Adjustment of Mask Pressure, for Bilevel Positive Airways Pressure Therapy, by Automated Algorithm

Adjustment of Non-invasive Positive Pressure Ventilation in Patients With Chronic Hypercapnic Ventilatory Failure Using Automated End-expiratory Pressure (AutoEEP) Algorithm

The aim of the study is to test the hypothesis that an automated algorithm for desired mask pressure improves breathing pattern and sleep quality in patients with hypercapnic ventilatory failure. For this purpose, The investigators will study different groups of patients, including those with obstructive and restrictive ventilatory defect, and obstructive sleep apnoea, non-naive to conventional bi-level positive airways pressure therapy.

Study Overview

• Status: Completed
• Conditions: Respiratory Insufficiency; Sleep Disordered Breathing
• Intervention / Treatment: Device: AutoVPAP with addition of AutoEPAP; Device: AutoVPAP with EPAP manually selected

Detailed Description

Persisting ventilatory failure associated with chronic obstructive pulmonary disease (COPD), obesity-hypoventilation-syndrome, sleep apnoea or neuromuscular disease is increasingly managed with domiciliary non-invasive positive pressure ventilation (NIPPV).

Optimal settings of non-invasive ventilation are usually titrated manually and require time and expertise. The development of systems lead to automated analysis and development of algorithms to adjust ventilators. However, there is a paucity of optimal algorithms, particularly the problem of upper airway obstruction. Therefore, the central aim of this study is to develop the automated setting of an end-expiratory positive airway pressure (EPAP), because upper airway obstruction is relatively common in this group of patients. We hypothesise that an automated end-expiratory airway pressure (AutoEEP) adjusting algorithm could overcome these problems and further optimise and adjust ventilator settings. Using non-invasive ventilation in patients with hypercapnic ventilatory failure, awake and asleep, we will measure physiological outcome parameters and apply an AutoEEP algorithm, comparing it against usual care.

• Study Type: Interventional
• Enrollment (Actual): 21
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Germany
  • Essen, Germany, 45239
    • Abteilung Pneumologie - Universitätsklinik, Ruhrlandklinik

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 75 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Subjects will be patients not naive to noninvasive ventilation, and being so treated for any form of hypercapnic ventilatory failure.
• Previously stabilised on bilevel noninvasive pressure support ventilation.
• Both genders, age <75years.
• Previously shown to have a requirement for an EEP above cm H2O in order to maintain upper airway patency, or those in whom such a raised EEP would be expected, e.g. obese patients.
• Patients also known to have adequate airway patency at an EEP of 4 to 5 cm H2O will be included to ensure specificity of the algorithm.

Exclusion Criteria:

• Acute critical illness (e.g. acute coronary syndrome, stroke)
• Serious anatomical variations of nose, sinuses, pharynx or oesophagus.
• Any condition at risk of oesophageal bleeding (e.g. oesophageal varices, gastric ulcer, etc.)
• Age >75 years
• Pregnancy
• Epilepsy
• Psychiatric disorders that could possibly influence the study
• Any kind of addiction
• Insufficient knowledge of the language
• Noninvasive ventilation otherwise contraindicated

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: AutoVPAP with addition of AutoEPAP; This arm will receive conventional device modified to enable algorithm for automatically applied Expiratory Positive Airway Pressure. Patients randomised to this group will then receive the other treatment the following night.	Device: AutoVPAP with addition of AutoEPAP; Implementation of automated algorithm for adjustment of conventional device parameter (EPAP0.; Device: AutoVPAP with EPAP manually selected; Conventionally applied Expiratory Positive Airway Pressure (EPAP)
Active Comparator: AutoVPAP without addition of AutoEPAP; This arm will receive conventionally applied Expiratory Positive Airway Pressure. Patients randomised to this group will then receive the other treatment the following night.	Device: AutoVPAP with addition of AutoEPAP; Implementation of automated algorithm for adjustment of conventional device parameter (EPAP0.; Device: AutoVPAP with EPAP manually selected; Conventionally applied Expiratory Positive Airway Pressure (EPAP)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Index of Apneoas Plus Hypopnoeas Per Hour of Sleep (AHI)	The AHI is a count of the number of pauses during sleep a person experiences. The total number of apneas/ hypopneas (sleep pauses) are divided by the total sleep time to get an index for that night	On completion of each consecutive night of polysomnography.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Mean SpO2	During sleep, pulse oximetery is recorded through a sensor on the participants finger	On completion of each night of 2 consecutive nights polysomnography.

Collaborators and Investigators

• Sponsor: ResMed
• Collaborators: University Hospital, Essen
• Investigators: Principal Investigator: Helmut Teschler, Dr. med., Abteilung Pneumologie - Universitätsklinik, Essen, Germany

Publications and helpful links

General Publications

• Battisti A, Tassaux D, Bassin D, Jolliet P. Automatic adjustment of noninvasive pressure support with a bilevel home ventilator in patients with acute respiratory failure: a feasibility study. Intensive Care Med. 2007 Apr;33(4):632-8. doi: 10.1007/s00134-007-0550-1. Epub 2007 Feb 24.

Study record dates

Study Major Dates

• Study Start: July 1, 2011
• Primary Completion (Actual): February 1, 2015
• Study Completion (Actual): February 1, 2015

Study Registration Dates

• First Submitted: July 25, 2011
• First Submitted That Met QC Criteria: July 26, 2011
• First Posted (Estimate): July 27, 2011

Study Record Updates

• Last Update Posted (Actual): March 26, 2021
• Last Update Submitted That Met QC Criteria: March 2, 2021
• Last Verified: March 1, 2021

More Information

Terms related to this study

• Keywords: Sleep quality; Breathing pattern; Gas exchange
• Additional Relevant MeSH Terms: Pathologic Processes; Nervous System Diseases; Respiratory Tract Diseases; Apnea; Respiration Disorders; Sleep Disorders, Intrinsic; Dyssomnias; Sleep Wake Disorders; Sleep Apnea Syndromes; Respiratory Aspiration; Respiratory Insufficiency
• Other Study ID Numbers: 09-4225

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No