Identifying Immunological and Clinical Predictors of COVID-19 Severity and Sequelae by Mathematical Modeling.

Since its emergence as a pandemic in March 2020, coronavirus disease (COVID-19) outcome has been explored via several predictive models, using specific clinical or biochemical parameters. In the current study, we developed an integrative non-linear predictive model of COVID-19 outcome, using clinical, biochemical, immunological, and radiological data of patients with different disease severities. Initially, the immunological signature of the disease was investigated through transcriptomics analysis of nasopharyngeal swab samples of patients with different COVID-19 severity versus control subjects (exploratory cohort, n=61), identifying significant differential expression of several cytokines. Accordingly, 24 cytokines were validated using a multiplex assay in the serum of COVID-19 patients and control subjects (validation cohort, n=77). Predictors of severity were Interleukin (IL)-10, Programmed Death-Ligand-1 (PDL-1), Tumor necrosis factors-α, absolute neutrophil count, C-reactive protein, lactate dehydrogenase, blood urea nitrogen, and ferritin; with high predictive efficacy (AUC=0.93 and 0.98 using ROC analysis of the predictive capacity of cytokines and biochemical markers, respectively). Increased IL-6 and granzyme B were found to predict liver injury in COVID-19 patients, whereas interferon-gamma (IFN-γ), IL-1 receptor-a (IL-1Ra) and PD-L1 were predictors of remarkable radiological findings. The model revealed consistent elevation of IL-15 and IL-10 in severe cases. Combining basic biochemical and radiological investigations with a limited number of curated cytokines will likely attain accurate predictive value in COVID-19. The model-derived cytokines highlight critical pathways in the pathophysiology of the COVID-19 with insight towards potential therapeutic targets. Our modeling methodology can be implemented using new datasets to identify key players and predict outcomes in new variants of COVID-19.

Assessing the utility and efficacy of e-OSCE among undergraduate medical students during the COVID-19 pandemic.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) and its quick progression to a global pandemic has urged medical schools to shift from didactic to distance learning and assessment approaches. The quality of clinical training and assessment have been jeopardized due to the regulatory restrictions and potential hazards to human lives. The aim of this paper is to evaluate the utility and efficacy of an electronic Objective Structured Clinical Examination (e-OSCE), which attempted to transform the format of a face-to-face OSCE to an e-OSCE. METHODS: We conducted three end of clerkship e-OSCEs for final year medical students in Surgery, Medicine and Family Medicine using the teleconferencing application of Microsoft Teams (MST). The e-OSCE blueprint included the assessment of all clinical skills except physical examination and procedural skills. Examiners supervised e-OSCE from the college campus, while all students were remotely assessed through the MST channels. During the exam, the students stayed in their specified MST channel and examiners rotated across all students. The utility and efficacy of e-OSCE was evaluated using a self-administered questionnaire for students, examiners and e-OSCE team. RESULTS: The data analysis showed that 93.4% students and 92.2% examiners agreed with the quality and process of e-OSCE. Similarly, 83.6% students and 98% examiners agreed with the seamless organization of e-OSCE. As many as 45.9% students and 74.5% examiners agreed that e-OSCE was close to real life practice. Approximately one fifth of students and one third of examiners preferred e-OSCE over the face-to-face OSCE. The analysis of qualitative data generated the themes of e-OSCE structure and technology. While majority of participants were satisfied with e-OSCE, students were concerned about examiners' training and e-OSCE contents. Examiners and e-OSCE team recognized the paper-less, tech-savy, fast and reliable format of e-OSCE. CONCLUSION: During and beyond COVID- 19 era, e-OSCE is a strong substitute to standard OSCE for assessing clinical competence except for physical examination and procedural skills. The planning and implementation of e-OSCE reflects an ingenuity in the assessment of clinical competencies of medical students.

Profiling Levels of Serum microRNAs and Soluble ACE2 in COVID-19 Patients.

Background: The main mechanism of viral entry in COVID-19 infection is through the angiotensin-converting enzyme 2 (ACE2) receptor present in the lungs. Numerous studies suggested a clinical significance of risk factors, such as gender, obesity, and diabetes on the soluble form of ACE2 (sACE2) and related miRNAs in COVID-19 infection. This study aims to investigate the serum level of sACE2 and 4 miRNAs (miR-421, miR-3909, miR-212-5p, and miR-4677-3p) in COVID-19 patients and assess their associations with clinicopathological parameters. Methods: Serum samples were collected from non-diabetic and diabetic COVID-19 patients and healthy controls. sACE2 levels were quantified using ELISA, and serum miRNA levels were measured using qPCR. In addition, laboratory blood tests were retrieved from the clinical records of COVID-19 patients. Results: sACE2 levels were upregulated in COVID-19 patients regardless of sex, diabetes status, or obesity. Furthermore, the four investigated miRNAs were upregulated in COVID-19 patients and were positively correlated with each other. Furthermore, miR-421, miR-3909, and miR-4677-3p were positively associated with sACE2, suggesting a strong link between these markers. Notably, miR-212-5p was selectively upregulated in moderate, male, and non-obese COVID-19 patients. Interestingly, miR-212-5p was correlated with D-dimer, while sACE2 was correlated with coagulation tests, such as aPTT and platelets, indicating their potential as markers of coagulopathy in COVID-19. Additionally, there was a positive correlation between sACE2 and C-reactive protein in diabetic COVID-19 patients, indicating a promising role of this marker in the inflammatory status of these patients. Conclusions: sACE2 and its regulatory miRNAs were upregulated and correlated with laboratory investigations of COVID-19 patients, thus indicating their clinical significance as biomarkers in COVID-19 infection.

Circulating Soluble ACE2 and Upstream microRNA Expressions in Serum of Type 2 Diabetes Mellitus Patients.

The global coronavirus disease 2019 (COVID-19) pandemic was associated with multiple organ failure and comorbidities, such as type 2 diabetes mellitus (T2DM). Risk factors, such as age, gender, and obesity, were associated with COVID-19 infection. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to use several host receptors for viral entry, such as angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) in the lung and other organs. However, ACE2 could be shed from the surface to be soluble ACE2 (sACE2) in the circulation. The epigenetic factors affecting ACE2 expression include a type of small non-coding RNAs called microRNAs (miRNAs). In this study, we aimed at exploring the status of the sACE2 as well as serum levels of several upstream novel miRNAs as non-invasive biomarkers that might have a potential role in T2DM patients. Serum samples were collected from 50 T2DM patients and 50 healthy controls, and sACE2 levels were quantified using enzyme-linked immunosorbent assay (ELISA). Also, RNA was extracted, and TaqMan miRNA reverse transcription quantitative PCR (RT-qPCR) was performed to measure serum miRNA levels. Our results revealed that sACE2 is decreased in the T2DM patients and is affected by age, gender, and obesity level. Additionally, 4 miRNAs, which are revealed by in silico analysis to be potentially upstream of ACE2 were detectable in the serum. Among them, miR-421 level was found to be decreased in the serum of diabetic patients, regardless of the presence or absence of diabetic complications, as well as being differential in various body mass index (BMI) groups. The other 3 miRNAs (miR-3909, miR-212-5p, and miR-4677-3p) showed associations with multiple factors including age, gender, BMI, and serum markers, in addition to being correlated to each other. In conclusion, our study reveals a decline in the circulating serum levels of sACE2 in T2DM patients and identified 4 novel miRNAs that were associated with T2DM, which are influenced by different clinical and demographic factors.