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

NCT01403584 | Completed Results

• 1 other identifier: 09-4225
• Study Type: interventional
• Target: 21
• Locations: 1 country
• Sites: 1

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.

Conditions

Respiratory Insufficiency; Sleep Disordered Breathing

Keywords

Breathing pattern; Gas exchange; Sleep quality

Outcome Measures

Primary Outcomes (1)

• 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 Outcomes (1)

• Mean SpO2

  On completion of each night of 2 consecutive nights polysomnography.

Study Arms (2)

AutoVPAP with addition of AutoEPAP

EXPERIMENTAL

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; Device: AutoVPAP with EPAP manually selected

AutoVPAP without addition of AutoEPAP

ACTIVE COMPARATOR

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; Device: AutoVPAP with EPAP manually selected

Interventions

AutoVPAP with addition of AutoEPAP DEVICE

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

AutoVPAP with addition of AutoEPAP; AutoVPAP without addition of AutoEPAP

AutoVPAP with EPAP manually selected DEVICE

Conventionally applied Expiratory Positive Airway Pressure (EPAP)

AutoVPAP with addition of AutoEPAP; AutoVPAP without addition of AutoEPAP

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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.

You may not qualify if:

• 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

Sponsors & Collaborators

• ResMed: lead
• University Hospital, Essen: collaborator

Study Sites (1)

Abteilung Pneumologie - Universitätsklinik, Ruhrlandklinik

Essen, 45239, Germany

Location

Related Publications (1)

• 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.

  PMID: 17323049 BACKGROUND

MeSH Terms

Conditions

Respiratory Insufficiency; Sleep Apnea Syndromes; Sleep Initiation and Maintenance Disorders

Condition Hierarchy (Ancestors)

Respiration Disorders; Respiratory Tract Diseases; Apnea; Sleep Disorders, Intrinsic; Dyssomnias; Sleep Wake Disorders; Nervous System Diseases; Mental Disorders

Limitations and Caveats

Exclusion of patients whose fundamental disorder was sleep-disordered breathing with an incidental diagnosis of COPD or of OHS and only moderate obesity, and without other supporting evidence, turned out not to be practicable for all cases.

Results Point of Contact

• Title: Prof. Helmut Teschler
• Organization: Universitätsklinik, Essen

teschlerh@t-online.de

0201 433 4001

Study Officials

• Helmut Teschler, Dr. med.

  Abteilung Pneumologie - Universitätsklinik, Essen, Germany

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: TREATMENT
• Intervention Model: CROSSOVER
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 25, 2011
• First Posted: July 27, 2011
• Study Start: July 1, 2011
• Primary Completion: February 1, 2015
• Study Completion: February 1, 2015
• Last Updated: March 26, 2021
• Results First Posted: March 26, 2021

Record last verified: 2021-03

Data Sharing

• IPD Sharing: Will not share

Locations

DE (1)