Twitch airway pressure elicited by magnetic phrenic nerve stimulation in anesthetized healthy children.

Children with diaphragm dysfunction may be unable to maintain adequate ventilation. Accurate diagnosis is important, but can only be achieved using an appropriate test and reference range. The aim of this study, therefore, was to measure diaphragm contractility and examine the influence of age and maturation, using magnetic phrenic nerve stimulation in healthy children. Anterolateral magnetic stimulation (MS) of the phrenic nerves was performed using a 43-mm figure-eight coil in 23 children (14 male; mean age, 7.8 years; range, 1.8-15.7) anesthetized for minor surgery with sevoflurane gas. The airway was maintained with a cuffed laryngeal mask airway (LMA) which was briefly occluded during MS. Diaphragm contractility was assessed by measuring the airway pressure (TwPaw) elicited by MS. TwPaw responses were obtained in all subjects, with mean (SD) TwPaw 18.2 (6.8) cm H2O bilateral, 7.3 (3.2) cm H2O left unilateral, and 8.6 (3.1) cm H2O right unilateral. Subgroup analysis was performed in 17 of the children who were prepubertal. Their mean (SD) TwPaw was 17.3 (6.8) cm H2O bilateral, 7.1 (3.7) cm H2O left unilateral, and 8.3 (3.3) right unilateral. The mean (SD) intrapatient coefficients of variation for bilateral and left and right unilateral TwPaw were 8.4% (5.2), 6.7% (3.5), and 11.7% (10.3), respectively. Bilateral and left and right unilateral TwPaw were significantly related to age (P < 0.05). In healthy prepubertal children, diaphragm contractility is primarily influenced by age.

The Windkessel model revisited: a qualitative analysis of the circulatory system.

In this paper, we derive a comprehensive computational model to estimate the arterial pressure and the cardiac output of humans, by refining and adapting the well-established equations of the Windkessel theory. The model inputs are based on patient specific factors such as age, sex, smoking and fitness habits as well as the use of specific drugs. The model's outputs correlate very strongly with physiological observations, with a low error of approximately 5% for the arterial pressure.