Microcirculatory alterations in critically ill COVID-19 patients analyzed using artificial intelligence.

BACKGROUND: The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that supervised deep machine learning could be used to identify previously unknown microcirculatory alterations, and combination with algorithmically quantified functional variables increases the model's performance to differentiate critically ill COVID-19 patients from healthy volunteers. METHODS: Four international, multi-central cohorts of critically ill COVID-19 patients and healthy volunteers (n = 59/n = 40) were used for neuronal network training and internal validation, alongside quantification of functional microcirculatory hemodynamic variables. Independent verification of the models was performed in a second cohort (n = 25/n = 33). RESULTS: Six thousand ninety-two image sequences in 157 individuals were included. Bootstrapped internal validation yielded AUROC(CI) for detection of COVID-19 status of 0.75 (0.69-0.79), 0.74 (0.69-0.79) and 0.84 (0.80-0.89) for the algorithm-based, deep learning-based and combined models. Individual model performance in external validation was 0.73 (0.71-0.76) and 0.61 (0.58-0.63). Combined neuronal network and algorithm-based identification yielded the highest externally validated AUROC of 0.75 (0.73-0.78) (P < 0.0001 versus internal validation and individual models). CONCLUSIONS: We successfully trained a deep learning-based model to differentiate critically ill COVID-19 patients from heathy volunteers in sublingual HVM image sequences. Internally validated, deep learning was superior to the algorithmic approach. However, combining the deep learning method with an algorithm-based approach to quantify the functional state of the microcirculation markedly increased the sensitivity and specificity as compared to either approach alone, and enabled successful external validation of the identification of the presence of microcirculatory alterations associated with COVID-19 status.

Case report: Microcirculatory leukocytes in a pediatric patient with severe SARS-CoV-2 pneumonia. Findings of leukocytes trafficking beyond the lungs

Background SARS-CoV-2 can lead to excessive coagulation and thrombo-inflammation with deposition of microthrombi and microvascular dysfunction. Several studies in human and animal models have already evidenced biomarkers of endothelial injury during SARS-CoV-2 infection. Real-time observation of sublingual microcirculation using an handheld vital microscopy with an Incident Dark Field (IDF) technique could represent a non-invasive way to assess early signs of microvascular dysfunction and endothelial inflammation in patients with severe COVID-19 infection. Clinical case We report for the first time in a pediatric patient with severe SARS-CoV-2 pneumonia findings about microcirculatory leukocytes in the sublingual microcirculation of a 7 month-old patient admitted to our PICU using handheld vital microscopy with IDF technique. Results Sublingual microcirculation analysis revealed the presence of microcirculatory alterations and an extensive presence of leukocytes in the patient’s sublingual microcirculation. It’s significant to underline how the patient didn’t show a contextual significant increase in inflammatory biomarkers or other clinical signs related to an inflammatory response, beyond the presence of severe hypoxic respiratory failure. Conclusion Leukocyte activation in multiple organs can occur at the endothelial lining of the microvasculature where a surge of pro-inflammatory mediators can result in accumulation of activated leukocytes and degradation of the endothelium. The introduction of a method to assess in a non-invasive, real-time manner the extent of inflammation in a patient with COVID19 could lead to potential clinical and therapeutic implications. However, more studies are required to prove that studying leukocytes microcirculation using sublingual microcirculation analysis could be useful as a bedside point of care monitor to predict the presence of systemic inflammation associated with the impact of COVID-19, leading in a late phase of severe SARS-CoV-2 infection to a microvascular dysfunction and micro-thrombosis.

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients.

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary outcome the increase or decrease in patients' Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs. 0.69, P < 0.01 [paired t-test with 95% confidence interval]). Conclusions: The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources.

Cardio-Pulmonary-Renal Consequences of Severe COVID-19.

Severe acute respiratory syndrome coronavirus 2 has rapidly spread worldwide and resulted in the coronavirus disease 2019 (COVID-19) pandemic. The disease raised an unprecedented demand for intensive care support due to severe pulmonary dysfunction and multiorgan failure. Although the pulmonary system is the potential target of the COVID-19, recent reports have demonstrated that COVID-19 profoundly influences the cardiovascular system and the kidneys. Research studies on cadavers have shown that direct heart and kidney injury can be frequently seen in patients deceased due to COVID-19 infection. On the other hand, functional or structural dysfunction of the heart may deteriorate the renal function and vice versa. This concept is already known as the cardiorenal syndrome and may play a role in COVID-19. Proactive monitoring of micro- and macrohemodynamics could allow prompt correction of circulatory dysfunction and can be of pivotal importance in the prevention of acute kidney injury. Moreover, type and amount of fluid therapy and vasoactive drug support could help manage these patients either with or without mechanical ventilator support. This brief review outlines the current evidence regarding the COVID-19-related renal and cardiorenal complications and discusses potential hemodynamic management strategies.

Capillary Leukocytes, Microaggregates, and the Response to Hypoxemia in the Microcirculation of Coronavirus Disease 2019 Patients.

OBJECTIVES: In this study, we hypothesized that coronavirus disease 2019 patients exhibit sublingual microcirculatory alterations caused by inflammation, coagulopathy, and hypoxemia. DESIGN: Multicenter case-controlled study. SETTING: Two ICUs in The Netherlands and one in Switzerland. PATIENTS: Thirty-four critically ill coronavirus disease 2019 patients were compared with 33 healthy volunteers. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The microcirculatory parameters quantified included total vessel density (mm × mm-2), functional capillary density (mm × mm-2), proportion of perfused vessels (%), capillary hematocrit (%), the ratio of capillary hematocrit to systemic hematocrit, and capillary RBC velocity (µm × s-1). The number of leukocytes in capillary-postcapillary venule units per 4-second image sequence (4 s-1) and capillary RBC microaggregates (4 s-1) was measured. In comparison with healthy volunteers, the microcirculation of coronavirus disease 2019 patients showed increases in total vessel density (22.8 ± sd 5.1 vs 19.9 ± 3.3; p < 0.0001) and functional capillary density (22.2 ± 4.8 vs 18.8 ± 3.1; p < 0.002), proportion of perfused vessel (97.6 ± 2.1 vs 94.6 ± 6.5; p < 0.01), RBC velocity (362 ± 48 vs 306 ± 53; p < 0.0001), capillary hematocrit (5.3 ± 1.3 vs 4.7 ± 0.8; p < 0.01), and capillary-hematocrit-to-systemic-hematocrit ratio (0.18 ± 0.0 vs 0.11 ± 0.0; p < 0.0001). These effects were present in coronavirus disease 2019 patients with Sequential Organ Failure Assessment scores less than 10 but not in patients with Sequential Organ Failure Assessment scores greater than or equal to 10. The numbers of leukocytes (17.6 ± 6.7 vs 5.2 ± 2.3; p < 0.0001) and RBC microaggregates (0.90 ± 1.12 vs 0.06 ± 0.24; p < 0.0001) was higher in the microcirculation of the coronavirus disease 2019 patients. Receiver-operating-characteristics analysis of the microcirculatory parameters identified the number of microcirculatory leukocytes and the capillary-hematocrit-to-systemic-hematocrit ratio as the most sensitive parameters distinguishing coronavirus disease 2019 patients from healthy volunteers. CONCLUSIONS: The response of the microcirculation to coronavirus disease 2019-induced hypoxemia seems to be to increase its oxygen-extraction capacity by increasing RBC availability. Inflammation and hypercoagulation are apparent in the microcirculation by increased numbers of leukocytes and RBC microaggregates.

Veno-arterial thrombosis and microcirculation imaging in a patient with COVID-19.

The Coronavirus pandemic has brought new challenges in intensive care medicine. Understanding of the pathophysiology of the vascular complications of SARS-CoV-2 infection could bring new resuscitation and therapeutic options. In this case report, we present a patient with COVID-19 pneumonia, who was admitted to our ICU and treated with high-flow nasal cannula, dexamethasone, remdesivir and high-dose prophylactic low molecular weight heparin. During ICU admission, substantial venous and arterial thrombosis developed. Meanwhile the microcirculation showed more than double amount of organ perfusion with very high total vessel density. We hypothesize that this might be a compensatory mechanism for the generalized prothrombic state in which the microcirculation increases the oxygen extraction capacity preventing multi-organ failure.

Case Report: Sublingual Microcirculatory Alterations in a Covid-19 Patient With Subcutaneous Emphysema, Venous Thrombosis, and Pneumomediastinum.

The Corona virus disease 2019 (Covid-19) has brought a wide range of challenges in intensive care medicine. Understanding of the pathophysiology of Covid-19 relies on interpreting of its impact on the vascular, particularly microcirculatory system. Herein we report on the first use of the latest generation hand-held vital microscope to evaluate the sublingual microcirculation in a Covid-19 patient with subcutaneous emphysema, venous thrombosis and pneumomediastinum. Remarkably, microcirculatory parameters of the patient were increased during the exacerbation period, which is not a usual finding in critically ill patients mostly presenting with a loss of hemodynamic coherence. In contrast, recovery from the disease led to a subsequent amelioration of these parameters. This report clearly shows the importance of microcirculatory monitoring for evaluating the course and the adequacy of therapy in Covid-19 patients.