Introduction : Les nourrissons, vu la grande compliance de leur cage thoracique, doivent maintenir activement leur volume pulmonaire de fin d’expiration (VPFE). Ceci se fait par interruption précoce de l’expiration, et par le freinage expiratoire au niveau laryngé et par la persistance de la contraction des muscles inspiratoires. Chez les nourrissons ventilés mécaniquement, notre équipe a montré que le diaphragme est activé jusqu’à la fin de l’expiration (activité tonique). Il n’est pas clair si cette activité tonique diaphragmatique compense pour l’absence de freinage laryngé liée à l’intubation endotrachéale. Objectif : Notre objectif est de déterminer si l’activité tonique diaphragmatique persiste après l’extubation chez les nourrissons et si elle peut être observée chez les enfants plus âgés. Méthode : Ceci est une étude observationnelle longitudinale prospective de patients âgés de 1 semaine à 18 ans admis aux soins intensifs pédiatriques (SIP), ventilés mécaniquement pour >24 heures et avec consentement parental. L’activité électrique du diaphragme (AEdi) a été enregistrée à l’aide d’une sonde nasogastrique spécifique à 4 moments durant le séjour aux SIP : en phase aigüe, pré et post-extubation et au congé. L’AEdi a été analysée de façon semi-automatique. L’AEdi tonique a été définie comme l’AEdi durant le dernier quartile de l’expiration. Résultats : 55 patients avec un âge médian de 10 mois (écart interquartile: 1-48) ont été étudiés. Chez les nourrissons (<1an, n=28), l’AEdi tonique en pourcentage de l’activité inspiratoire était de 48% (30-56) en phase aigüe, 38% (25-44) pré-extubation, 28% (17-42) post-extubation et 33% (22-43) au congé des SIP (p<0.05, ANOVA, avec différence significative entre enregistrements 1 et 3-4). Aucun changement significatif n’a été observé pré et post-extubation. L’AEdi tonique chez les patients plus âgés (>1an, n=27) était négligeable en phases de respiration normale (0.6mcv). Par contre, une AEdi tonique significative (>1mcv et >10%) a été observée à au moins un moment durant le séjour de 10 (37%) patients. La bronchiolite est le seul facteur indépendant associé à l’activité tonique diaphragmatique. Conclusion : Chez les nourrissons, l’AEdi tonique persiste après l’extubation et elle peut être réactivée dans certaines situations pathologiques chez les enfants plus âgés. Elle semble être un indicateur de l’effort du patient pour maintenir son VPFE. D’autres études devraient être menées afin de déterminer si la surveillance de l’AEdi tonique pourrait faciliter la détection de situations de ventilation inappropriée. / Background: Infants have to actively maintain their end expiratory lung volume (EELV) due to their high rib cage compliance. Mechanisms such as high respiratory rate, short expiratory time and laryngeal braking are implicated. In mechanically ventilated infants, the diaphragm stays activated until the end of expiration (tonic activity), contributing to EELV maintenance. It is unclear whether tonic activity compensates for the lack of laryngeal braking due to intubation or if it is normally present. Objective: To determine if tonic diaphragm activity remains after extubation in infants, and if it can be observed in older children. Methods: Prospective observational study of pediatric patients 1 week to 18 years-old ventilated for >24 hr with parental consent. Diaphragm electrical activity (EAdi) was recorded using a specific nasogastric catheter during four periods: (i) the acute phase, (ii) pre-extubation, (iii) postextubation, and (iv) at PICU discharge. EADi was analyzed in a semi-automatic manner. Tonic EAdi was defined as the EAdi in the last quartile of expiration. Results: Fifty-five patients, median age 10 months (Interquartile range: 1–48) were studied. In infants (<1 year, n=28), tonic EAdi as a percentage of inspiratory activity was 48% (30-56) in acute phase, 38% (25-44) pre-extubation, 28% (17-42) post-extubation et 33% (22-43) at PICU discharge (p<0.05, ANOVA, with statistically significant difference between recordings 1 and 3-4). No significant change was observed between pre- and post-extubation periods. In older patients (n=27), tonic activity was negligible as a whole (0.6mcv). However, significant tonic EAdi (>1mcv and >10%) was observed in 10 patients (37%). Bronchiolitis was the only independent factor associated with tonic EAdi. Conclusions: In infants, tonic EAdi remains involved in ventilatory control after extubation and restoration of laryngeal braking. Tonic EAdi can be reactivated in older patients. The interest of tonic EAdi as a tool to titrate mechanical ventilation warrants further evaluation.

Background: This work presents a generalized technique to estimate pulmonary ventilation-to-volume (v/V) distributions using the multiple-breath nitrogen washout, in which both tidal volume (VT) and the end-expiratory lung volume (EELV) are allowed to vary during the maneuver. In addition, the volume of the series dead space (vd), unlike the classical model, is considered a common series unit connected to a set of parallel alveolar units. Methods: The numerical solution for simulated data, either error-free or with the N2 measurement contaminated with the addition of Gaussian random noise of 3 or 5 % standard deviation was tested under several conditions in a computational model constituted by 50 alveolar units with unimodal and bimodal distributions of v/V. Non-negative least squares regression with Tikhonov regularization was employed for parameter retrieval. The solution was obtained with either unconstrained or constrained (VT, EELV and vd) conditions. The Tikhonov gain was fixed or estimated and a weighting matrix (WM) was considered. The quality of estimation was evaluated by the sum of the squared errors (SSE) (between reference and recovered distributions) and by the deviations of the first three moments calculated for both distributions. Additionally, a shape classification method was tested to identify the solution as unimodal or bimodal, by counting the number of shape agreements after 1000 repetitions. Results: The accuracy of the results showed a high dependence on the noise amplitude. The best algorithm for SSE and moments included the constrained and the WM solvers, whereas shape agreement improved without WM, resulting in 97.2 % for unimodal and 90.0 % for bimodal distributions in the highest noise condition. Conclusions: In conclusion this generalized method was able to identify v/V distributions from a lung model with a common series dead space even with variable VT. Although limitations remain in presence of experimental noise, appropriate combination of processing steps were also found to reduce estimation errors.

Background: This work presents a generalized technique to estimate pulmonary ventilation-to-volume (v/V) distributions using the multiple-breath nitrogen washout, in which both tidal volume (VT) and the end-expiratory lung volume (EELV) are allowed to vary during the maneuver. In addition, the volume of the series dead space (vd), unlike the classical model, is considered a common series unit connected to a set of parallel alveolar units. Methods: The numerical solution for simulated data, either error-free or with the N2 measurement contaminated with the addition of Gaussian random noise of 3 or 5 % standard deviation was tested under several conditions in a computational model constituted by 50 alveolar units with unimodal and bimodal distributions of v/V. Non-negative least squares regression with Tikhonov regularization was employed for parameter retrieval. The solution was obtained with either unconstrained or constrained (VT, EELV and vd) conditions. The Tikhonov gain was fixed or estimated and a weighting matrix (WM) was considered. The quality of estimation was evaluated by the sum of the squared errors (SSE) (between reference and recovered distributions) and by the deviations of the first three moments calculated for both distributions. Additionally, a shape classification method was tested to identify the solution as unimodal or bimodal, by counting the number of shape agreements after 1000 repetitions. Results: The accuracy of the results showed a high dependence on the noise amplitude. The best algorithm for SSE and moments included the constrained and the WM solvers, whereas shape agreement improved without WM, resulting in 97.2 % for unimodal and 90.0 % for bimodal distributions in the highest noise condition. Conclusions: In conclusion this generalized method was able to identify v/V distributions from a lung model with a common series dead space even with variable VT. Although limitations remain in presence of experimental noise, appropriate combination of processing steps were also found to reduce estimation errors.