjust pressure to treat an apnea. However, this treatment is reactive and often ineffective since the necessary pressure is applied seconds after breathing has already stopped; The results of a previous study performed showed strong indications for predicting an apnea before it occurs using measurements collected by existing sensors of the CPAP and APAP machines. If apnea events can be predicted before they occur, the air pressure required to treat them could be supplied ahead of time, preventing the apnea from occurring.

The hypothesis to be tested is whether obstructive sleep apnea events can be prevented, by predicting their onset ahead of time and adjusting the airway pressure accordingly.

Conditions

  • Sleep Apnea, Mixed Central and Obstructive

Interventions

DEVICE

cMAP Flow V 2.0

Breathing data collected by the device will be processed by a machine learning algorithm to predict obstructive apnea events. When obstructive apnea events are predicted, the algorithm triggers the CPAP device to respond to the apnea event ahead of its onset. For the control treatment, the device will operate as its conventional treatment.

Sponsors & Collaborators

  • NovaResp Technologies Inc

    lead INDUSTRY

Principal Investigators

  • Debra Morrison, M.D. · Nova Scotia Health

Study Design

Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Model
CROSSOVER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-12-01
Primary Completion
2022-08-12
Completion
2022-08-12

Countries

  • Canada

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04873024 on ClinicalTrials.gov