Microvascular flow alterations in critically ill COVID-19 patients: A prospective study

Abou-Arab, Osama; Beyls, Christophe; Khalipha, Abdelilah; Guilbart, Mathieu; Huette, Pierre; Malaquin, Stéphanie; Lecat, Benoit; Macq, Pierre-Yves; Roger, Pierre-Alexandre; Haye, Guillaume; Bernasinski, Michaël; Besserve, Patricia; Soriot-Thomas, S.; Jounieaux, Vincent; Dupont, Hervé; Mahjoub, Yazine

doi:10.1371/journal.pone.0246636

Cited by 16 publications

(10 citation statements)

References 27 publications

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“…The function of the sublingual microcirculation, on the other hand, directly reflects the oxygen delivery capacity to the tissue, and has previously been shown to tightly correlate with the outcome in critically ill patients [ 30 , 31 ]. The increased microcirculatory functional capacity found in the present study is consistent with previous findings [ 2 , 32 , 33 ] and has been shown to persist until the occurrence multi-organ failure [ 2 , 32 ] or severe endothelial dysfunction [ 34 , 35 ]. However, in contrast to previous measurement methods of microcirculatory function such as subjective classification of image sequences and assignment of mean flow index (MFI) categories, the quantitative, fully automated, algorithm-based image sequence analysis enabled by MicroTools and used in the present study, allowed for accurate quantification of the functional microcirculatory hemodynamic variables, as well as the elimination of inter-observer bias introduced by subjective grading [ 3 ].…”

Section: Discussionsupporting

confidence: 93%

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

et al. 2022

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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.

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Section: Discussionsupporting

confidence: 93%

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

et al. 2022

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“…To date, a number of studies have investigated the sublingual microcirculation in COVID-19 patients [17][18][19][20][21][22][23] A first evaluation conducted by Damiani et al [17] in 12 patients with COVID-19 pneumonia showed that sublingual microvascular capillary densities were inversely correlated with D-dimer levels, suggesting the impact of microthrombosis on the microcirculatory function. In a prospective observational study [20], Kanoore Edul et al demonstrated that sublingual microcirculation in severe COVID-19-ARDS patients was characterized by decreases in PPV (0.96 ± 0.03) and flow quality (MFI: 2.79 ± 0.10 and red blood cell velocity: 1124 ± 161 µm/s) along with high vascular densities (TVD: 21.9 ± 3.9 and PVD: 21.0 ± 3.5 mm/mm 2 ), compared to normal values.…”

Section: Introductionmentioning

confidence: 99%

Microcirculatory Alterations in Critically Ill Patients with COVID-19-Associated Acute Respiratory Distress Syndrome

Dedda

Ascari

Fantinato

et al. 2022

JCM

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Background: Presently, a number of specific observations have been performed on microcirculatory function in a coronavirus disease-19 (COVID-19) setting. We hypothesized that, in the critically ill, endothelial dysfunction secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the subsequent inflammation and coagulopathy may lead to microcirculatory alterations, further exacerbated by the hypoxemic state. A dysfunctional microcirculation may represent the hidden motor underlying the development of COVID-19’s clinical manifestations. Methods: A single center, prospective, observational study. We analyzed bedside sublingual microcirculation in twenty-four consecutive COVID-19-associated acute respiratory distress syndrome (ARDS) patients mechanically ventilated in an Intensive Care Unit (ICU), together with macro-hemodynamics, clinical parameters, echocardiography, and laboratory data at a single time-point after ICU admission. All participants were recruited between March and May 2020. Results: The microcirculatory pattern was characterized by increased values of total vessel density and perfused vessel density, a reduced value of proportion of perfused vessels and microvascular flow index, and high values of heterogeneity index. The duration of mechanical ventilation before microcirculation assessment was inversely associated with the proportion of perfused vessels (p = 0.023). Within the macro-hemodynamic parameters, the right ventricle end-diastolic diameter was inversely associated with proportion of perfused vessels and microvascular flow index (p = 0.039 and 0.014, respectively) and directly associated with the heterogeneity index (p = 0.033). Conclusions: In COVID-19-associated ARDS patients, the microcirculation showed impaired quality of flow parameters coupled with a high vessel density.

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“…Present observations are in line with the available evidence showing an abnormal capillary density and/or function in COVID-19 patients. Previous studies have suggested that COVID-19 patients have reduced flow reserve in the forearm skin, as well as reduced microcirculatory flow index and perfused vessel density in the sublingual circulation (29)(30)(31). Interestingly, in one of these observations Sabioni et al have observed that peak hyperemic flow was impaired in either moderate or severe COVID-19 patients, but basal flow velocity was only affected in patients with severe COVID-19 (31).…”

Section: Discussionmentioning

confidence: 98%

Coronary Microvascular Dysfunction is Common in Patients Hospitalized with COVID-19 Infection

Güvenç¹

2021

Preprint

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Background and aims: Myocardial injury is frequent in patients hospitalized with Sars-COV-2 infection and portents a worse prognosis, but the cause of myocardial injury is uncertain. Coronary microvascular dysfunction (CMD) has been hypothesized as a possible explanation, but direct evidence demonstrating CMD in COVID-19 patients is missing. In the present study, we aimed to investigate whether CMD is present in hospitalized COVID-19 patients, and to understand whether there is a relationship between biomarkers of myocardial injury, myocardial strain and inflammation and CMD in COVID-19 patients. Methods: 39 patients that were hospitalized with COVID-19 and 40 control subjects were included to the present study. Biomarkers for myocardial injury, myocardial strain, inflammation and fibrin turnover were obtained at admission. A comprehensive echocardiographic examination, including measurement of coronary flow velocity reserve (CFVR), were done after the patient was stabilized. Results: Patients with COVID-19 infection had a lower hyperemic coronary flow velocity, resulting in a significantly lower CFVR (2.0±0.3 vs. 2.4±0.5, p<0.001). Patients with severe COVID-19 also had a lower CFVR compared to those with moderate COVID-19 (1.8±0.2 vs. 2.2±0.2, p<0.001) due to an increase in basal flow velocity (30.0±6.2 vs. 26.0±4.8, p=0.04). CFVR correlated with troponin (p=0.

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Microvascular flow alterations in critically ill COVID-19 patients: A prospective study

Cited by 16 publications

References 27 publications

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

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

Microcirculatory Alterations in Critically Ill Patients with COVID-19-Associated Acute Respiratory Distress Syndrome

Coronary Microvascular Dysfunction is Common in Patients Hospitalized with COVID-19 Infection

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