ABSTRACT
This paper proposes a program for continuous estimation of respiratory mechanics parameters in ventilated patients. This program can be used with any ventilator providing airway pressure and flow signals without additional equipment. Overall breathing resistance, dynamic elastance (E) and positive end expiratory pressure (P(0)) are periodically estimated by multiple linear regression on selected parts of breathing cycles. Experimental validation together with justification of the selection procedure are based on signals obtained while ventilating a lung mechanical analogue with various intensive care ventilators. Clinical validity has been tested on 12 ventilated patients. The quality of estimation has been assessed by mean square difference between measured and reconstituted pressure (MSE), coefficient of determination (R(2)) and the condition number (a confidence index), and by comparison of E and P(0) with corresponding static values. The high R(2) and the low MSE obtained on most clinical cycles indicate that selected parts of cycles obey closely the model underlying parameter estimation. Agreement between static and dynamic parameters demonstrates the clinical validity of our program.
Subject(s)
Algorithms , Diagnosis, Computer-Assisted/methods , Respiration, Artificial/methods , Respiratory Mechanics , Respiratory Tract Diseases/diagnosis , Software , Aged , Aged, 80 and over , Humans , Middle Aged , Pulmonary Ventilation , Respiratory Tract Diseases/therapy , Signal Processing, Computer-Assisted , Ventilators, Mechanical/classificationABSTRACT
The instantaneous pressure applied by the respiratory muscles [Pmus(t)] of a patient under ventilatory support may be continuously assessed with the help of a model of the passive respiratory system updated cycle by cycle. Inspiratory activity (IA) is considered present when Pmus goes below a given threshold. In six patients, we compared IA with (i) inspiratory activity (IAref) obtained from esophageal pressure and diaphragmatic EMG and (ii) that (IAvent) detected by the ventilator. In any case, a ventilator support onset coincides with an IA onset but the opposite is not true. IA onset is always later than IAref beginning ((0.21 +/- 0.10 s) and IA end always precedes IAref end (0.46 +/- 0.16 s). These results clearly deteriorate when the model is not updated.
Subject(s)
Respiration, Artificial , Respiratory Distress Syndrome/physiopathology , Respiratory Muscles/physiopathology , Aged , Electromyography , Humans , Inhalation/physiology , Middle Aged , Models, Biological , Reference Values , Respiratory Distress Syndrome/therapy , Respiratory Physiological PhenomenaABSTRACT
We studied the changes in lung and upper airway mechanics in adult human subjects with obstructive sleep apnea/hypopnea syndrome (OSAHS) during wakefulness, sleep, and at arousal from sleep. We used two numerical methods that we have previously developed specifically for dealing with inspiratory flow limitation during sleep: the modified Mead-Whittenberger method, and information-weighted histograms obtained using recursive least squares. Full polysomnography including esophageal pressure and airflow measurements was performed in seven men with OSAHS (respiratory disturbance index: 55.8 +/- 23.2 events/h). Pharyngeal pressure was recorded in four of the subjects to partition lung mechanics into its upper airway and lower lung components. Both techniques showed that total lung resistance and elastance increased significantly (p < 0.05) during obstructed breathing and that this increase was reversed at the end of the obstruction. The partitioning of mechanics showed that upper airway collapse was primarily responsible for the increase in lung resistance. Our results suggest that OSAHS may lead to transient abnormalities in the recruitment of lung units and the gas exchanging capacity of the lungs.
