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

Respiratory Insufficiency Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT01403584
• Other study ID #: 09-4225
• Status: Completed
• Phase: N/A
• Start date: July 2011
• Est. completion date: February 2015

Study information

• Verified date: March 2021
• Source: ResMed
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 21
• Est. completion date: February 2015
• Est. primary completion date: February 2015
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 75 Years

Eligibility

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

Related Conditions & MeSH terms

• Pulmonary Valve Insufficiency
• Respiratory Aspiration
• Respiratory Insufficiency
• Sleep Apnea Syndromes
• Sleep Disordered Breathing

Intervention

Device:
• AutoVPAP with addition of AutoEPAP
Implementation of automated algorithm for adjustment of conventional device parameter (EPAP0.
• AutoVPAP with EPAP manually selected
Conventionally applied Expiratory Positive Airway Pressure (EPAP)

Locations

Country	Name	City	State
Germany	Abteilung Pneumologie - Universitätsklinik, Ruhrlandklinik	Essen

Sponsors (2)

Lead Sponsor	Collaborator
ResMed	University Hospital, Essen

Country where clinical trial is conducted

Germany, 

References & 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. Epub 2007 Feb 24. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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	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.