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To evaluate the association of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) initial viral load (iVL) and the incidence of myocardial injury (MCI) in hospitalized patients with SARS-CoV-2 infection, we conducted a retrospective longitudinal study of hospitalized patients who had a nasopharyngeal swab sample on admission that returned a positive result for SARS-CoV-2 by polymerase chain reaction between April 4 and June 5, 2020. The cycle threshold (Ct) value was used as a surrogate for the iVL level, with a Ct level of 36 or less for elevated iVL and greater than 36 for low iVL. Myocardial injury was defined as an elevated high-sensitivity cardiac troponin I level that was higher than the 99th percentile upper reference limit. A total of 270 patients were included. Of these, 171 (63.3%) had an elevated iVL and 88 (32.6%) had MCI. There was no significant difference in the incidence of MCI in patients with low iVL compared to those with elevated iVL (28 of 99 [28.3%] vs 60 of 171 [35.1%]; P=.25). In a multivariable model, MCI (odds ratio, 3.86; 95% CI, 1.80 to 8.34; P

Fungal endophthalmitis is one of the leading causes of vision loss worldwide. Post-operative and traumatic injuries are major contributing factors resulting in ocular fungal infections in healthy and, more importantly, immunocompromised individuals. Among the fungal pathogens, the Aspergillus species, Aspergillus fumigatus, continues to be more prevalent in fungal endophthalmitis patients. However, due to overlapping clinical symptoms with other endophthalmitis etiology, fungal endophthalmitis pose a challenge in its diagnosis and treatment. Hence, it is critical to understand its pathobiology to develop and deploy proper therapeutic interventions for combating Aspergillus infections. This review highlights the different modes of Aspergillus transmission and the host immune response during endophthalmitis. Additionally, we discuss recent advancements in the diagnosis of fungal endophthalmitis. Finally, we comprehensively summarize various antifungal regimens and surgical options for the treatment of Aspergillus endophthalmitis.

BackgroundHospitalization of patients infected with the severe acute respiratory syndrome virus 2 (SARS-CoV-2) have remained considerable worldwide. Patients often develop severe complications and have high mortality rates. The cycle threshold (Ct) value derived from nasopharyngeal swab samples using real time polymerase chain reaction (RT-PCR) may be a useful prognostic marker in hospitalized patients with SARS-CoV-2 infection, however, its role in predicting the course of the pandemic has not been evaluated thus far.MethodsWe conducted a retrospective cohort study which included all patients who had a nasopharyngeal sample positive for SARS-CoV-2 between April 4 -June 5, 2020. The Ct value was used to estimate the number of viral particles in a patient sample. The trend in initial viral load on admission on a population level was evaluated. Moreover, patient characteristics and outcomes stratified by viral load categories were compared and initial viral load was assessed as an independent predictor of intubation and in-hospital mortality.ResultsA total of 461 hospitalized patients met the inclusion criteria. This study consisted predominantly of acutely infected patients with a median of 4 days since symptom onset to PCR. As the severity of the pandemic eased, there was an increase in the percentage of samples in the low initial viral load category, coinciding with a decrease in deaths. Compared to an initial low viral load, a high initial viral load was an independent predictor of in-hospital mortality (OR 5.5, CI 3.1-9.7, p < 0.001) and intubation (OR 1.82 CI 1.07-3.11, p = 0.03), while an initial intermediate viral load was associated with increased risk of inpatient mortality (OR 1.9, CI 1.14-3.21, p = 0.015) but not with increased risk for intubation.ConclusionThe Ct value obtained from nasopharyngeal samples of hospitalized patients on admission may serve as a prognostic marker at an individual level and may help predict the course of the pandemic when evaluated at a population level.