End-Tidal to Arterial Pco2 Ratio as Guide to Weaning from Venovenous Extracorporeal Membrane Oxygenation.

Rationale: Weaning from venovenous extracorporeal membrane oxygenation (VV-ECMO) is based on oxygenation and not on carbon dioxide elimination. Objectives: To predict readiness to wean from VV-ECMO. Methods: In this multicenter study of mechanically ventilated adults with severe acute respiratory distress syndrome receiving VV-ECMO, we investigated a variable based on CO2 elimination. The study included a prospective interventional study of a physiological cohort (n = 26) and a retrospective clinical cohort (n = 638). Measurements and Main Results: Weaning failure in the clinical and physiological cohorts were 37% and 42%, respectively. The main cause of failure in the physiological cohort was high inspiratory effort or respiratory rate. All patients exhaled similar amounts of CO2, but in patients who failed the weaning trial, [Formula: see text]e was higher to maintain the PaCO2 unchanged. The effort to eliminate one unit-volume of CO2, was double in patients who failed (68.9 [42.4-123] vs. 39 [20.1-57] cm H2O/[L/min]; P = 0.007), owing to the higher physiological Vd (68 [58.73] % vs. 54 [41.64] %; P = 0.012). End-tidal partial carbon dioxide pressure (PetCO2)/PaCO2 ratio was a clinical variable strongly associated with weaning outcome at baseline, with area under the receiver operating characteristic curve of 0.87 (95% confidence interval [CI], 0.71-1). Similarly, the PetCO2/PaCO2 ratio was associated with weaning outcome in the clinical cohort both before the weaning trial (odds ratio, 4.14; 95% CI, 1.32-12.2; P = 0.015) and at a sweep gas flow of zero (odds ratio, 13.1; 95% CI, 4-44.4; P < 0.001). Conclusions: The primary reason for weaning failure from VV-ECMO is high effort to eliminate CO2. A higher PetCO2/PaCO2 ratio was associated with greater likelihood of weaning from VV-ECMO.

Mechanisms of oxygenation responses to proning and recruitment in COVID-19 pneumonia.

PURPOSE: This study aimed at investigating the mechanisms underlying the oxygenation response to proning and recruitment maneuvers in coronavirus disease 2019 (COVID-19) pneumonia. METHODS: Twenty-five patients with COVID-19 pneumonia, at variable times since admission (from 1 to 3 weeks), underwent computed tomography (CT) lung scans, gas-exchange and lung-mechanics measurement in supine and prone positions at 5 cmH2O and during recruiting maneuver (supine, 35 cmH2O). Within the non-aerated tissue, we differentiated the atelectatic and consolidated tissue (recruitable and non-recruitable at 35 cmH2O of airway pressure). Positive/negative response to proning/recruitment was defined as increase/decrease of PaO2/FiO2. Apparent perfusion ratio was computed as venous admixture/non aerated tissue fraction. RESULTS: The average values of venous admixture and PaO2/FiO2 ratio were similar in supine-5 and prone-5. However, the PaO2/FiO2 changes (increasing in 65% of the patients and decreasing in 35%, from supine to prone) correlated with the balance between resolution of dorsal atelectasis and formation of ventral atelectasis (p = 0.002). Dorsal consolidated tissue determined this balance, being inversely related with dorsal recruitment (p = 0.012). From supine-5 to supine-35, the apparent perfusion ratio increased from 1.38 ± 0.71 to 2.15 ± 1.15 (p = 0.004) while PaO2/FiO2 ratio increased in 52% and decreased in 48% of patients. Non-responders had consolidated tissue fraction of 0.27 ± 0.1 vs. 0.18 ± 0.1 in the responding cohort (p = 0.04). Consolidated tissue, PaCO2 and respiratory system elastance were higher in patients assessed late (all p < 0.05), suggesting, all together, "fibrotic-like" changes of the lung over time. CONCLUSION: The amount of consolidated tissue was higher in patients assessed during the third week and determined the oxygenation responses following pronation and recruitment maneuvers.

Effect of the Lymphocyte Activation Gene 3 Polymorphism rs951818 on Mortality and Disease Progression in Patients with Sepsis-A Prospective Genetic Association Study.

(1) Background: Sepsis is a leading cause of death and a global public health problem. Accordingly, deciphering the underlying molecular mechanisms of this disease and the determinants of its morbidity and mortality is pivotal. This study examined the effect of the rs951818 SNP of the negative costimulatory lymphocyte-activation gene 3 (LAG-3) on sepsis mortality and disease severity. (2) Methods: 707 consecutive patients with sepsis were prospectively enrolled into the present study from three surgical ICUs at University Medical Center Goettingen. Both 28- and 90-day mortality were analyzed as the primary outcome, while parameters of disease severity served as secondary endpoints. (3) Results: In the Kaplan-Meier analysis LAG-3 rs951818 AA-homozygote patients showed a significantly lower 28-day mortality (17.3%) compared to carriers of the C-allele (23.7%, p = 0.0476). In addition, these patients more often received invasive mechanical ventilation (96%) during the course of disease than C-allele carriers (92%, p = 0.0466). (4) Conclusions: Genetic profiling of LAG-3 genetic variants alone or in combination with other genetic biomarkers may represent a promising approach for risk stratification of patients with sepsis. Patient-individual therapeutic targeting of immune checkpoints, such as LAG-3, may be a future component of sepsis therapy. Further detailed investigations in clinically relevant sepsis models are necessary.

COVID-19 pneumonia: pathophysiology and management.

Coronavirus disease 2019 (COVID-19) pneumonia is an evolving disease. We will focus on the development of its pathophysiologic characteristics over time, and how these time-related changes determine modifications in treatment. In the emergency department: the peculiar characteristic is the coexistence, in a significant fraction of patients, of severe hypoxaemia, near-normal lung computed tomography imaging, lung gas volume and respiratory mechanics. Despite high respiratory drive, dyspnoea and respiratory rate are often normal. The underlying mechanism is primarily altered lung perfusion. The anatomical prerequisites for PEEP (positive end-expiratory pressure) to work (lung oedema, atelectasis, and therefore recruitability) are lacking. In the high-dependency unit: the disease starts to worsen either because of its natural evolution or additional patient self-inflicted lung injury (P-SILI). Oedema and atelectasis may develop, increasing recruitability. Noninvasive supports are indicated if they result in a reversal of hypoxaemia and a decreased inspiratory effort. Otherwise, mechanical ventilation should be considered to avert P-SILI. In the intensive care unit: the primary characteristic of the advance of unresolved COVID-19 disease is a progressive shift from oedema or atelectasis to less reversible structural lung alterations to lung fibrosis. These later characteristics are associated with notable impairment of respiratory mechanics, increased arterial carbon dioxide tension (P aCO2 ), decreased recruitability and lack of response to PEEP and prone positioning.

Using Artificial Intelligence for Automatic Segmentation of CT Lung Images in Acute Respiratory Distress Syndrome.

Knowledge of gas volume, tissue mass and recruitability measured by the quantitative CT scan analysis (CT-qa) is important when setting the mechanical ventilation in acute respiratory distress syndrome (ARDS). Yet, the manual segmentation of the lung requires a considerable workload. Our goal was to provide an automatic, clinically applicable and reliable lung segmentation procedure. Therefore, a convolutional neural network (CNN) was used to train an artificial intelligence (AI) algorithm on 15 healthy subjects (1,302 slices), 100 ARDS patients (12,279 slices), and 20 COVID-19 (1,817 slices). Eighty percent of this populations was used for training, 20% for testing. The AI and manual segmentation at slice level were compared by intersection over union (IoU). The CT-qa variables were compared by regression and Bland Altman analysis. The AI-segmentation of a single patient required 5-10 s vs. 1-2 h of the manual. At slice level, the algorithm showed on the test set an IOU across all CT slices of 91.3 ± 10.0, 85.2 ± 13.9, and 84.7 ± 14.0%, and across all lung volumes of 96.3 ± 0.6, 88.9 ± 3.1, and 86.3 ± 6.5% for normal lungs, ARDS and COVID-19, respectively, with a U-shape in the performance: better in the lung middle region, worse at the apex and base. At patient level, on the test set, the total lung volume measured by AI and manual segmentation had a R 2 of 0.99 and a bias -9.8 ml [CI: +56.0/-75.7 ml]. The recruitability measured with manual and AI-segmentation, as change in non-aerated tissue fraction had a bias of +0.3% [CI: +6.2/-5.5%] and -0.5% [CI: +2.3/-3.3%] expressed as change in well-aerated tissue fraction. The AI-powered lung segmentation provided fast and clinically reliable results. It is able to segment the lungs of seriously ill ARDS patients fully automatically.

Role of total lung stress on the progression of early COVID-19 pneumonia.

PURPOSE: We investigated if the stress applied to the lung during non-invasive respiratory support may contribute to the coronavirus disease 2019 (COVID-19) progression. METHODS: Single-center, prospective, cohort study of 140 consecutive COVID-19 pneumonia patients treated in high-dependency unit with continuous positive airway pressure (n = 131) or non-invasive ventilation (n = 9). We measured quantitative lung computed tomography, esophageal pressure swings and total lung stress. RESULTS: Patients were divided in five subgroups based on their baseline PaO2/FiO2 (day 1): non-CARDS (median PaO2/FiO2 361 mmHg, IQR [323-379]), mild (224 mmHg [211-249]), mild-moderate (173 mmHg [164-185]), moderate-severe (126 mmHg [114-138]) and severe (88 mmHg [86-99], p < 0.001). Each subgroup had similar median lung weight: 1215 g [1083-1294], 1153 [888-1321], 968 [858-1253], 1060 [869-1269], and 1127 [937-1193] (p = 0.37). They also had similar non-aerated tissue fraction: 10.4% [5.9-13.7], 9.6 [7.1-15.8], 9.4 [5.8-16.7], 8.4 [6.7-12.3] and 9.4 [5.9-13.8], respectively (p = 0.85). Treatment failure of CPAP/NIV occurred in 34 patients (24.3%). Only three variables, at day one, distinguished patients with negative outcome: PaO2/FiO2 ratio (OR 0.99 [0.98-0.99], p = 0.02), esophageal pressure swing (OR 1.13 [1.01-1.27], p = 0.032) and total stress (OR 1.17 [1.06-1.31], p = 0.004). When these three variables were evaluated together in a multivariate logistic regression analysis, only the total stress was independently associated with negative outcome (OR 1.16 [1.01-1.33], p = 0.032). CONCLUSIONS: In early COVID-19 pneumonia, hypoxemia is not linked to computed tomography (CT) pathoanatomy, differently from typical ARDS. High lung stress was independently associated with the failure of non-invasive respiratory support.

A Potential Role of the Renin-Angiotensin-System for Disturbances of Respiratory Chemosensitivity in Acute Respiratory Distress Syndrome and Severe Acute Respiratory Syndrome.

Acute respiratory distress syndrome (ARDS) represents an acute diffuse inflammation of the lungs triggered by different causes, uniformly leading to a noncardiogenic pulmonary edema with inhomogeneous densities in lung X-ray and lung CT scan and acute hypoxemia. Edema formation results in "heavy" lungs, inducing loss of compliance and the need to spend more energy to "move" the lungs. Consequently, an ARDS patient, as long as the patient is breathing spontaneously, has an increased respiratory drive to ensure adequate oxygenation and CO2 removal. One would expect that, once the blood gases get back to "physiological" values, the respiratory drive would normalize and the breathing effort return to its initial status. However, in many ARDS patients, this is not the case; their respiratory drive appears to be upregulated and fully or at least partially detached from the blood gas status. Strikingly, similar alteration of the respiratory drive can be seen in patients suffering from SARS, especially SARS-Covid-19. We hypothesize that alterations of the renin-angiotensin-system (RAS) related to the pathophysiology of ARDS and SARS are involved in this dysregulation of chemosensitive control of breathing.

The impact of ventilation-perfusion inequality in COVID-19: a computational model.

COVID-19 infection may lead to acute respiratory distress syndrome (CARDS) where severe gas exchange derangements may be associated, at least in the early stages, only with minor pulmonary infiltrates. This may suggest that the shunt associated to the gasless lung parenchyma is not sufficient to explain CARDS hypoxemia. We designed an algorithm (VentriQlar), based on the same conceptual grounds described by J.B. West in 1969. We set 498 ventilation-perfusion (VA/Q) compartments and, after calculating their blood composition (PO2, PCO2, and pH), we randomly chose 106 combinations of five parameters controlling a bimodal distribution of blood flow. The solutions were accepted if the predicted PaO2 and PaCO2 were within 10% of the patient's values. We assumed that the shunt fraction equaled the fraction of non-aerated lung tissue at the CT quantitative analysis. Five critically-ill patients later deceased were studied. The PaO2/FiO2 was 91.1 ± 18.6 mmHg and PaCO2 69.0 ± 16.1 mmHg. Cardiac output was 9.58 ± 0.99 L/min. The fraction of non-aerated tissue was 0.33 ± 0.06. The model showed that a large fraction of the blood flow was likely distributed in regions with very low VA/Q (Qmean = 0.06 ± 0.02) and a smaller fraction in regions with moderately high VA/Q. Overall LogSD, Q was 1.66 ± 0.14, suggestive of high VA/Q inequality. Our data suggest that shunt alone cannot completely account for the observed hypoxemia and a significant VA/Q inequality must be present in COVID-19. The high cardiac output and the extensive microthrombosis later found in the autopsy further support the hypothesis of a pathological perfusion of non/poorly ventilated lung tissue.NEW & NOTEWORTHY Hypothesizing that the non-aerated lung fraction as evaluated by the quantitative analysis of the lung computed tomography (CT) equals shunt (VA/Q = 0), we used a computational approach to estimate the magnitude of the ventilation-perfusion inequality in severe COVID-19. The results show that a severe hyperperfusion of poorly ventilated lung region is likely the cause of the observed hypoxemia. The extensive microthrombosis or abnormal vasodilation of the pulmonary circulation may represent the pathophysiological mechanism of such VA/Q distribution.

Physiological and quantitative CT-scan characterization of COVID-19 and typical ARDS: a matched cohort study.

PURPOSE: To investigate whether COVID-19-ARDS differs from all-cause ARDS. METHODS: Thirty-two consecutive, mechanically ventilated COVID-19-ARDS patients were compared to two historical ARDS sub-populations 1:1 matched for PaO2/FiO2 or for compliance of the respiratory system. Gas exchange, hemodynamics and respiratory mechanics were recorded at 5 and 15 cmH2O PEEP. CT scan variables were measured at 5 cmH2O PEEP. RESULTS: Anthropometric characteristics were similar in COVID-19-ARDS, PaO2/FiO2-matched-ARDS and Compliance-matched-ARDS. The PaO2/FiO2-matched-ARDS and COVID-19-ARDS populations (both with PaO2/FiO2 106 ± 59 mmHg) had different respiratory system compliances (Crs) (39 ± 11 vs 49.9 ± 15.4 ml/cmH2O, p = 0.03). The Compliance-matched-ARDS and COVID-19-ARDS had similar Crs (50.1 ± 15.7 and 49.9 ± 15.4 ml/cmH2O, respectively) but significantly lower PaO2/FiO2 for the same Crs (160 ± 62 vs 106.5 ± 59.6 mmHg, p < 0.001). The three populations had similar lung weights but COVID-19-ARDS had significantly higher lung gas volume (PaO2/FiO2-matched-ARDS 930 ± 644 ml, COVID-19-ARDS 1670 ± 791 ml and Compliance-matched-ARDS 1301 ± 627 ml, p < 0.05). The venous admixture was significantly related to the non-aerated tissue in PaO2/FiO2-matched-ARDS and Compliance-matched-ARDS (p < 0.001) but unrelated in COVID-19-ARDS (p = 0.75), suggesting that hypoxemia was not only due to the extent of non-aerated tissue. Increasing PEEP from 5 to 15 cmH2O improved oxygenation in all groups. However, while lung mechanics and dead space improved in PaO2/FiO2-matched-ARDS, suggesting recruitment as primary mechanism, they remained unmodified or worsened in COVID-19-ARDS and Compliance-matched-ARDS, suggesting lower recruitment potential and/or blood flow redistribution. CONCLUSIONS: COVID-19-ARDS is a subset of ARDS characterized overall by higher compliance and lung gas volume for a given PaO2/FiO2, at least when considered within the timeframe of our study.