Prior sars-cov-2 infection is associated with subclinical changes in the cardiovascular morphology, function, energetics and exercise capacity

Background: COVID-19 has documented multisystem effects. Whether clinically significant cardiac involvement is related to severity of disease in a working age military population remains unknown, but has implications for occupational grading and ability to deploy. Aims: To determine in the military population 1) whether prior SARS-CoV-2 infection causes clinically significant cardiac disease and 2) whether changes are related to disease severity. Methods: 105 military personnel were recruited, 85 with prior SARS-CoV-2 infection (39±10 years, 87% male;50 mild (community), 35 severe (hospitalized) and 20 healthy volunteers (mean age 39 ±8.4 years, 90% male) underwent comprehensive cardiopulmonary investigations including;cardiopulmonary exercise test, exercise echocardiography, cardiac31MRI and P-MR spectroscopy (rest and dobutamine stress). Results: Prior SARS-CoV-2 infection was related to lower VO2max (110±18.2 vs 133±6.7% predicted, p<0.05), anaerobic threshold (45±10 vs 56±14% of peak VO2, p<0.05), VO2/HR (102±21 vs 128±24% predicted, p<0.05) and VE/VCO2 slope (28.3±5.0 vs 25.8±2.7, p<0.05) and an increase in average E/e' change from rest to exercise stress (+1.49±2.4 vs-0.16±3.6, p<0.05). Whilst resting myocardial energetics were similar, prior SARS-CoV-2 infection was associated with a fall in PCr/ATP during stress (by 8%, p=<0.01) which was not seen in healthy controls. When groups were ordered normal> mild> severe disease, RVEDVi, RV stroke volume, VO2peak, VO2pulse and VE/VCO slope were reduced (Jonckheere-Terpstra, all p<0.05). Conclusion: In a young military population, prior SARS-CoV-2 infection is associated with subclinical cardiovascular changes including;lower right ventricular volumes, reduced markers of exercise capacity and reduced myocardial energetics during stress.

Clinical signs predictive of covid-19 mortality among transplant recipients

Purpose: The presentation of Coronavirus disease 2019 (COVID-19) ranges from mild illness to severe respiratory failure. Disease progression may differ in immunocompromised patients and immunocompetent hosts. Therefore, we aim to characterize COVID-19 clinical presentation and outcomes in solid organ transplant recipients (SOTRs) to identify initial clinical factors that may predict COVID-19 associated mortality. Methods: We prospectively reviewed baseline demographic and clinical characteristics among adult kidney, pancreas, liver, heart and lung transplant recipients diagnosed with COVID-19 between March 1, 2020 and May 5, 2020 at our transplant center in New York City. A series of chi-square and Fisher's exact tests were conducted to investigate the relationship between several predictor variables (baseline characteristics, symptoms at presentation, and baseline immunosuppression regimen) and 30-day mortality. Results: 73 SOTRs (53 kidney, 8 liver, 7 heart, 3 lung, 2 heart/kidney) with SARSCoV-2 PCR-confirmed COVID-19 were included in the final analysis. Median age was 59 years (IQR 54-68) and 34.2% were female. Median time since transplant was 21 months (IQR 13-46.5). All patients were on baseline immunosuppresion as shown in table 1. The majority of patients were diagnosed in the Emergency Department. Most common presenting symptoms were cough (68.5%), gastrointestinal symptoms (54.8%) and dyspnea (45.2%) with median of 5 days from symptom onset to hospitalization. All patients had elevated inflammatory markers at time of diagnosis (median CRP 54 mg/L, median ferritin 704 ng/mL, median procalcitonin 0.11 ng/mL, median D-dimer 311 ng/mL). 84.1% of patients required supplemental oxygen, including intubation in 19.7%. 13 of 63 (21%) hospitalized patients died. Dyspnea on presentation was the only baseline or presenting patient factor found to be predictive of death (p =.004). When stratified by initial chest X-ray findings, dyspnea combined with abnormal chest X-ray predicted mortality (p=.021) while dyspnea with normal chest X-ray did not. Conclusions: Presenting symptoms of dyspnea and radiographic signs of pneumonia on initial imaging predicted mortality among SOTRs with COVID-19 in our cohort. These findings can inform allocation of limited resources in COVID-19 management, including the triage and timing of COVID-19 directed therapies early in the illness course among different patient populations.

Single-Cell RNA-seq Reveals Angiotensin-Converting Enzyme 2 and Transmembrane Serine Protease 2 Expression in TROP2+ Liver Progenitor Cells: Implications in Coronavirus Disease 2019-Associated Liver Dysfunction.

The recent coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2. COVID-19 was first reported in China (December 2019) and is now prevalent across the globe. Entry of severe acute respiratory syndrome coronavirus 2 into mammalian cells requires the binding of viral Spike (S) proteins to the angiotensin-converting enzyme 2 receptor. Once entered, the S protein is primed by a specialized serine protease, transmembrane serine protease 2 in the host cell. Importantly, besides the respiratory symptoms that are consistent with other common respiratory virus infections when patients become viremic, a significant number of COVID-19 patients also develop liver comorbidities. We explored whether a specific target cell-type in the mammalian liver could be implicated in disease pathophysiology other than the general deleterious response to cytokine storms. Here, we used single-cell RNA-seq to survey the human liver and identified potentially implicated liver cell-type for viral ingress. We analyzed ~300,000 single cells across five different (i.e., human fetal, healthy, cirrhotic, tumor, and adjacent normal) liver tissue types. This study reports on the co-expression of angiotensin-converting enzyme 2 and transmembrane serine protease 2 in a TROP2+ liver progenitor population. Importantly, we detected enrichment of this cell population in the cirrhotic liver when compared with tumor tissue. These results indicated that in COVID-19-associated liver dysfunction and cell death, a viral infection of TROP2+ progenitors in the liver might significantly impair liver regeneration in patients with liver cirrhosis.

The impact of COVID-19 on clinical trials in the Asia-Pacific region and future implications (preprint)

The COVID-19 pandemic has affected the conduct of clinical trials in an unparalleled manner due to multiple levels of restrictions imposed to control the spread of SARS-CoV2. These restrictions have presented major challenges for clinicians, sponsors, contract research organizations and patients participating in ongoing clinical trials and have necessitated alternative solutions to ensure study and patient care continuity. In this review, we assessed the impact of the pandemic on key metrics of the commencement and continuation of clinical trials in the Asia-Pacific region and the efforts made to mitigate these challenges. Overall, newly initiated studies in 2020, outside of those directly related to COVID-19, were reduced. Access to sites and recruitment were also impacted significantly although recovery has begun in the latter half of 2020. Clinical trials consist of complex workflows across study procedures and site-patient engagements. Based on clinician and industry surveys, the impact of COVID-19 may drive an increase in interest and adoption of virtual, digital technologies and tools to help alleviate the numerous challenges for clinical trial stakeholders. We discuss these new approaches and debate their readiness and appropriateness for widespread use. With ongoing acceleration of the pandemic and the maturation of technology, we expect increasing near-term adoption of virtual and digital methodologies in clinical trials. As a silver lining of the pandemic, these approaches may make studies more patient centric, improve clinical trial efficiency and enhance the experience and care of the patients enrolled on trials.

Early COVID-19 pandemic modeling: Three compartmental model case studies from Texas, USA.

The novel coronavirus (SARS-CoV-2) emerged in late 2019 and spread globally in early 2020. Initial reports suggested the associated disease, COVID-19, produced rapid epidemic growth and caused high mortality. As the virus sparked local epidemics in new communities, health systems and policy makers were forced to make decisions with limited information about the spread of the disease. We developed a compartmental model to project COVID-19 healthcare demands that combined information regarding SARS-CoV-2 transmission dynamics from international reports with local COVID-19 hospital census data to support response efforts in three Metropolitan Statistical Areas (MSAs) in Texas, USA: Austin-Round Rock, Houston-The Woodlands-Sugar Land, and Beaumont-Port Arthur. Our model projects that strict stay-home orders and other social distancing measures could suppress the spread of the pandemic. Our capacity to provide rapid decision-support in response to emerging threats depends on access to data, validated modeling approaches, careful uncertainty quantification, and adequate computational resources.