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Aims: To describe through emblematic images rare but clinically relevant carotid artery stenting complications that occurred at two high-volume centres for carotid artery stenting (CAS). Background: CAS is an alternative to carotid endarterectomy (CEA) for the treatment of carotid artery stenosis in patients judged to be at high risk for CEA. CAS complications range between 1 and 9% and are higher in older patients complaining of neurological symptoms at the time of presentation. Besides periprocedural or early-after-procedure stroke, which remains the true Achilles' heel of CAS, other dramatic complications might compromise the clinical outcomes of this procedure. Methods: Five infrequent complications, out of more than 1000 CAS performed in the years 2016–2021, have been described. Results: Among CAS complications, acute carotid stent thrombosis, rescue retrieval of a disconnected distal cerebral embolic protection device, plaque prolapse after carotid stenting, cerebral hyperperfusion syndrome (CHS), and radial artery long sheath entrapment requiring surgical intervention were found to account for 0.3% of the total number of procedures performed by operators with high CAS volume. Conclusions: Unusual CAS complications may infrequently occur, even in hands of expert operators. To know how to deal with such complications might help interventionalists to improve CAS performance. [ABSTRACT FROM AUTHOR]

Background and Objectives: In patients with COVID-19, high-flow nasal cannula (HFNC) and continuous positive airway pressure (CPAP) are widely applied as initial treatments for moderate-to-severe acute hypoxemic respiratory failure. The aim of the study was to assess which respiratory supports improve 28-day mortality and to identify a predictive index of treatment response. Materials and Methods: This is a single-center retrospective observational study including 159 consecutive adult patients with COVID-19 and moderate-to-severe hypoxemic acute respiratory failure. Results: A total of 159 patients (82 in the CPAP group and 77 in the HFNC group) were included in the study. Mortality within 28 days was significantly lower with HFNC compared to CPAP (16.8% vs. 50%), while ICU admission and tracheal intubation within 28 days were significantly higher with CPAP compared to HFNC treatment (32% vs. 13%). We identified an index for survival in HFNC by including three variables easily available at admission (LDH, age, and respiratory rate) and the PaO2/FiO2 ratio at 48 h. The index showed high discrimination for survival with an AUC of 0.88, a negative predictive value of 86%, and a positive predictive value of 95%. Conclusions: Treatment with HFNC appears to be associated with greater survival and fewer ICU admission than CPAP. LDH, respiratory rate, age, and PaO2/FiO2 at 48 h were independently associated with survival and an index based on these variables allows for the prediction of treatment success and the assessment of patient allocation to the appropriate intensity of care after 48 h. Further research is warranted to determine effects on other outcomes and to assess the performance of the index in larger cohorts. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is characterized by multi-organ involvement, including respiratory and cardiac events. Echocardiography is widely considered the first-choice tool for the evaluation of cardiac structures and function because of its reproducibility, feasibility, easy to use at bedside, and for good cost-effectiveness. The aim of our literature review is to define the utility of echocardiography in the prediction of prognosis and mortality in COVID-19 patients with mild to critical respiratory illness, with or without known cardiovascular disease. Moreover, we focused our attention on classical echocardiographic parameters and the use of speckle tracking to predict the evolution of respiratory involvement. Finally, we tried to explore the possible relationship between pulmonary disease and cardiac manifestations. [ABSTRACT FROM AUTHOR]

To realize a machine learning (ML) model to estimate the dose of low molecular weight heparin to be administered, preventing thromboembolism events in COVID-19 patients with active cancer. Methods: We used a dataset comprising 131 patients with active cancer and COVID-19. We considered five ML models: logistic regression, decision tree, random forest, support vector machine and Gaussian naive Bayes. We decided to implement the logistic regression model for our study. A model with 19 variables was analyzed. Data were randomly split into training (70%) and testing (30%) sets. Model performance was assessed by confusion matrix metrics on the testing data for each model as positive predictive value, sensitivity and F1-score. Results: We showed that the five selected models outperformed classical statistical methods of predictive validity and logistic regression was the most effective, being able to classify with an accuracy of 81%. The most relevant result was finding a patient-proof where python function was able to obtain the exact dose of low weight molecular heparin to be administered and thereby to prevent the occurrence of VTE. Conclusions: The world of machine learning and artificial intelligence is constantly developing. The identification of a specific LMWH dose for preventing VTE in very high-risk populations, such as the COVID-19 and active cancer population, might improve with the use of new training ML-based algorithms. Larger studies are needed to confirm our exploratory results. [ABSTRACT FROM AUTHOR]

Background and Objectives: In patients with COVID-19, high-flow nasal cannula (HFNC) and continuous positive airway pressure (CPAP) are widely applied as initial treatments for moderate-to-severe acute hypoxemic respiratory failure. The aim of the study was to assess which respiratory supports improve 28-day mortality and to identify a predictive index of treatment response. Materials and Methods: This is a single-center retrospective observational study including 159 consecutive adult patients with COVID-19 and moderate-to-severe hypoxemic acute respiratory failure. Results: A total of 159 patients (82 in the CPAP group and 77 in the HFNC group) were included in the study. Mortality within 28 days was significantly lower with HFNC compared to CPAP (16.8% vs. 50%), while ICU admission and tracheal intubation within 28 days were significantly higher with CPAP compared to HFNC treatment (32% vs. 13%). We identified an index for survival in HFNC by including three variables easily available at admission (LDH, age, and respiratory rate) and the PaO 2 /FiO 2 ratio at 48 h. The index showed high discrimination for survival with an AUC of 0.88, a negative predictive value of 86%, and a positive predictive value of 95%. Conclusions: Treatment with HFNC appears to be associated with greater survival and fewer ICU admission than CPAP. LDH, respiratory rate, age, and PaO 2 /FiO 2 at 48 h were independently associated with survival and an index based on these variables allows for the prediction of treatment success and the assessment of patient allocation to the appropriate intensity of care after 48 h. Further research is warranted to determine effects on other outcomes and to assess the performance of the index in larger cohorts., Competing Interests: The authors declare no conflicts of interest.

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) represents a public health problem worldwide. COVID-19 triggers a maladaptive cytokine release commonly referred to as cytokine storm syndrome with increased production of proinflammatory cytokines, which also appears to contribute to chronic neuroinflammation and neurodegenerative disorders' appearance, including multiple sclerosis, Parkinson's disease, and Alzheimer's disease. In this context, SARS-CoV-2 might enter the central nervous system through binding with the angiotensin converting enzyme 2 receptors which are highly expressed in glial cells and neurons. For this reason, an association between COVID-19, its dependent cytokine storm, and the development and/or progression of neurodegenerative disorders might be evaluated. Therefore, the aim of this review was to assess the impact of COVID-19 on neurodegenerative disorders, focusing on the possible increased mortality risk and/or deterioration of the clinical course of pre-existing chronic neurological diseases in patients with dementia., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)