Drug Repurposing for the Treatment of COVID-19: A Knowledge Graph Approach.

Identifying effective drug treatments for COVID-19 is essential to reduce morbidity and mortality. Although a number of existing drugs have been proposed as potential COVID-19 treatments, effective data platforms and algorithms to prioritize drug candidates for evaluation and application of knowledge graph for drug repurposing have not been adequately explored. A COVID-19 knowledge graph by integrating 14 public bioinformatic databases containing information on drugs, genes, proteins, viruses, diseases, symptoms and their linkages is developed. An algorithm is developed to extract hidden linkages connecting drugs and COVID-19 from the knowledge graph, to generate and rank proposed drug candidates for repurposing as treatments for COVID-19 by integrating three scores for each drug: motif scores, knowledge graph PageRank scores, and knowledge graph embedding scores. The knowledge graph contains over 48 000 nodes and 13 37 000 edges, including 13 563 molecules in the DrugBank database. From the 5624 molecules identified by the motif-discovery algorithms, ranking results show that 112 drug molecules had the top 2% scores, of which 50 existing drugs with other indications approved by health administrations reported. The proposed drug candidates serve to generate hypotheses for future evaluation in clinical trials and observational studies.

Case report: Coronavirus Disease 2019 (COVID-19) modified RNA vaccination-induced Adult-Onset Still's Disease with fulminant myocarditis as initial presentation.

Myocarditis is a rare complication of Coronavirus Disease 2019 (COVID-19) vaccination. We report a case of an elderly female who presented initially with acute myocarditis, fulminant heart failure, and atrial fibrillation after receiving a modified ribonucleic acid (mRNA) vaccine (BNT162b2). Unlike other patients with vaccine-induced myocarditis, she developed persistent fever, sore throat, polyarthralgia, diffuse macular rash, and lymphadenopathy. After extensive investigation, she was diagnosed with post-vaccination Adult-Onset Still's Disease. The systemic inflammation gradually subsided after the use of non-steroidal anti-inflammatory drugs and systemic steroids. She was discharged from hospital with stable hemodynamics. Methotrexate was subsequently given to maintain long-term remission.

Thromboembolic events and hemorrhagic stroke after mRNA (BNT162b2) and inactivated (CoronaVac) covid-19 vaccination: A self-controlled case series study.

Background: This study aims to evaluate the association between thromboembolic events and hemorrhagic stroke following BNT162b2 and CoronaVac vaccination. Methods: Patients with incident thromboembolic events or hemorrhagic stroke within 28 days of covid-19 vaccination or SARS-CoV-2 positive test during 23 February to 30 September 2021 were included. The incidence per 100,000 covid-19 vaccine doses administered and SARS-CoV-2 test positive cases were estimated. A modified self-controlled case series (SCCS) analysis using the data from the Hong Kong territory-wide electronic health and vaccination records. Seasonal effect was adjusted by month. Findings: A total of 5,526,547 doses of BNT162b2 and 3,146,741 doses of CoronaVac were administered. A total of 334 and 402 thromboembolic events, and 57 and 49 hemorrhagic stroke cases occurred within 28 days after BNT162b2 and CoronaVac vaccination, respectively. The crude incidence of thromboembolic events and hemorrhagic stroke per 100,000 doses administered for both covid-19 vaccines were smaller than that per 100,000 SARS-CoV-2 test positive cases. The modified SCCS detected an increased risk of hemorrhagic stroke in BNT162b2 14-27 days after first dose with adjusted IRR of 2.53 (95% CI 1.48-4.34), and 0-13 days after second dose with adjusted IRR 2.69 (95% CI 1.54-4.69). No statistically significant risk was observed for thromboembolic events for both vaccines. Interpretation: We detected a possible safety signal for hemorrhagic stroke following BNT162b2 vaccination. The incidence of thromboembolic event or hemorrhagic stroke following vaccination is lower than that among SARS-CoV-2 test positive cases; therefore, vaccination against covid-19 remains an important public health intervention. Funding: This study was funded by a research grant from the Food and Health Bureau, The Government of the Hong Kong Special Administrative Region (reference COVID19F01).

Association between BNT162b2 or CoronaVac COVID-19 vaccines and major adverse cardiovascular events among individuals with cardiovascular disease.

AIMS: Concern about the cardiovascular safety of coronavirus disease 2019 (COVID-19) vaccines among individuals with cardiovascular disease (CVD) may lead to vaccine hesitancy. We sought to assess the association between two COVID-19 vaccines, BNT162b2 and CoronaVac, and the risk of major adverse cardiovascular events (MACE) in individuals with established CVD. METHODS AND RESULTS: We identified individuals with a history of CVD before 23 February 2021 and a diagnosis of MACE between 23 February 2021 and 31 January 2022 in Hong Kong. MACE was defined as a composite of myocardial infarction, stroke, revascularization, and cardiovascular death. Electronic health records from the Hong Kong Hospital Authority were linked to vaccination records from the Department of Health. A self-controlled case-series method was used to evaluate the risk of MACE for 0-13 and 14-27 days after two doses of COVID-19 vaccine. We estimated incidence rate ratios (IRRs) to compare the risk of MACE between each risk period and the baseline period. A total of 229 235 individuals with CVD were identified, of which 1764 were vaccinated and had a diagnosis of MACE during the observation period (BNT162b2 = 662; CoronaVac = 1102). For BNT162b2, IRRs were 0.48 [95% confidence interval (CI) 0.23-1.02] for the first dose and 0.87 (95% CI 0.50-1.52) for the second dose during the 0-13 days risk period, 0.40 (95% CI 0.18-0.93) for the first dose and 1.13 (95% CI 0.70-1.84) for the second dose during the 14-27 days risk period. For CoronaVac, the IRRs were 0.43 (95% CI 0.24-0.75) for the first dose and, 0.73 (95% CI 0.46-1.16) for the second dose during the 0-13 days risk period, 0.54 (95% CI 0.33-0.90) for the first dose and 0.83 (95% CI 0.54-1.29) for the second dose during the 14-27 days risk period. Consistent results were found in subgroup analyses for different sexes, age groups and different underlying cardiovascular conditions. CONCLUSION: Our findings showed no evidence of an increased risk of MACE after vaccination with BNT162b2 or CoronaVac in patients with CVD. Future research is required to monitor the risk after the third dose of each vaccine.

Challenges in management of ST elevation myocardial infarction during COVID-19 pandemic.

The coronavirus disease-2019 (COVID-19) pandemic has brought unprecedented changes to our world and health-care system. Its high virulence and infectiousness directly infect people's respiratory system and indirectly disrupt our health-care infrastructure. In particular, ST elevation myocardial infarction (STEMI) is a clinical emergency emphasizes on the establishment of care system to minimize delay to reperfusion. As such, the impact of COVID-19 on STEMI care, ranging from disease severity, patient delay, diagnostic difficulty, triage to selection of reperfusion strategy and postoperative care, is immense. Importantly, not only we have to save our patients, but we must also need to protect all health-care workers and prevent environmental contamination. Otherwise, in-hospital transmission can quickly evolve into nosocomial outbreak with staff infection and quarantine which lead to health-care system collapse. In this article, we will discuss the challenges in various aspects of STEMI management during COVID-19, as well as the mitigation measures we can take to optimize outcome and our future.

Erratum: Drug Repurposing for the Treatment of COVID-19: A Knowledge Graph Approach.

[This corrects the article DOI: 10.1002/adtp.202100055.].

Observational study on wearable biosensors and machine learning-based remote monitoring of COVID-19 patients.

Patients infected with SARS-CoV-2 may deteriorate rapidly and therefore continuous monitoring is necessary. We conducted an observational study involving patients with mild COVID-19 to explore the potentials of wearable biosensors and machine learning-based analysis of physiology parameters to detect clinical deterioration. Thirty-four patients (median age: 32 years; male: 52.9%) with mild COVID-19 from Queen Mary Hospital were recruited. The mean National Early Warning Score 2 (NEWS2) were 0.59 ± 0.7. 1231 manual measurement of physiology parameters were performed during hospital stay (median 15 days). Physiology parameters obtained from wearable biosensors correlated well with manual measurement including pulse rate (r = 0.96, p < 0.0001) and oxygen saturation (r = 0.87, p < 0.0001). A machine learning-derived index reflecting overall health status, Biovitals Index (BI), was generated by autonomous analysis of physiology parameters, symptoms, and other medical data. Daily BI was linearly associated with respiratory tract viral load (p < 0.0001) and NEWS2 (r = 0.75, p < 0.001). BI was superior to NEWS2 in predicting clinical worsening events (sensitivity 94.1% and specificity 88.9%) and prolonged hospitalization (sensitivity 66.7% and specificity 72.7%). Wearable biosensors coupled with machine learning-derived health index allowed automated detection of clinical deterioration.

Cardiovascular sequalae in uncomplicated COVID-19 survivors.

BACKGROUND: A high proportion of COVID-19 patients were reported to have cardiac involvements. Data pertaining to cardiac sequalae is of urgent importance to define subsequent cardiac surveillance. METHODS: We performed a systematic cardiac screening for 97 consecutive COVID-19 survivors including electrocardiogram (ECG), echocardiography, serum troponin and NT-proBNP assay 1-4 weeks after hospital discharge. Treadmill exercise test and cardiac magnetic resonance imaging (CMR) were performed according to initial screening results. RESULTS: The mean age was 46.5 ± 18.6 years; 53.6% were men. All were classified with non-severe disease without overt cardiac manifestations and did not require intensive care. Median hospitalization stay was 17 days and median duration from discharge to screening was 11 days. Cardiac abnormalities were detected in 42.3% including sinus bradycardia (29.9%), newly detected T-wave abnormality (8.2%), elevated troponin level (6.2%), newly detected atrial fibrillation (1.0%), and newly detected left ventricular systolic dysfunction with elevated NT-proBNP level (1.0%). Significant sinus bradycardia with heart rate below 50 bpm was detected in 7.2% COVID-19 survivors, which appeared to be self-limiting and recovered over time. For COVID-19 survivors with persistent elevation of troponin level after discharge or newly detected T wave abnormality, echocardiography and CMR did not reveal any evidence of infarct, myocarditis, or left ventricular systolic dysfunction. CONCLUSION: Cardiac abnormality is common amongst COVID-survivors with mild disease, which is mostly self-limiting. Nonetheless, cardiac surveillance in form of ECG and/or serum biomarkers may be advisable to detect more severe cardiac involvement including atrial fibrillation and left ventricular dysfunction.

Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes Platform to Study SARS-CoV-2 Related Myocardial Injury.

BACKGROUND: SARS-CoV-2 infection is associated with myocardial injury, but there is a paucity of experimental platforms for the condition.Methods and Results:Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) infected by SARS-CoV-2 for 3 days ceased beating and exhibited cytopathogenic changes with reduced viability. Active viral replication was evidenced by an increase in supernatant SARS-CoV-2 and the presence of SARS-CoV-2 nucleocaspid protein within hiPSC-CMs. Expressions of BNP, CXCL1, CXCL2, IL-6, IL-8 and TNF-α were upregulated, while ACE2 was downregulated. CONCLUSIONS: Our hiPSC-CM-based in-vitro SARS-CoV-2 myocarditis model recapitulated the cytopathogenic effects and cytokine/chemokine response. It could be exploited as a drug screening platform.

Artificial intelligence mobile health platform for early detection of COVID-19 in quarantine subjects using a wearable biosensor: protocol for a randomised controlled trial.

INTRODUCTION: There is an outbreak of COVID-19 worldwide. As there is no effective therapy or vaccine yet, rigorous implementation of traditional public health measures such as isolation and quarantine remains the most effective tool to control the outbreak. When an asymptomatic individual with COVID-19 exposure is being quarantined, it is necessary to perform temperature and symptom surveillance. As such surveillance is intermittent in nature and highly dependent on self-discipline, it has limited effectiveness. Advances in biosensor technologies made it possible to continuously monitor physiological parameters using wearable biosensors with a variety of form factors. OBJECTIVE: To explore the potential of using wearable biosensors to continuously monitor multidimensional physiological parameters for early detection of COVID-19 clinical progression. METHOD: This randomised controlled open-labelled trial will involve 200-1000 asymptomatic subjects with close COVID-19 contact under mandatory quarantine at designated facilities in Hong Kong. Subjects will be randomised to receive a remote monitoring strategy (intervention group) or standard strategy (control group) in a 1:1 ratio during the 14 day-quarantine period. In addition to fever and symptom surveillance in the control group, subjects in the intervention group will wear wearable biosensors on their arms to continuously monitor skin temperature, respiratory rate, blood pressure, pulse rate, blood oxygen saturation and daily activities. These physiological parameters will be transferred in real time to a smartphone application called Biovitals Sentinel. These data will then be processed using a cloud-based multivariate physiology analytics engine called Biovitals to detect subtle physiological changes. The results will be displayed on a web-based dashboard for clinicians' review. The primary outcome is the time to diagnosis of COVID-19. ETHICS AND DISSEMINATION: Ethical approval has been obtained from institutional review boards at the study sites. Results will be published in peer-reviewed journals.

Impact of coronavirus disease 2019 (COVID-19) outbreak on outcome of myocardial infarction in Hong Kong, China.

OBJECTIVE: To determine whether COVID-19 may adversely affect outcome of myocardial infarction (MI) patients in Hong Kong, China. BACKGROUND: The COVID-19 pandemic has infected thousands of people and placed enormous stress on healthcare system. Apart from being an infectious disease, it may affect human behavior and healthcare resource allocation which potentially cause treatment delay in MI. METHODS: This was a single center cross-sectional observational study. From November 1, 2019 to March 31, 2020, we compared outcome of patients admitted for acute ST-elevation MI (STEMI) and non-ST elevation MI (NSTEMI) before (group 1) and after (group 2) January 25, 2020 which was the date when Hong Kong hospitals launched emergency response measures to combat COVID-19. RESULTS: There was a reduction in daily emergency room attendance since January 25, 2020 (group 1,327/day vs. group 2,231/day) and 149 patients with diagnosis of MI were included into analysis (group 1 N = 85 vs. group 2 N = 64). For STEMI, patients in group 2 tended to have longer symptom-to-first medical contact time and more presented out of revascularization window (group 1 27.8 vs. group 2 33%). The primary composite outcome of in-hospital death, cardiogenic shock, sustained ventricular tachycardia or fibrillation (VT/VF) and use of mechanical circulatory support (MCS) was significantly worse in group 2 (14.1 vs. 29.7%, p = .02). CONCLUSIONS: More MI patients during COVID-19 outbreak had complicated in-hospital course and worse outcomes. Besides direct infectious complications, cardiology community has to acknowledge the indirect effect of communicable disease on our patients and system of care.