Browsing by Author "Gattarello, Simone"

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 aCO 2 ), decreased recruitability and lack of response to PEEP and prone positioning.

Abstract Background The individual components of mechanical ventilation may have distinct effects on kidney perfusion and on the risk of developing acute kidney injury; we aimed to explore ventilatory predictors of acute kidney failure and the hemodynamic changes consequent to experimental high-power mechanical ventilation. Methods Secondary analysis of two animal studies focused on the outcomes of different mechanical power settings, including 78 pigs mechanically ventilated with high mechanical power for 48 h. The animals were categorized in four groups in accordance with the RIFLE criteria for acute kidney injury (AKI), using the end-experimental creatinine: (1) NO AKI: no increase in creatinine; (2) RIFLE 1-Risk: increase of creatinine of > 50%; (3) RIFLE 2-Injury: two-fold increase of creatinine; (4) RIFLE 3-Failure: three-fold increase of creatinine; Results The main ventilatory parameter associated with AKI was the positive end-expiratory pressure (PEEP) component of mechanical power. At 30 min from the initiation of high mechanical power ventilation, the heart rate and the pulmonary artery pressure progressively increased from group NO AKI to group RIFLE 3. At 48 h, the hemodynamic variables associated with AKI were the heart rate, cardiac output, mean perfusion pressure (the difference between mean arterial and central venous pressures) and central venous pressure. Linear regression and receiving operator characteristic analyses showed that PEEP-induced changes in mean perfusion pressure (mainly due to an increase in CVP) had the strongest association with AKI. Conclusions In an experimental setting of ventilation with high mechanical power, higher PEEP had the strongest association with AKI. The most likely physiological determinant of AKI was an increase of pleural pressure and CVP with reduced mean perfusion pressure. These changes resulted from PEEP per se and from increase in fluid administration to compensate for hemodynamic impairment consequent to high PEEP;

The physiological dead space is a strong indicator of severity and outcome of acute respiratory distress syndrome (ARDS). The "ideal" alveolar PCO2, in equilibrium with pulmonary capillary PCO2, is a central concept in the physiological dead space measurement. As it cannot be measured, it is surrogated by arterial PCO2 which, unfortunately, may be far higher than ideal alveolar PCO2, when the right-to-left venous admixture is present. The "ideal" alveolar PCO2 equals the end-tidal PCO2 (PETCO2) only in absence of alveolar dead space. Therefore, in the perfect gas exchanger (alveolar dead space = 0, venous admixture = 0), the PETCO2/PaCO2 is 1, as PETCO2, PACO2 and PaCO2 are equal. Our aim is to investigate if and at which extent the PETCO2/PaCO2, a comprehensive meter of the "gas exchanger" performance, is related to the anatomo physiological characteristics in ARDS.

The amount of energy delivered to the respiratory system is recognized as a cause of Ventilator Induced Lung Injury (VILI). How energy dissipation within the lung causes damage is still a matter of debate. Expiratory flow control has been proposed as a strategy to reduce the energy dissipated into the respiratory system during expiration and, possibly, VILI. We studied 22 healthy pigs (29±2 kg), which were randomized into a control (n=11) and a valve group (n=11), where the expiratory flow was controlled through a variable resistor. Both groups were ventilated with the same tidal volume, PEEP and inspiratory flow. Electric impedance tomography was continuously acquired. At completion, lung weight, wet to dry ratios and histology were evaluated. The total mechanical power was similar in the control and valve groups (8.54±0.83 J min -1 and 8.42±0.54 J min - 1 respectively, p=0.552). The total energy dissipated within the whole system (circuit + respiratory system) was remarkably different (4.34±0.66 vs 2.62±0.31 J/min, p<0.001). However, most of this energy was dissipated across the endotracheal tube (2.87±0.3 vs 1.88±0.2 J/min, p<0.001). The amount dissipated into the respiratory system averaged 1.45±0.5 in controls vs 0.73±0.16 J min -1 in the valve group, p<0.001. Although respiratory mechanics, gas exchange, hemodynamics, wet to dry ratios and histology were similar in the two groups, the decrease of end-expiratory lung impedance was significantly greater in the control group (p=0.02). We conclude that with our experimental conditions, the reduction of energy dissipated in the respiratory system did not lead to appreciable differences in VILI.

Abstract Background To develop and validate classifier models that could be used to identify patients with a high percentage of potentially recruitable lung from readily available clinical data and from single CT scan quantitative analysis at intensive care unit admission. 221 retrospectively enrolled mechanically ventilated, sedated and paralyzed patients with acute respiratory distress syndrome (ARDS) underwent a PEEP trial at 5 and 15 cmH 2 O of PEEP and two lung CT scans performed at 5 and 45 cmH 2 O of airway pressure. Lung recruitability was defined at first as percent change in not aerated tissue between 5 and 45 cmH 2 O (radiologically defined; recruiters: Δ 45-5 non-aerated tissue  > 15%) and secondly as change in PaO 2 between 5 and 15 cmH 2 O (gas exchange-defined; recruiters: Δ 15-5 PaO2  > 24 mmHg). Four machine learning (ML) algorithms were evaluated as classifiers of radiologically defined and gas exchange-defined lung recruiters using different models including different variables, separately or combined, of lung mechanics, gas exchange and CT data. Results ML algorithms based on CT scan data at 5 cmH 2 O classified radiologically defined lung recruiters with similar AUC as ML based on the combination of lung mechanics, gas exchange and CT data. ML algorithm based on CT scan data classified gas exchange-defined lung recruiters with the highest AUC. Conclusions ML based on a single CT data at 5 cmH 2 O represented an easy-to-apply tool to classify ARDS patients in recruiters and non-recruiters according to both radiologically defined and gas exchange-defined lung recruitment within the first 48 h from the start of mechanical ventilation.

Background Under the hypothesis that mechanical power ratio could identify the spontaneously breathing patients with higher risk of respiratory failure, we assessed lung mechanics in non-intubated patients with COVID-19 pneumonia aimed at: 1) describe their characteristics; 2) compare lung mechanics between patients who received respiratory treatment escalation and those who did not; 3) identify variables associated with the need for respiratory treatment escalation. Methods Secondary analysis of prospectively enrolled cohort involving 111 consecutive spontaneously breathing adults receiving continuous positive airway pressure, enrolled from September 2020 to December 2021. Lung mechanics, other previously reported predictive indices were calculated, as well as a novel variable: the mechanical power ratio (the ratio between the actual and the expected baseline mechanical power). Patients were grouped according to the outcome: 1) no-treatment escalation (patient supported in continuous positive airway pressure until improvement); 2) treatment escalation (escalation of the respiratory support to non-invasive or invasive mechanical ventilation); and the association between lung mechanics/predictive scores and outcome was assessed. Results At day 1, patients undergoing treatment escalation had similar spontaneous tidal volume than patients who did not (7.1 ± 1.9 vs 7.1 ± 1.4 mL/KgIBW; p=0.990). In contrast, they showed higher respiratory rate (20 ± 5 vs 18 ± 5 bpm; p=0.028), minute ventilation (9.2 ± 3.0 vs 7.9 ± 2.4 L/min; p=0.011), tidal pleural pressure (8.1 ± 3.7 vs 6.0 ± 3.1 cmH2O; p=0.003), mechanical power ratio (2.4 ± 1.4 vs 1.7 ± 1.5; p=0.042) and lower PaO2/FiO2 (174 ± 64 vs 220 ± 95; p=0.007). Mechanical power (AUC 0.738 [95%CI 0.636-0.839] p<0.001), the mechanical power ratio (AUC 0.734 [95%CI 0.625-0.844] p <0.001) and the pressure-rate index (AUC 0.733 [95%CI 0.631-0.835] p <0.001) showed the highest AUC. Conclusions In this COVID-19 cohort, tidal volume was similar in patients undergoing treatment escalation and in patients who did not; mechanical power, its ratio, and pressure-rate index were the variables presenting the highest association with the clinical outcome.

Background: Ventilator-induced lung injury (VILI) via respiratory mechanics is deeply interwoven with hemodynamic, kidney and fluid/electrolyte changes. We aimed to assess the role of positive fluid balance in the framework of ventilation-induced lung injury. Methods: Post-hoc analysis of seventy-eight pigs invasively ventilated for 48 h with mechanical power ranging from 18 to 137 J/min and divided into two groups: high vs. low pleural pressure (10.0 ± 2.8 vs. 4.4 ± 1.5 cmH 2 O; p < 0.01). Respiratory mechanics, hemodynamics, fluid, sodium and osmotic balances, were assessed at 0, 6, 12, 24, 48 h. Sodium distribution between intracellular, extracellular and non-osmotic sodium storage compartments was estimated assuming osmotic equilibrium. Lung weight, wet-to-dry ratios of lung, kidney, liver, bowel and muscle were measured at the end of the experiment. Results: High pleural pressure group had significant higher cardiac output (2.96 ± 0.92 vs. 3.41 ± 1.68 L/min; p < 0.01), use of norepinephrine/epinephrine (1.76 ± 3.31 vs. 5.79 ± 9.69 mcg/kg; p < 0.01) and total fluid infusions (3.06 ± 2.32 vs. 4.04 ± 3.04 L; p < 0.01). This hemodynamic status was associated with significantly increased sodium and fluid retention (at 48 h, respectively, 601.3 ± 334.7 vs. 1073.2 ± 525.9 mmol, p < 0.01; and 2.99 ± 2.54 vs. 6.66 ± 3.87 L, p < 0.01). Ten percent of the infused sodium was stored in an osmotically inactive compartment. Increasing fluid and sodium retention was positively associated with lung-weight ( R 2 = 0.43, p < 0.01; R 2 = 0.48, p < 0.01) and with wet-to-dry ratio of the lungs ( R 2 = 0.14, p < 0.01; R 2 = 0.18, p < 0.01) and kidneys ( R 2 = 0.11, p = 0.02; R 2 = 0.12, p = 0.01). Conclusion: Increased mechanical power and pleural pressures dictated an increase in hemodynamic support resulting in proportionally increased sodium and fluid retention and pulmonary edema.

Abstract 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.

Background Despite the fervent scientific effort, a state-of-the art assessment of the different causes of hypoxemia (shunt, ventilation-perfusion mismatch and diffusion limitation) in COVID-19 ARDS is currently lacking. In this study we aimed to understand what is the relative contribution of the different mechanisms of hypoxemia in this disease and what is their relationship with the distribution of tissue and blood within the lung. Methods We prospectively enrolled 10 patients with COVID-19 ARDS, intubated for <7 days. We performed the Multiple Inert Gas Elimination Technique (MIGET) and a Dual-Energy Computed Tomography (DECT), which was quantitatively analyzed both for the tissue and blood volume. We also recorded variables related to the respiratory mechanics and invasive hemodynamics (PiCCO). Results The population (51±15 years, PaO2/FiO2 172±86 mmHg) had a mortality of 50%. MIGET showed a shunt of 25±16% and a deadspace of 53±11%. The ventilation and perfusion were mismatched (LogSD, Q 0.86±0.33). Unexpectedly, we also found evidence of diffusion limitation/post-pulmonary shunting (Predicted PaO2= 1.6*measured PaO2 - 37.5 mmHg). In the well-aerated regions, the blood volume was in excess compared to the tissue, while the opposite happened in the atelectasis. Shunt was proportional to the blood volume of the atelectasis (R 2=0.70, p=0.003). VA/QT mismatch was correlated with the blood volume of the poorly-aerated tissue (R 2=0.54, p=0.016). The overperfusion coefficient was related to PaO2/FiO2 (R 2=0.66, p=0.002), excess tissue mass (R 2=0.84, p<0.001) and to EtCO2/PaCO2 (R 2=0.63, p=0.004). Conclusions These data support the hypothesis of a highly multifactorial genesis of hypoxemia. Evidence from autoptic studies (i.e., opening of Intrapulmonary Bronchopulmonary Anastomosis) may explain the unexpected post-pulmonary shunting. The hyperperfusion might be related to the disease severity.