Evidence of brain metabolism redistribution from neocortex to primitive brain structures in early acute COVID-19 respiratory syndrome.

BACKGROUND: Neuropsychiatric sequelae of COVID-19 have been widely documented in patients with severe neurological symptoms during the chronic or subacute phase of the disease. However, it remains unclear whether subclinical changes in brain metabolism can occur early in the acute phase of the disease. The aim of this study was to identify and quantify changes in brain metabolism in patients hospitalized for acute respiratory syndrome due to COVID-19 with no or mild neurological symptoms. RESULTS: Twenty-three non-intubated patients (13 women; mean age 55.5 ± 12.1 years) hospitalized with positive nasopharyngeal swab test (RT-PCR) for COVID-19, requiring supplemental oxygen and no or mild neurological symptoms were studied. Serum C-reactive protein measured at admission ranged from 6.43 to 189.0 mg/L (mean: 96.9 ± 54.2 mg/L). The mean supplemental oxygen demand was 2.9 ± 1.4 L/min. [18F]FDG PET/CT images were acquired with a median of 12 (4-20) days of symptoms. After visual interpretation of the images, semiquantitative analysis of [18F]FDG uptake in multiple brain regions was evaluated using dedicated software and the standard deviation (SD) of brain uptake in each region was automatically calculated in comparison with reference values of a normal database. Evolutionarily ancient structures showed positive SD mean values of [18F]FDG uptake. Lenticular nuclei were bilaterally hypermetabolic (> 2 SD) in 21/23 (91.3%) patients, and thalamus in 16/23 (69.6%), bilaterally in 11/23 (47.8%). About half of patients showed hypermetabolism in brainstems, 40% in hippocampi, and 30% in cerebellums. In contrast, neocortical regions (frontal, parietal, temporal and occipital lobes) presented negative SD mean values of [18F]FDG uptake and hypometabolism (< 2 SD) was observed in up to a third of patients. Associations were found between hypoxia, inflammation, coagulation markers, and [18F]FDG uptake in various brain structures. CONCLUSIONS: Brain metabolism is clearly affected during the acute phase of COVID-19 respiratory syndrome in neurologically asymptomatic or oligosymptomatic patients. The most frequent finding is marked hypermetabolism in evolutionary ancient structures such as lenticular nucleus and thalami. Neocortical metabolism was reduced in up to one third of patients, suggesting a redistribution of brain metabolism from the neocortex to evolutionary ancient brain structures in these patients.

Improving deep neural network generalization and robustness to background bias via layer-wise relevance propagation optimization.

Features in images' backgrounds can spuriously correlate with the images' classes, representing background bias. They can influence the classifier's decisions, causing shortcut learning (Clever Hans effect). The phenomenon generates deep neural networks (DNNs) that perform well on standard evaluation datasets but generalize poorly to real-world data. Layer-wise Relevance Propagation (LRP) explains DNNs' decisions. Here, we show that the optimization of LRP heatmaps can minimize the background bias influence on deep classifiers, hindering shortcut learning. By not increasing run-time computational cost, the approach is light and fast. Furthermore, it applies to virtually any classification architecture. After injecting synthetic bias in images' backgrounds, we compared our approach (dubbed ISNet) to eight state-of-the-art DNNs, quantitatively demonstrating its superior robustness to background bias. Mixed datasets are common for COVID-19 and tuberculosis classification with chest X-rays, fostering background bias. By focusing on the lungs, the ISNet reduced shortcut learning. Thus, its generalization performance on external (out-of-distribution) test databases significantly surpassed all implemented benchmark models.

Construction of a nomogram for predicting COVID-19 in-hospital mortality: A machine learning analysis.

Background and objectives: We aim to verify the use of ML algorithms to predict patient outcome using a relatively small dataset and to create a nomogram to assess in-hospital mortality of patients with COVID-19. Methods: A database of 200 COVID-19 patients admitted to the Clinical Hospital of State University of Campinas (UNICAMP) was used in this analysis. Patient features were divided into three categories: clinical, chest abnormalities, and body composition characteristics acquired by computerized tomography. These features were evaluated independently and combined to predict patient outcomes. To minimize performance fluctuations due to low sample number, reduce possible bias related to outliers, and evaluate the uncertainties generated by the small dataset, we developed a shuffling technique, a modified version of the Monte Carlo Cross Validation, creating several subgroups for training the algorithm and complementary testing subgroups. The following ML algorithms were tested: random forest, boosted decision trees, logistic regression, support vector machines, and neural networks. Performance was evaluated by analyzing Receiver operating characteristic (ROC) curves. The importance of each feature in the determination of the outcome predictability was also studied and a nomogram was created based on the most important features selected by the exclusion test. Results: Among the different sets of features, clinical variables age, lymphocyte number and weight were the most valuable features for prognosis prediction. However, we observed that skeletal muscle radiodensity and presence of pleural effusion were also important for outcome determination. Integrating these independent predictors was successfully developed to accurately predict mortality in COVID-19 in hospital patients. A nomogram based on these five features was created to predict COVID-19 mortality in hospitalized patients. The area under the ROC curve was 0.86 ± 0.04. Conclusion: ML algorithms can be reliable for the prediction of COVID-19-related in-hospital mortality, even when using a relatively small dataset. The success of ML techniques in smaller datasets broadens the applicability of these methods in several problems in the medical area. In addition, feature importance analysis allowed us to determine the most important variables for the prediction tasks resulting in a nomogram with good accuracy and clinical utility in predicting COVID-19 in-hospital mortality.

Plasma Angiotensin II Is Increased in Critical Coronavirus Disease 2019.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) employs angiotensin-converting enzyme 2 (ACE2) as its receptor for cell entrance, and studies have suggested that upon viral binding, ACE2 catalytic activity could be inhibited; therefore, impacting the regulation of the renin-angiotensin-aldosterone system (RAAS). To date, only few studies have evaluated the impact of SARS-CoV-2 infection on the blood levels of the components of the RAAS. The objective of this study was to determine the blood levels of ACE, ACE2, angiotensin-II, angiotensin (1-7), and angiotensin (1-9) at hospital admission and discharge in a group of patients presenting with severe or critical evolution of coronavirus disease 2019 (COVID-19). We showed that ACE, ACE2, angiotensin (1-7), and angiotensin (1-9) were similar in patients with critical and severe COVID-19. However, at admission, angiotensin-II levels were significantly higher in patients presenting as critical, compared to patients presenting with severe COVID-19. We conclude that blood levels of angiotensin-II are increased in hospitalized patients with COVID-19 presenting the critical outcome of the disease. We propose that early measurement of Ang-II could be a useful biomarker for identifying patients at higher risk for extremely severe progression of the disease.

Non-Alcoholic Fatty Liver Disease in Long-Term Type 2 Diabetes: Role of rs738409 PNPLA3 and rs499765 FGF21 Polymorphisms and Serum Biomarkers.

Fibroblast growth factor 21 (FGF21) signaling and genetic factors are involved in non-alcoholic fatty liver disease (NAFLD) pathogenesis. However, these factors have rarely been studied in type 2 diabetes mellitus (T2D) patients from admixed populations such as in those of Brazil. Therefore, we aimed to evaluate rs738409 patanin-like phospholipase domain-containing protein (PNPLA3) and rs499765 FGF21 polymorphisms in T2D, and their association with NAFLD, liver fibrosis, and serum biomarkers (FGF21 and cytokeratin 18 levels). A total of 158 patients were included, and the frequency of NAFLD was 88.6%, which was independently associated with elevated body mass index. Significant liver fibrosis (≥F2) was detected by transient elastography (TE) in 26.8% of NAFLD patients, and was independently associated with obesity, low density lipoprotein, and gamma-glutamyl transferase (GGT). PNPLA3 GG genotype and GGT were independently associated with cirrhosis. PNPLA3 GG genotype patients had higher GGT and AST levels; PNPLA3 GG carriers had higher TE values than CG patients, and FGF21 CG genotype patients showed lower gamma-GT values than CC patients. No differences were found in serum values of FGF21 and CK18 in relation to the presence of NAFLD or liver fibrosis. The proportion of NAFLD patients with liver fibrosis was relevant in the present admixed T2D population, and was associated with PNPLA3 polymorphisms.

Safety and Outcomes Associated with the Pharmacological Inhibition of the Kinin-Kallikrein System in Severe COVID-19.

Background: Coronavirus disease 19 (COVID-19) can develop into a severe respiratory syndrome that results in up to 40% mortality. Acute lung inflammatory edema is a major pathological finding in autopsies explaining O2 diffusion failure and hypoxemia. Only dexamethasone has been shown to reduce mortality in severe cases, further supporting a role for inflammation in disease severity. SARS-CoV-2 enters cells employing angiotensin-converting enzyme 2 (ACE2) as a receptor, which is highly expressed in lung alveolar cells. ACE2 is one of the components of the cellular machinery that inactivates the potent inflammatory agent bradykinin, and SARS-CoV-2 infection could interfere with the catalytic activity of ACE2, leading to the accumulation of bradykinin. Methods: In this case control study, we tested two pharmacological inhibitors of the kinin-kallikrein system that are currently approved for the treatment of hereditary angioedema, icatibant, and inhibitor of C1 esterase/kallikrein, in a group of 30 patients with severe COVID-19. Results: Neither icatibant nor inhibitor of C1 esterase/kallikrein resulted in changes in time to clinical improvement. However, both compounds were safe and promoted the significant improvement of lung computed tomography scores and increased blood eosinophils, which are indicators of disease recovery. Conclusions: In this small cohort, we found evidence for safety and a beneficial role of pharmacological inhibition of the kinin-kallikrein system in two markers that indicate improved disease recovery.

Evaluation of the efficacy and safety of icatibant and C1 esterase/kallikrein inhibitor in severe COVID-19: study protocol for a three-armed randomized controlled trial.

BACKGROUND: SARS-CoV-2, the virus that causes COVID-19, enters the cells through a mechanism dependent on its binding to angiotensin-converting enzyme 2 (ACE2), a protein highly expressed in the lungs. The putative viral-induced inhibition of ACE2 could result in the defective degradation of bradykinin, a potent inflammatory substance. We hypothesize that increased bradykinin in the lungs is an important mechanism driving the development of pneumonia and respiratory failure in COVID-19. METHODS: This is a phase II, single-center, three-armed parallel-group, open-label, active control superiority randomized clinical trial. One hundred eighty eligible patients will be randomly assigned in a 1:1:1 ratio to receive either the inhibitor of C1e/kallikrein 20 U/kg intravenously on day 1 and day 4 plus standard care; or icatibant 30 mg subcutaneously, three doses/day for 4 days plus standard care; or standard care alone, as recommended in the clinical trials published to date, which includes supplemental oxygen, non-invasive and invasive ventilation, antibiotic agents, anti-inflammatory agents, prophylactic antithrombotic therapy, vasopressor support, and renal replacement therapy. DISCUSSION: Accumulation of bradykinin in the lungs is a common side effect of ACE inhibitors leading to cough. In animal models, the inactivation of ACE2 leads to severe acute pneumonitis in response to lipopolysaccharide (LPS), and the inhibition of bradykinin almost completely restores the lung structure. We believe that inhibition of bradykinin in severe COVID-19 patients could reduce the lung inflammatory response, impacting positively on the severity of disease and mortality rates. TRIAL REGISTRATION: Brazilian Clinical Trials Registry Universal Trial Number (UTN) U1111-1250-1843. Registered on May/5/2020.

Noninvasive imaging assessment of rehabilitation therapy in heart failure with preserved and reduced left ventricular ejection fraction (IMAGING-REHAB-HF): design and rationale.

BACKGROUND: Studies have shown significant benefits of exercise therapy in heart failure (HF) with a reduced ejection fraction (HFrEF) and HF with a preserved ejection fraction (HFpEF). The mechanisms responsible for the beneficial effect of exercise in HFrEF and HFpEF are still unclear. We hypothesized that the effect of exercise on myocardial remodeling may explain its beneficial effect. METHODS: IMAGING-REHAB-HF is a single-center, randomized, controlled clinical trial using cardiac magnetic resonance imaging, vasomotor endothelial function, cardiac sympathetic activity imaging and serum biomarkers to compare the effect of exercise therapy in HFpEF (LVEF ≥ 45%) and HFrEF (LVEF < 45%). Subjects will be assessed at baseline and after 4 months. The exercise program will consist of three 60-min exercise sessions/week. The primary endpoints are the effect of exercise on myocardial extracellular volume (ECV), left ventricular (LV) systolic function, LV mass, LV mass-to-volume and LV cardiomyocyte volume. Secondary endpoints include the effect of exercise on vasomotor endothelial function, cardiac sympathetic activity and plasmatic biomarkers. Patients will be allocated in a 2:1 fashion to supervised exercise program or usual care. A total sample size of 90 patients, divided into two groups according to LVEF:HFpEF group (45 patients:30 in the intervention arm and 15 in the control arm) and HFrEF group (45 patients:30 in the intervention arm and 15 in the control arm) - will be necessary to achieve adequate power. CONCLUSION: This will be the first study to evaluate the benefits of a rehabilitation program on cardiac remodeling in HF patients. The unique design of our study may provide unique data to further elucidate the mechanisms involved in reverse cardiac remodeling after exercise in HFpEF and HFrEF patients.