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Completed

NCT Number: NCT01403584

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

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.

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Key information

Age range

18 year–75 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Abteilung Pneumologie - Universitätsklinik, Ruhrlandklinik

Essen, 45239, Germany

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

AutoVPAP with addition of AutoEPAP

Device

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

AutoVPAP with EPAP manually selected

Device

Conventionally applied Expiratory Positive Airway Pressure (EPAP)

Primary outcomes

  1. Index of Apneoas Plus Hypopnoeas Per Hour of Sleep (AHI)

    Time frame: 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 outcomes

  1. Mean SpO2

    Time frame: On completion of each night of 2 consecutive nights polysomnography.

    During sleep, pulse oximetery is recorded through a sensor on the participants finger

Sponsors and collaborators

Lead sponsor

ResMed

Industry

Collaborators

  • University Hospital, Essen

Registry information

Official study title

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

Important dates

Study start
2011
Primary completion
2015
Study completion
2015
First posted
Jul 27, 2011
Registry last updated
Mar 26, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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