This narrative review focuses on thoracic ultrasonography (lung and pleural) with the aim of outlining its utility for the critical care clinician. The article summarizes the applications of thoracic ...ultrasonography for the evaluation and management of pneumothorax, pleural effusion, acute dyspnea, pulmonary edema, pulmonary embolism, pneumonia, interstitial processes, and the patient on mechanical ventilatory support. Mastery of lung and pleural ultrasonography allows the intensivist to rapidly diagnose and guide the management of a wide variety of disease processes that are common features of critical illness. Its ease of use, rapidity, repeatability, and reliability make thoracic ultrasonography the “go to” modality for imaging the lung and pleura in an efficient, cost effective, and safe manner, such that it can largely replace chest imaging in critical care practice. It is best used in conjunction with other components of critical care ultrasonography to yield a comprehensive evaluation of the critically ill patient at point of care.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Imaging has greatly contributed to the understanding of lung disease in the critically ill and currently serves as a tool to diagnose lung pathology, monitor its course, and guide clinical ...management. Lung ultrasound is a real-time imaging modality that is simple, non-invasive, potentially ubiquitous, and free of ionizing radiation. Its increasing popularity and supporting research data substantiate its role as an emerging technique for bedside chest imaging in critical care. Furthermore, the International Consensus Conference on Lung ultrasound (ICC-LUS) promoted by the World Interactive Network Focused on Critical UltraSound (WINFOCUS) recently standardized the nomenclature and technique for lung ultrasound, and provided recommendations supporting its use in clinical practice. While the utility of lung ultrasound in the emergency setting is unquestioned, its potential role in the more complex and resource-rich intensive care environment is still under investigation. The purpose of this paper was to describe current and potential uses of lung ultrasound in the specific setting of adult intensive care, with an emphasis on respiratory monitoring, and to provide a framework for the practical application of this tool at the bedside.
General anaesthesia decreases pulmonary compliance and increases pulmonary shunt due to the development of atelectasis. The presence of capnoperitoneum during laparoscopic surgery may further ...decrease functional residual capacity, promoting an increased amount of atelectasis compared with laparotomy. The aim of this study was to evaluate the effects of different levels of positive end-expiratory pressure (PEEP) in both types of surgery and to investigate whether higher levels of PEEP should be used during laparoscopic surgery.
This prospective observational study included 52 patients undergoing either laparotomy or laparoscopic surgery. Three levels of PEEP were applied in random order: (1) zero (ZEEP), (2) 5 cmH2O and (3) 10 cmH2O. Pulmonary shunt and ventilation/perfusion mismatch were assessed by the automatic lung parameter estimator system.
Pulmonary shunt was similar in both groups. However, in laparotomy, a PEEP of 5 cmH2O significantly decreased shunt when compared with ZEEP (12 vs 6%; P+0.001), with additional PEEP having no further effect. In laparoscopic surgery, a significant reduction in shunt (13 vs 6%; P+0.001) was obtained only at a PEEP of 10 cmH2O. Although laparoscopic surgery was associated with a lower pulmonary compliance, increasing levels of PEEP were able to ameliorate it in both groups.
Both surgeries have similar negative effects on pulmonary shunt, while the presence of capnoperitoneum reduced only the pulmonary compliance. It appears that a more aggressive PEEP level is required to reduce shunt and to maximize compliance in case of laparoscopic surgery.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Summary
Pulmonary complications have a significant impact on morbidity and mortality in patients after major surgery. Lung ultrasound can be used at the bed‐side, and has gained widespread acceptance ...in the intensive care unit. We conducted a prospective study to evaluate whether lung ultrasound could be used as a predictive marker for postoperative ventilatory support in high‐risk surgical patients. We included 109 patients admitted to the intensive care unit while having mechanical ventilation of the lungs following major surgery. The PaO2/FIO2 ratio was calculated on admission and an ultrasound examination performed, including: lung (‘lung ultrasound score’, number of consolidated lung areas); cardiac (mitral flow); and inferior vena cava imaging (diameter and respiratory variation). Respiratory outcomes included: the need for ventilation support (mechanical ventilation, non‐invasive ventilation or high‐flow nasal cannula oxygen therapy); acute respiratory distress syndrome; cardiogenic pulmonary oedema; and early or late pulmonary infection. Patients with a lung ultrasound score ≥ 10 had a lower PaO2/FIO2 ratio, and needed more postoperative ventilatory support, than patients with lung ultrasound score < 10. Twenty patients had acute respiratory distress syndrome, and 14 had cardiogenic pulmonary oedema. The presence of ≥ 2 areas of consolidated lung was associated with a lower PaO2/FIO2 ratio, postoperative ventilatory support, longer intensive care stay and episodes of ventilator‐associated pneumonia requiring antibiotics. Our results suggest that at intensive care unit admission, lung ultrasound scoring and detection of atelectasis can predict postoperative pulmonary outcomes after major visceral surgery, and could enhance bed‐side decision making.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•Automated methods for detection and classification of patient-ventilator asynchrony require large datasets with good-quality labels.•Realistic ventilation waveforms with labels are generated from ...simulated data by a generative-adversarial learning approach.•The generated waveforms improve the training of a machine learning algorithm for detection and classification of patient-ventilator asynchrony.•The proposed generative-adversarial approach is a promising avenue to create large datasets with good-quality labels, applicable to other domains.
Mechanical ventilation is a life-saving treatment for critically-ill patients. During treatment, patient-ventilator asynchrony (PVA) can occur, which can lead to pulmonary damage, complications, and higher mortality. While traditional detection methods for PVAs rely on visual inspection by clinicians, in recent years, machine learning models are being developed to detect PVAs automatically. However, training these models requires large labeled datasets, which are difficult to obtain, as labeling is a labour-intensive and time-consuming task, requiring clinical expertise. Simulating the lung-ventilator interactions has been proposed to obtain large labeled datasets to train machine learning classifiers. However, the obtained data lacks the influence of different hardware, of servo-controlled algorithms, and different sources of noise. Here, we propose VentGAN, an adversarial learning approach to improve simulated data by learning the ventilator fingerprints from unlabeled clinical data.
In VentGAN, the loss functions are designed to add characteristics of clinical waveforms to the generated results, while preserving the labels of the simulated waveforms. To validate VentGAN, we compare the performance for detection and classification of PVAs when training a previously developed machine learning algorithm with the original simulated data and with the data generated by VentGAN. Testing is performed on independent clinical data labeled by experts. The McNemar test is applied to evaluate statistical differences in the obtained classification accuracy.
VentGAN significantly improves the classification accuracy for late cycling, early cycling and normal breaths (p< 0.01); no significant difference in accuracy was observed for delayed inspirations (p = 0.2), while the accuracy decreased for ineffective efforts (p< 0.01).
Generation of realistic synthetic data with labels by the proposed framework is feasible and represents a promising avenue for improving training of machine learning models.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The aim of this study was to evaluate in vitro the accuracy of second generation esophageal catheters at different surrounding pressures and filling volumes and to suggest appropriate catheter ...management in clinical practice.
Six different esophageal catheters were placed in an experimental chamber at four chamber pressures (0, 10, 20 and 30 cmH2O) and at filling volumes ranging from 0 to 10 mL. The working volume was defined as the volume range between the maximum (Vmax) and minimum (Vmin) volumes achieving acceptable accuracy (defined by a balloon transmural pressure ± 1 cmH2O). Accuracy was evaluated for a standard volume of 0.5 mL and for volumes recommended by manufacturers. Data are shown as median and interquartile range.
In the four conditions of chamber pressure Vmin, Vmax and working volume were 1.0 (0.5, 1.5), 5.3 (3.8, 7.1), and 3.5 (2.9, 6.1) mL. Increasing chamber pressure increased Vmin (rho=0.9; P<0.0001), that reached 2.0 mL (1.6-2.0) at 30 cmH2O. Vmax and working volumes differed among catheters, whereas Vmin did not. By injecting 0.5 mL and the minimum recommended volume by manufacturer, balloon transmural pressure was <-1 cmH2O in 71% and 53% of cases, it was negatively related to chamber pressure (rho=-0.97 and -0.71; P<0.0001) and reached values of -10.4 (-12.4, -9.7) and -9.8 (-10.6, -3.4) at 30 cmH2O.
Measuring positive esophageal pressures needs higher injected volumes than usually recommended. The range of appropriate filling volumes is catheter-specific. Both absolute values and respiratory changes of esophageal pressure can be underestimated by an underfilled balloon.
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