The PaO2/FiO2 ratio significantly increased from 68 [58-89] to 168 [137-218] and the oxygenation index significantly decreased from 28 [26-35] to 13 [10-15]. The duration of ECMO was 12 [8-25] days. Nine (82%) patients experienced ECMO-related complications and the main complication was major bleeding requiring blood transfusions. Intensive care unit mortality rate was 55% but no patient died from ECMO-related complications. In COVID-19 patients with severe ARDS, venovenous ECMO allowed ultra-protective ventilation, improved oxygenation and should be considered in highly selected patients with the most severe ARDS.Introduction Current imaging modalities for peripheral nerves display the nerve's structure but not its function. Based on a nerve's capacity for axonal transport, it may be visualized by targeted application of a contrast agent and assessing the distribution through radiological imaging, thus revealing a nerve's continuity. This concept has not been explored, however, may potentially guide the treatment of peripheral nerve injuries. In this experimental proof-of-concept study, we tested imaging through MRI after administering gadolinium-based contrast agents which were then retrogradely transported. Methods We synthesized MRI contrast agents consisting of paramagnetic agents and various axonal transport facilitators (HSA-DTPA-Gd, chitosan-DTPA-Gd or PLA/HSA-DTPA-Gd). First, we measured their relaxivity values in vitro to assess their radiological suitability. Subsequently, the sciatic nerve of 24 rats was cut and labeled with one of the contrast agents to achieve retrograde distribution along the nerve. One maging approach for the evaluation of a peripheral nerve's integrity was implemented. The findings provide radiological and chemical evidence of successful contrast agent uptake along the sciatic nerve and its distribution within the spinal canal in rats. This novel concept may assist in the diagnostic process of peripheral nerve injuries in the future.Aims To evaluate the ocular and systemic factors involved in cataract surgery complications in a teaching hospital using artificial intelligence. Methods One eye of 1,229 patients with a mean age of 70.2 ± 10.3 years old that underwent cataract surgery was selected for this study. Ocular and systemic details of the patients were recorded and then analyzed by means of artificial intelligence. A total of 1.25 billion simulations of artificial intelligence learning and testing were conducted on several variables and a customized model of analysis was developed. Results A total of 73 complications were recorded in this study. According to the analysis performed, the main factors involved in cataract surgery complications were a surgeon in training, axial length and intraocular lens power. https://www.selleckchem.com/products/sbe-b-cd.html The model predicted how long surgery would last with an error of less then 6 min compared to the effective time needed. Conclusions According to the data here obtained, artificial intelligence could be an interesting option to build customized models able to prevent complications and to predict actual surgery time. The customized algorithm option allows the development of better models adaptable to different units as well as the possibility to be calibrated for the same unit along time.Objective Salivary gland ultrasound (SGUS) is emerging as a valid tool in the management of primary Sjögren's syndrome (pSS). This study aimed to investigate whether pSS patients with normal-appearing or pathological SGUS findings showed different clinical, laboratory, and pathologic pSS-related features, and to compare the results by using two different SGUS scores. Methods Consecutive pSS patients, according to the ACR-EULAR classification criteria, were evaluated. Salivary glands were scored using the early 1992 score by De Vita et al. and the latest 2019 OMERACT score, both being semiquantitative 0-3 scoring systems focused on ultrasonographic parenchymal inhomogeneity (grades 0 and 1, normal-appearing; grades 2 and 3, pathological). The patients were then divided into two groups "SGUS normal-appearing" if all the salivary glands had normal-appearing parenchyma (grade 0 or 1), or "SGUS pathological" if the grade was 2 or 3 in at least one salivary gland. The associations between SGUS and pSS-related clinierved by using the two SGUS scoring systems. Conclusion The SGUS allowed the identification of different phenotypes of pSS, and different SGUS scores focused on salivary gland inhomogeneity may be effective to this end.Background During the COVID-19 pandemic people are facing risks of adverse health effects due to the restrictions implemented such as quarantine measures, reduced social contact, and self-isolation. In this qualitative review, we collected data on potential preventive and therapeutic health benefits of Complementary and Integrative Medicine (CIM) that might be useful during the COVID-19 pandemic. We have reviewed the scientific literature to summarize CIM practices that could be beneficial for improving physical and mental health and well-being of the population under the current pandemic circumstances. It must be noted that this review is not SARS-CoV-2 specific and we explicitly do not intend to make any SARS-CoV-2 specific health claims in this article. Methods and Findings A qualitative, non-systematic literature review was conducted in Medline to identify literature describing preventive and therapeutic CIM approaches for strengthening mental and physical health. For a variety of CIM approaches clinical ntial benefit in the COVID-19 pandemic in different areas is worth to be analyzed. While this qualitative review has several obvious limitations, it might serve as useful starting point for further research on this topic.Background Identifying clinical-features or a scoring-system to predict a benefit from hospital admission for patients with COVID-19 can be of great value for the decision-makers in the health sector. We aimed to identify differences in patients' demographic, clinical, laboratory, and radiological findings of COVID-19 positive cases to develop and validate a diagnostic-model predicting who will develop severe-form and who will need critical-care in the future. Methods In this observational retrospective study, COVID-19 positive cases (total 417) diagnosed in Al Kuwait Hospital, Dubai, UAE were recruited, and their prognosis in terms of admission to the hospital and the need for intensive care was reviewed until their tests turned negative. Patients were classified according to their clinical state into mild, moderate, severe, and critical. We retrieved all the baseline clinical data, laboratory, and radiological results and used them to identify parameters that can predict admission to the intensive care unit (ICU).