Compared with PSV, NAVA increases the breathing pattern variability and complexity of flow, whereas the complexity of EAdi is unchanged. Whether this improves clinical outcomes remains to be determined.

In humans, lung ventilation exhibits breath-to-breath variability and dynamics that are nonlinear, complex, sensitive to initial conditions, unpredictable in the long-term, and chaotic. Hypercapnia, as produced by the inhalation of a CO(2)-enriched gas mixture, stimulates ventilation. Hypocapnia, as produced by mechanical hyperventilation, depresses ventilation in animals and in humans during sleep, but it does not induce apnea in awake humans. This emphasizes the suprapontine influences on ventilatory control. How cortical and subcortical commands interfere thus depend on the prevailing CO(2) levels. However, CO(2) also influences the variability and complexity of ventilation. This study was designed to describe how this occurs and to test the hypothesis that CO(2) chemoreceptors are important determinants of ventilatory dynamics. Spontaneous ventilatory flow was recorded in eight healthy subjects. Breath-by-breath variability was studied through the coefficient of variation of several ventilatory variables. Chaos was assessed with the noise titration method (noise limit) and characterized with numerical indexes [largest Lyapunov exponent (LLE), sensitivity to initial conditions; Kolmogorov-Sinai entropy (KSE), unpredictability; and correlation dimension (CD), irregularity]. In all subjects, under all conditions, a positive noise limit confirmed chaos. Hypercapnia reduced breathing variability, increased LLE (P = 0.0338 vs. normocapnia; P = 0.0018 vs. hypocapnia), increased KSE, and slightly reduced CD. Hypocapnia increased variability, decreased LLE and KSE, and reduced CD. These results suggest that chemoreceptors exert a strong influence on ventilatory variability and complexity. However, complexity persists in the quasi-absence of automatic drive. Ventilatory variability and complexity could be determined by the interaction between the respiratory central pattern generator and suprapontine structures.

Congenital central hypoventilation syndrome (CCHS) is a neurorespiratory disease characterized by life-threatening sleep-related hypoventilation involving an alteration of CO2/H(+) chemosensitivity. Incidental findings have suggested that desogestrel may allow recovery of the ventilatory response to CO2. The effects of desogestrel on resting ventilation have not been reported. This study was designed to test the hypothesis that desogestrel strengthens baseline ventilation by analyzing the ventilation of CCHS patients. Rodent models were used in order to determine the mechanisms involved. Ventilation in CCHS patients was measured with a pneumotachometer. In mice, ventilatory neural activity was recorded from ex vivo medullary-spinal cord preparations, ventilation was measured by plethysmography and c-fos expression was studied in medullary respiratory nuclei. Desogestrel increased baseline respiratory frequency of CCHS patients leading to a decrease in their PETCO2. In medullary spinal-cord preparations or in vivo mice, the metabolite of desogestrel, etonogestrel, induced an increase in respiratory frequency that necessitated the functioning of serotoninergic systems, and modulated GABAA and NMDA ventilatory regulations. c-FOS analysis showed the involvement of medullary respiratory groups of cell including serotoninergic neurons of the raphe pallidus and raphe obscurus nuclei that seem to play a key role. Thus, desogestrel may improve resting ventilation in CCHS patients by a stimulant effect on baseline respiratory frequency. Our data open up clinical perspectives based on the combination of this progestin with serotoninergic drugs to enhance ventilation in CCHS patients.

The mammalian ventilatory behaviour exhibits nonlinear dynamics as reflected by certain nonlinearity or complexity indicators (e.g. correlation dimension, approximate entropy, Lyapunov exponents...) but this is not sufficient to determine its possible chaotic nature. To address this, we applied the noise titration technique, previously shown to discern and quantify chaos in short and noisy time series, to ventilatory flow recordings obtained in quietly breathing normal humans. Nine subjects (8 men and 1 woman, 24-42 yrs) were studied during 15-minute epochs of ventilatory steadystate (10.1±3.0 breaths/minute, tidal volume 0.63±0.2L). Noise titration applied to the unfiltered signals subsampled at 5 Hz detected nonlinearity in all cases (noise limit 20.2±12.5%). Noise limit values were weakly correlated to the correlation dimension and the largest Lyapunov exponent of the signals. This study shows that the noise titration approach evidences a chaotic dimension to the behavior of ventilatory flow over time in normal humans during tidal breathing.