SlowFast GCN Network for Quantification of Parkinsonian Gait Using 2D Videos

Parkinson's disease(PD) is a progressive neu-rodegenerative disease defined by clinical syndrome including bradykinesia, tremor and postural instability. The PD-related disability and impairment are usually monitored by clinicals using the MDS-UPDRS scale. However, due to COVID-19, it became much harder for the patients to reach hospitals and obtain necessary assessment and treatment. Nowadays, 2D videos are easily accessible and can be a promising so-lution for on-site and remote diagnosis of movement disorder. Inspired by the frequency-based video processing mechanism of human visual system, we propose a video-based SlowFast GCN network to quantify the gait disorder. The model consists of two parts: the fast pathway and the slow pathway. The former detects characteristics such as tremor and bilateral asymmetry, while the latter extracts characteristics such as bradykinesia and freezing of gait. Furthermore, in order to investigate the influence of age on the model performance, an aged control group and a young control group were set up for verification. The proposed model was evaluated on a video dataset collected from 68 participants. We achieved a balanced accuracy of 87.5% and precision of 87.9%, which outperformed existing competing methods. When replacing the young healthy controls with the same number of older controls, the balanced accuracy and precision were decreased by 10.4% and 9.7%, which indicates that age has a significant effect on the model perfomance. © 2022 IEEE.

Cytokine Release Syndrome and Sepsis: Analogous Clinical Syndromes with Distinct Causes and Challenges in Management.

Both cytokine release syndrome (CRS) and sepsis are clinical syndromes rather than distinct diseases and share considerable overlap. It can often be challenging to distinguish between the two, but it is important given the availability of targeted treatment options. In addition, several other clinical syndromes overlap with CRS and sepsis, further making it difficult to differentiate them. This has particularly been highlighted in the recent coronavirus disease-2019 pandemic. As we start to understand the differences in the inflammatory markers and presentations in these syndromes, hopefully we will be able to enhance treatment and improve outcomes.

Acute Clinical Syndromes and Suspicion of SARS-CoV-2 Infection: The Experience of a Single Romanian Center in the Early Pandemic Period.

Background and Objectives: During the coronavirus disease 2019 (COVID-19) pandemic, patients with chronic diseases suffering exacerbations have required acute medical care. The purpose of our study was to determine useful criteria for the differentiation of patients with acute clinical syndromes and suspicion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Materials and Methods: This was an observational retrospective study, conducted in an internal medicine clinic from April to May 2020. We collected clinical, biological, and computed tomography (CT) data on patients with exacerbations of chronic diseases and clinical suspicion of SARS-CoV-2 infection. Patients with an already-positive real-time reverse-transcription polymerase chain reaction (RT-PCR) test for SARS-CoV-2 on presentation at the emergency department were excluded from our study. Results: Of 253 suspected cases, 20 were laboratory-confirmed as having SARS-CoV-2 infection by RT-PCR, whereas COVID-19 diagnosis was ruled out in the remaining 233. Venous thromboembolism (VTE) correlated significantly with COVID-19 diagnosis in suspected patients, while laboratory markers were not significantly different between the two groups. Of the suspected patients, significantly higher percentages of dry cough, fever, myalgias, sore throat, loss of smell and appetite, and ground-glass opacities (GGOs) on CT were found in SARS-CoV-2-positive individuals. Conclusions: The study demonstrated that, until receiving the result of an RT-PCR test for SARS-CoV-2 (usually 12-24 h), association with VTE as a comorbidity, fever, dry cough, and myalgia as clinical features, and GGO on CT are the main markers for the identification of COVID-19 patients among those suspected with acute clinical syndromes. Our results also provide evidence for doctors not to rely solely on biological markers in the case of suspected SARS-CoV-2 infection in patients with exacerbations of chronic diseases. These data are useful for faster decision-making with regard to suspected COVID-19 patients before receiving RT-PCR test results, thus avoiding keeping patients in crowded emergency departments.