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Background: Laparoscopic surgery with pneumoperitoneum increases respiratory system elastance due to the augmented intra-abdominal pressure. We aim to evaluate to which extent positive end-expiratory pressure (PEEP) is able to counteract abdominal hypertension preventing progressive lung collapse and how rib cage elastance influences PEEP effect. Methods: Forty-four Wistar rats were mechanically ventilated and randomly assigned into three groups: control (CTRL), pneumoperitoneum (PPT) and pneumoperitoneum with restricted rib cage (PPT-RC). A pressure-volume (PV) curve followed by a recruitment maneuver and a decremental PEEP trial were performed in all groups. Thereafter, animals were ventilated using PEEP of 3 and 8 cmH2O divided into two subgroups used to evaluate respiratory mechanics or computed tomography (CT) images. In 26 rats, we compared respiratory system elastance (Ers) at the two PEEP levels. In 18 animals, CT images were acquired to calculate total lung volume (TLV), total volume and air volume in six anatomically delimited regions of interest (three along the cephalo-caudal and three along the ventro-dorsal axes). Results: PEEP of minimal Ers was similar in CTRL and PPT groups (3.8 ± 0.45 and 3.5 ± 3.89 cmH2O, respectively) and differed from PPT-RC group (9.8 ± 0.63 cmH2O). Chest restriction determined a right- and downward shift of the PV curve, increased Ers and diminished TLV and lung aeration. Increasing PEEP augmented TLV in CTRL group (11.8 ± 1.3 to 13.6 ± 2 ml, p < 0.05), and relative air content in the apex of PPT group (3.5 ± 1.4 to 4.6 ± 1.4% TLV, p < 0.03) and in the middle zones in PPT-RC group (21.4 ± 1.9 to 25.3 ± 2.1% TLV cephalo-caudally and 18.1 ± 4.3 to 22.0 ± 3.3% TLV ventro-dorsally, p < 0.005). Conclusion: Regional lung recruitment potential during pneumoperitoneum depends on rib cage elastance, reinforcing the concept of PEEP individualization according to the patient's condition.

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BACKGROUND: Expert systems can help alleviate problems related to the shortage of human resources in critical care, offering expert advice in complex situations. Expert systems use contextual information to provide advice to staff. In mechanical ventilation, it is crucial for an expert system to be able to determine the ventilatory mode in use. Different manufacturers have assigned different names to similar or even identical ventilatory modes so an expert system should be able to detect the ventilatory mode. The aim of this study is to evaluate the accuracy of an algorithm to detect the ventilatory mode in use. METHODS: We compared the results of a two-step algorithm designed to identify seven ventilatory modes. The algorithm was built into a software platform (BetterCare® system, Better Care SL; Barcelona, Spain) that acquires ventilatory signals through the data port of mechanical ventilators. The sample analyzed compared data from consecutive adult patients who underwent >24 h of mechanical ventilation in intensive care units (ICUs) at two hospitals. We used Cohen's kappa statistics to analyze the agreement between the results obtained with the algorithm and those recorded by ICU staff. RESULTS: We analyzed 486 records from 73 patients. The algorithm correctly labeled the ventilatory mode in 433 (89 %). We found an unweighted Cohen's kappa index of 84.5 % [CI (95 %) = (80.5 %: 88.4 %)]. CONCLUSIONS: The computerized algorithm can reliably identify ventilatory mode.

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BACKGROUND: Hypoxemia in acute lung injury/acute respiratory distress syndrome (ALI/ARDS) patients represents a common finding in the intensive care unit (ICU) and frequently does not respond to standard ventilatory techniques. OBJECTIVE: To study whether the early short-term application of high-frequency percussive ventilation (HFPV) can improve gas exchange in hypoxemic patients with ALI/ARDS or many other conditions in comparison to conventional ventilation (CV) using the same mean airway pressure (P(aw)), representing the main determinant of oxygenation and hemodynamics, irrespective of the mode of ventilation. METHODS: Thirty-five patients not responding to CV were studied. During the first 12 h after admission to the ICU the patients underwent CV. Thereafter HFPV was applied for 12 h with P(aw) kept constant. They were then returned to CV. Gas exchange was measured at: 12 h after admission, every 4 h during the HFPV trial, 1 h after the end of HFPV, and 12 h after HFPV. Thirty-five matched patients ventilated with CV served as the control group (CTRL). RESULTS: PaO(2)/FiO(2) and the arterial alveolar ratio (a/A PO(2)) increased during HFPV treatment and a PaO(2)/FiO(2) steady state was reached during the last 12 h of CV, whereas both did not change in CTRL. PaCO(2) decreased during the first 4 h of HFPV, but thereafter it remained unaltered; PaCO(2) did not vary in CTRL. Respiratory system compliance increased after HFPV. CONCLUSIONS: HFPV improved gas exchange in patients who did not respond to conventional treatment. This improvement remained unaltered until 12 h after the end of HFPV.

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