ABSTRACT
› We report the case of a young professional soccer player who underwent cardiac MRI (CMR) for work-up of discrete intermit-tent chest pain and subtle ST segment elevations in the ECG after having been tested positive for SARS-CoV-2 type B.1.1.529 despite full vaccination including recent mRNA booster. › Troponin levels were significantly increased and myocarditis was suspected. Comprehensive CMR including CINE and late gadolinium enhancement as well as multi-parametric T1/T2 mapping techniques revealed local hypokinesia and swelling of the posterolateral wall with non-ischemic late gadolinium enhancement and increased T2 relaxation time compatible with acute viral myocarditis. The patient was admitted to a cardiology ward for rhythm and troponin monitoring and was discharged after two days of uneventful rhythm monitoring and with decreased troponin levels. › Adhering to current recommendations the patient was advised to abstain from moderate-to high-intensity sports and exercise for 3-6 months. After 6 months of exercise avoidance, follow-up ECG showed regression of prior ST segment elevations, and Holter ECG as well as a treadmill exercise stress test did not reveal any abnormalities. Follow-up CMR was performed before return-to-sports which revealed persisting myocardial fibrosis but complete regression of myocardial edemam and excluded ongoing inflammation. › This example underscores the value of multi-parametric CMR tissue characterization for the work-up of suspected SARS-CoV-2 associated myocarditis, as well as for follow-up before return-to-sports. © 2023, Dynamic Media Sales Verlag. All rights reserved.
ABSTRACT
Background. COVID-19 can cause serious illness requiring multimodal treatment of the viral infection and its associated complications, including the potential for secondary infections. Studies have suggested an increased risk of fungal infections, including candidemia following severe COVID-19 though understanding of risk factors and clinical outcomes remains unclear. Methods. A multi-center, case-control study of patients with severe COVID-19 was conducted to evaluate risk factors and clinical outcomes in patients who developed candidemia between August 2020 to August 2021. Risk factors associated with candidemia and mortality were characterized using multivariate analyses. Results. A total of 275 patients were enrolled in the study, including 91 patients with severe COVID-19 and subsequent candidemia and 184 patients with severe COVID-19 without candidemia. Most patients received antibiotics prior to candidemia episode (93%), while approximately one-quarter of all patients received biologic for COVID-19. In-hospital mortality was significantly higher in the case group compared to the control group (68% vs 40%, P < 0.01). Multivariable logistic regression revealed that the use of central lines, biologic and paralytic therapy were independent risk factors for candidemia. The presence of candidemia, older age, central line use, and intensive care unit admission were significantly associated with mortality. Demographics and Baseline Characteristics of Study Patients with SARS-CoV-2 Positive With or Without Candidemia Hospitalization Details and Outcomes Conclusion. Clinicians should be aware of the possibility of development of candidemia in hospitalized older patients with severe COVID-19 and should closely monitor those patients at risk. Risk factors for developing candidemia in the setting of COVID-19 are largely consistent with classic risk factors previously identified.
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Background. Patients with COVID-19 disease often receive antibiotics to treat suspected bacterial coinfections. Procalcitonin (PCT) is a biomarker used for suspected bacterial infections. The objective of this study is to evaluate the association between PCT and the use of antimicrobials in COVID-19 patients. Methods. This was a retrospective, cohort study of adult patients admitted with confirmed COVID-19 from March 30, 2020 to March 30, 2021. Data collected included demographics, baseline inflammatory markers including initial PCT and C-reactive protein (CRP) values, past medical history, initiation of empiric antibiotics, mechanical ventilation, in-hospital mortality, days of antibiotic therapy, and length of hospital stay (LOS). Univariate analyses were utilized to assess for any significant differences in demographics based on predefined initial PCT groupings (< 0.25 ng/ml (group 1), 0.25-0.49 ng/ml (group 2), and >= 0.5 ng/ml (group 3)). Multivariate analyses were performed to evaluate for any differences between initial PCT values and in-hospital mortality, LOS, and days of antibiotic therapy. Results. Out of 149 patients, 61.7% had an initial PCT value < 0.25 ng/ml, 17.45% had an initial value of 0.25-0.49 ng/ml, and 20.8% had an initial value >= 0.5 ng/ml. A total of 145 patients (97%) received empiric antibiotics. Univariate analysis among the three groups displayed a difference in the initial CRP value, which was higher in groups 2 and 3 versus group 1 (p < 0.001). Regression analysis controlling for initial CRP value found that patients in groups 2 and 3 had a higher duration of antibiotic therapy compared to group 1 (12 and 11 versus 8 days) (p < 0.001) and a longer LOS (17 and 15 vs 12 days) (p = 0.009). More patients (34.6%) were mechanically ventilated in group 2 compared to group 1 (14.1%) and group 3 (22.6%) with a trend toward significance (p = 0.059). Multivariate analysis found no significant association between PCT levels and mortality. The rate of in-hospital mortality in patients receiving invasive ventilation was higher in groups 2 and 3 (78% and 86%, respectively) compared to group 1 (54%, p < 0.001). Conclusion. When controlling for CRP, an initial PCT value > 0.25 ng/ml was associated with increased days of antibiotic therapy and longer duration of hospital stay in COVID-19 patients.
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Background. Limited data exists regarding the impact of coronavirus disease 2019 (COVID-19) on people living with human immunodeficiency virus (PLWH). The purpose of the study was to compare the clinical outcomes of patients hospitalized with COVID-19 and HIV versus those without HIV. Methods. This was a retrospective, cohort study of adult patients admitted with confirmed COVID-19 from March 1st to May 30th 2020 at an urban hospital in New York City. Data collected included demographics, past medical history, HIV status, baseline laboratory values, treatment and outcomes such as length of stay, mechanical ventilation, patient disposition at discharge, and in-hospital mortality. Fisher's exact test was used to compare categorical values and a t-test was used to compare continuous values. Results. Out of 983 patients, 6.9% were PLWH and 93.1% were HIV-negative. The average age in both groups was 61 vs. 62 years, respectively. There were more male patients in the PLWH than the non-HIV group (76.8% vs. 58.6%). Majority of PLWH were Black (49.3%). Forty-seven percent of PLWH were mechanically ventilated versus 33.3% of the non-HIV group. The most common comorbidity in both groups was hypertension (82.4% vs. 72.6%). When compared to HIV-negative patients, PLWH had a higher rate of kidney disease (72.1% vs. 53.6%, p=0.0086), chronic obstructive pulmonary disease (41.2% vs. 14.5%, p=0.0001), liver disease (45.6% vs. 11.5%, p=0.0001) and current smoking (14.3% vs. 5.8%, p=0.0103). In PLWH, 70.6% of patients were on an integrase-based regimen. Fifty-three percent of PLWH had a CD4 count of > 200 cells/mm3 and 35.3% had an undetectable viral load (< 20 copies/mL). Unadjusted hospital mortality was 51.4% in PLWH and 36.2% in the non-HIV cohort (p=0.0089). The average length of hospital stay was 9.1 days vs. 8.4 days in PLWH versus the non-HIV group (p=0.4493). More patients were discharged to a nursing home in the non-HIV group vs. PLWH (37.8% vs. 14.3%, p=0.0001). Conclusion. Hospitalized patients with COVID-19 and HIV had a higher in-hospital mortality compared to those without HIV during the first COVID wave in New York City.
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Background: Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in COVID-19. We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential. Aims: To identify biomarkers of coagulation, inflammation, and fibrinolysis that may predict clinical course and outcome of COVID-19 patients. Methods: We performed a single-center prospective study of 14 adult COVID-19(+) ICU patients who were age and sex-matched to 14 COVID-19(-) ICU patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Ten biomarkers of interest were subjected to linear discriminant analysis (LDA) to explore the discriminatory ability of biomarkers for COVID-19 status. Linear repeated measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts. Results: LDA identified high D-dimer as the strongest contributor in distinguishing COVID-19 status however D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients -low (30%) and high (100%) mortality groups (Figure 1). Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels. Conclusions: Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19.
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Background : COVID-19 infection is characterized by immunothrombosis that likely reflects hypercoagulation, endothelial dysfunction, and increased formation of neutrophil extracellular traps. Aims : In this study, we investigated the utility of immunothrombosis biomarkers to distinguish between COVID-19 patients and non-COVID septic pneumonia patients. We also investigated the prognostic utility of the biomarkers in predicting ICU mortality in the two patients groups. Methods : The participants in this study were ICU COVID-19 patients ( n = 14), ICU non-COVID septic pneumonia patients ( n = 19), and age-and sex-matched healthy controls ( n = 14). Blood samples were collected on Days 4, 7, 10, and/or 14. We measured plasma levels of the following biomarkers: thrombin-antithrombin (TAT) complexes, protein C, antithrombin, soluble TM, soluble EPCR, fibrinogen, D-dimer, cell-free DNA (cfDNA), and citrullinated histones (H3-Cit). Data analysis was based on binomial logit models and receiver operating characteristic curve analyses. Results : We identified 8 biomarkers that distinguish COVID-19 patients from healthy individuals: cfDNA, D-dimer, sEPCR, PC, sTM, fibrinogen, H3-Cit, and TAT complexes. In comparison, 4 biomarkers distinguish COVID-19 from non-COVID septic pneumonia patients: fibrinogen, sEPCR, antithrombin, and cfDNA. With respect to prognosis, the main predictors of ICU mortality differ between the two patient groups. In COVID-19 patients, non-survivors have higher sTM and H3-Cit compared with survivors. In septic pneumonia patients, non-survivor patients have lower levels of protein C and higher cfDNA levels compared with survivors. In addition, the most recent values of the biomarkers have stronger prognostic value compared to their Day 1 values. Conclusions : Our results suggest that fibrinogen, sEPCR, antithrombin, and cfDNA have utility for distinguishing COVID-19 patients from non-COVID septic pneumonia patients. Our data also suggest that the predictors of ICU mortality differ between the two patient groups: sTM and H3-Cit for COVID-19 patients, and protein C and cfDNA for non-COVID septic pneumonia patients. These findings suggests that there are pathophysiological differences between the two patients groups.