NCT01403584

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 21 (actual)
• Sponsor: ResMed · Industry
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Not accepted

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

Interventions

Type	Name	Description
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)

Timeline

• Start date: 2011-07-01
• Primary completion: 2015-02-01
• Completion: 2015-02-01
• First posted: 2011-07-27
• Last updated: 2021-03-26
• Results posted: 2021-03-26

Locations

1 site across 1 country: Germany