Effectiveness Monitoring of Home Non-invasive Mechanical Ventilation by Pressure and Flow-time Signals Analysis Integrated on Digital Diagnosis Platform.
Effectiveness Monitoring of Home Non-invasive Mechanical Ventilation by Pressure and Flow-time Signals Analysis Integrated on Digital Diagnosis Platform.
The main objective will be to determine the effectiveness of home non-invasive ventilation by flow-time and time-pressure curves analysis in a cohort of patients with this treatment by digital diagnosis platform.
A multicenter study with observational prospective design will be implemented on 3 spanish hospitals in Barcelona. Inclusion criteria will be equivalent sample size of patients with restrictive lung disease, neuromuscular pathology and hypoventilation-obesity.
Digital diagnosis platform will be used to incorporate and unify signals of different medical devices: a pneumotachograph on branch ventilator that captures pressure and flow-time signals, inductance plethysmography used to like a patient effort sensor and portable pulse oximeter recordings. Nocturnal polygraphic or polysomnographic tracings performed and recorded on sites will be processed systematically by main asynchronies diagnosis algorithms between patient and ventilator. These algorithms providing global and fractionated asynchronies count based on time, leaks or saturation criteria which will be used to compared effective ventilation phases and phases with nocturnal desaturations. Therefore, prevalence and asynchronies model on home NIV can be determine establishing the correlation between desaturation phases and respiratory events and identifying minimum tolerable leak level to keep adequate ventilation.
Inclusion Criteria:
Exclusion Criteria: