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.

Automated Quantitative Lung CT Improves Prognostication in Non-ICU COVID-19 Patients beyond Conventional Biomarkers of Disease.

(1) Background: COVID-19 continues to represent a worrying pandemic. Despite the high percentage of non-severe illness, a wide clinical variability is often reported in real-world practice. Accurate predictors of disease aggressiveness, however, are still lacking. The purpose of our study was to evaluate the impact of quantitative analysis of lung computed tomography (CT) on non-intensive care unit (ICU) COVID-19 patients' prognostication; (2) Methods: Our historical prospective study included fifty-five COVID-19 patients consecutively submitted to unenhanced lung CT. Primary outcomes were recorded during hospitalization, including composite ICU admission for the need of mechanical ventilation and/or death occurrence. CT examinations were retrospectively evaluated to automatically calculate differently aerated lung tissues (i.e., overinflated, well-aerated, poorly aerated, and non-aerated tissue). Scores based on the percentage of lung weight and volume were also calculated; (3) Results: Patients who reported disease progression showed lower total lung volume. Inflammatory indices correlated with indices of respiratory failure and high-density areas. Moreover, non-aerated and poorly aerated lung tissue resulted significantly higher in patients with disease progression. Notably, non-aerated lung tissue was independently associated with disease progression (HR: 1.02; p-value: 0.046). When different predictive models including clinical, laboratoristic, and CT findings were analyzed, the best predictive validity was reached by the model that included non-aerated tissue (C-index: 0.97; p-value: 0.0001); (4) Conclusions: Quantitative lung CT offers wide advantages in COVID-19 disease stratification. Non-aerated lung tissue is more likely to occur with severe inflammation status, turning out to be a strong predictor for disease aggressiveness; therefore, it should be included in the predictive model of COVID-19 patients.

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.