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

Not Applicable

Completed

Interventions: Device: AutoVPAP with addition of AutoEPAP
Device: AutoVPAP with EPAP manually selected

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.

Recruitment & 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

Arm && Interventions

Group	Intervention	Description
AutoVPAP without addition of AutoEPAP	AutoVPAP with 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.
AutoVPAP with addition of AutoEPAP	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.
AutoVPAP with addition of AutoEPAP	AutoVPAP with EPAP manually selected	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.
AutoVPAP without addition of AutoEPAP	AutoVPAP with EPAP manually selected	This arm will receive conventionally applied Expiratory Positive Airway Pressure. Patients randomised to this group will then receive the other treatment the following night.

Primary Outcome Measures

Name	Time	Method
Index of Apneoas Plus Hypopnoeas Per Hour of Sleep (AHI)	On completion of each consecutive night of polysomnography.	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

Secondary Outcome Measures

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