Abstract:Acute respiratory distress syndrome (ARDS) is a severe form of respiratory failure burden by high hospital mortality. No specific pharmacologic treatment is currently available and its ventilatory management is a key strategy to allow reparative and regenerative lung tissue processes. Unfortunately, a poor management of mechanical ventilation can induce ventilation induced lung injury (VILI) caused by physical and biological forces which are at play. Different parameters have been described over the years to a… Show more
“…The pulmonary shunt computation is based on the analysis of at three sites [ 16 , 17 ]: arterialized blood in the lung capillaries after the gas exchange ( ); venous blood from the pulmonary arteries ( ); and arterial blood ( ) (Fig. 1 ) [ 8 , 18 ]. Fig.…”
Section: Pulmonary Shuntmentioning
confidence: 99%
“… Incorporating shunt assessment and its changes over time due to treatment into prognostic algorithms (e.g., machine learning) in the future, along with other parameters of gas exchange (e.g., PaO 2 /FiO 2 ) and mechanical ventilation (e.g., driving pressure) to predict prognosis or outcomes. Considering the addition of shunt computation as a routine assessment of lung injury severity [ 18 ] during the routine clinical practice, when addressing certain, defined syndromes, such as ARDS. …”
Section: Future Directionsmentioning
confidence: 99%
“…Considering the addition of shunt computation as a routine assessment of lung injury severity [ 18 ] during the routine clinical practice, when addressing certain, defined syndromes, such as ARDS.…”
Background
Pulmonary shunt refers to the passage of venous blood into the arterial blood system bypassing the alveoli-blood gas exchange. Pulmonary shunt is defined by a drop in the physiologic coupling of lung ventilation and lung perfusion. This may consequently lead to respiratory failure.
Main body
The pulmonary shunt assessment is often neglected. From a mathematical point of view, pulmonary shunt can be assessed by estimating the degree of mixing between oxygenated and deoxygenated blood. To compute the shunt, three key components are analyzed: the oxygen (O2) content in the central venous blood before gas exchange, the calculated O2 content in the pulmonary capillaries after gas exchange, and the O2 content in the arterial system, after the mixing of shunted and non-shunted blood. Computing the pulmonary shunt becomes of further importance in patients on extracorporeal membrane oxygenation (ECMO), as arterial oxygen levels may not directly reflect the gas exchange of the native lung.
Conclusion
In this review, the shunt analysis and its practical clinical applications in different scenarios are discussed by using an online shunt simulator.
Graphical Abstract
“…The pulmonary shunt computation is based on the analysis of at three sites [ 16 , 17 ]: arterialized blood in the lung capillaries after the gas exchange ( ); venous blood from the pulmonary arteries ( ); and arterial blood ( ) (Fig. 1 ) [ 8 , 18 ]. Fig.…”
Section: Pulmonary Shuntmentioning
confidence: 99%
“… Incorporating shunt assessment and its changes over time due to treatment into prognostic algorithms (e.g., machine learning) in the future, along with other parameters of gas exchange (e.g., PaO 2 /FiO 2 ) and mechanical ventilation (e.g., driving pressure) to predict prognosis or outcomes. Considering the addition of shunt computation as a routine assessment of lung injury severity [ 18 ] during the routine clinical practice, when addressing certain, defined syndromes, such as ARDS. …”
Section: Future Directionsmentioning
confidence: 99%
“…Considering the addition of shunt computation as a routine assessment of lung injury severity [ 18 ] during the routine clinical practice, when addressing certain, defined syndromes, such as ARDS.…”
Background
Pulmonary shunt refers to the passage of venous blood into the arterial blood system bypassing the alveoli-blood gas exchange. Pulmonary shunt is defined by a drop in the physiologic coupling of lung ventilation and lung perfusion. This may consequently lead to respiratory failure.
Main body
The pulmonary shunt assessment is often neglected. From a mathematical point of view, pulmonary shunt can be assessed by estimating the degree of mixing between oxygenated and deoxygenated blood. To compute the shunt, three key components are analyzed: the oxygen (O2) content in the central venous blood before gas exchange, the calculated O2 content in the pulmonary capillaries after gas exchange, and the O2 content in the arterial system, after the mixing of shunted and non-shunted blood. Computing the pulmonary shunt becomes of further importance in patients on extracorporeal membrane oxygenation (ECMO), as arterial oxygen levels may not directly reflect the gas exchange of the native lung.
Conclusion
In this review, the shunt analysis and its practical clinical applications in different scenarios are discussed by using an online shunt simulator.
Graphical Abstract
“…Lung ultrasound (LUS) is widely used as a diagnostic technique and as a guide in quick therapeutic decision making in critical care settings. It is an interesting tool in the evaluation of respiratory failure etiology [ 7 ] and has been recently demonstrated to be a useful monitoring device for the clinical history of ARDS [ 8 , 9 , 10 ].…”
Background: Noninvasive ventilation, mainly helmet CPAP, was widely used during the COVID-19 pandemic, even outside of intensive care units. Both the ROX index and the LUS score (LUSS) have been proposed as tools to predict negative outcomes in patients with hypoxemia treated with noninvasive ventilation (NIV) outside of ICUs. We aim to evaluate whether the combination of LUSS with the ROX index improves the predictive performance of these indices in patients with hypoxemia due to COVID-19 pneumonia, treated with NIV outside of ICUs. Methods: This is a monocentric prospective observational study conducted at the university teaching hospital Fondazione IRCCS San Gerardo dei Tintori (Monza, Italy) from February to April 2021. LUSS and ROX were collected at the same time in noninvasively ventilated patients outside of the ICU. An LUS exam was performed by 3 emergency medicine attending physicians with at least 5 years’ experience in point-of-care ultrasonography using a 12-zone system. To evaluate the accuracy of the prognostic indices in predicting a composite outcome (endotracheal intubation and mortality), ROC curves were used. A logistic multivariable model was used to explore the predictors of the composite outcome of endotracheal intubation and in-hospital mortality. An unadjusted Kaplan–Meier analysis was used to explore the association with the composite outcome of survival without invasive mechanical ventilation at the 30-day follow-up by stratifying the 3 indices by their best cut-offs. Results: A total of 79 patients were included in the statistical analysis and stratified into 2 groups based on the presence of a negative outcome, which was reported in 24 patients out of 79 (30%). A great proportion of patients (66 patients—84%) were treated with helmet CPAP. All three indices (LUSS, ROX and LUSS/ROX) were independently associated with negative outcomes in the multivariable analyses. Although the comparison between the AUROC of LUSS or ROX versus LUSS/ROX did not reveal a statistically significant difference, we observed a trend toward a higher accuracy for predicting negative outcomes using the LUSS/ROX index as compared to using LUSS. With the Kaplan–Maier approach, all three indices stratified by the best cut-off reported a significant association with the outcome of 30-day survival without mechanical ventilation. Conclusions: A multimodal noninvasive approach that combines ultrasound (i.e., LUSS) and a bedside clinical evaluation (i.e., the ROX index) may help clinicians to predict outcomes and to identify patients who would benefit the most from invasive respiratory support.
“…echanical ventilation plays a pivotal role in supporting lung function among critically ill patients suffering from respiratory failure (1). The need for invasive mechanical ventilation in COVID-19-induced acute respiratory distress syndrome (C-ARDS) is associated with ICU mortality ranging from 16% to 78% (2)(3)(4)(5)(6)(7).…”
OBJECTIVES:
In patients with COVID-19 respiratory failure, controlled mechanical ventilation (CMV) is often necessary during the acute phases of the disease. Weaning from CMV to pressure support ventilation (PSV) is a key objective when the patient’s respiratory functions improve. Limited evidence exists regarding the factors predicting a successful transition to PSV and its impact on patient outcomes.
DESIGN:
Retrospective observational cohort study.
SETTING:
Twenty-four Italian ICUs from February 2020 to May 2020.
PATIENTS:
Mechanically ventilated ICU patients with COVID-19-induced respiratory failure.
INTERVENTION:
The transition period from CMV to PSV was evaluated. We defined it as “failure of assisted breathing” if the patient returned to CMV within the first 72 hours.
MEASUREMENTS AND MAIN RESULTS:
Of 1260 ICU patients screened, 514 were included. Three hundred fifty-seven patients successfully made the transition to PSV, while 157 failed. Pao
2/Fio
2 ratio before the transition emerged as an independent predictor of a successful shift (odds ratio 1.00; 95% CI, 0.99–1.00; p = 0.003). Patients in the success group displayed a better trend in Pao
2/Fio
2, Paco
2, plateau and peak pressure, and pH level. Subjects in the failure group exhibited higher ICU mortality (hazard ratio 2.08; 95% CI, 1.42–3.06; p < 0.001), an extended ICU length of stay (successful vs. failure 21 ± 14 vs. 27 ± 17 d; p < 0.001) and a longer duration of mechanical ventilation (19 ± 18 vs. 24 ± 17 d, p = 0.04).
CONCLUSIONS:
Our study emphasizes that the Pao
2/Fio
2 ratio was the sole independent factor associated with a failed transition from CMV to PSV. The unsuccessful transition was associated with worse outcomes.
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