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

NCT ID: NCT01403584

Last Updated: 2021-03-26

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 21 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2011-07-31
• Study Completion Date: 2015-02-28

Brief Summary

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.

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.

Conditions

Respiratory Insufficiency; Sleep Disordered Breathing

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: CROSSOVER
• Primary Study Purpose: TREATMENT
• Blinding Strategy: SINGLE

Study Groups

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.

Group Type: EXPERIMENTAL

AutoVPAP with addition of AutoEPAP

Intervention Type: DEVICE

Implementation of automated algorithm for adjustment of conventional device parameter (EPAP0.

AutoVPAP with EPAP manually selected

Intervention Type: DEVICE

Conventionally applied Expiratory Positive Airway Pressure (EPAP)

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.

Group Type: ACTIVE_COMPARATOR

AutoVPAP with addition of AutoEPAP

Intervention Type: DEVICE

Implementation of automated algorithm for adjustment of conventional device parameter (EPAP0.

AutoVPAP with EPAP manually selected

Intervention Type: DEVICE

Conventionally applied Expiratory Positive Airway Pressure (EPAP)

Interventions

AutoVPAP with addition of AutoEPAP

Implementation of automated algorithm for adjustment of conventional device parameter (EPAP0.

Intervention Type: DEVICE

AutoVPAP with EPAP manually selected

Conventionally applied Expiratory Positive Airway Pressure (EPAP)

Intervention Type: DEVICE

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University Hospital, Essen

OTHER

Sponsor Role: collaborator

ResMed

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Helmut Teschler, Dr. med.

Role: PRINCIPAL_INVESTIGATOR

Abteilung Pneumologie - Universitätsklinik, Essen, Germany

Locations

Abteilung Pneumologie - Universitätsklinik, Ruhrlandklinik

Essen, , Germany

Countries

Germany

References

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.

Reference Type: BACKGROUND

PMID: 17323049 (View on PubMed)

Other Identifiers

09-4225

Identifier Type: -

Identifier Source: org_study_id