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Cancer patients display immunomodulation related to malignancy and anti-cancer therapies, but how these factors impact COVID-19 remains unknown. To investigate immune responses in cancer patients with COVID-19, we undertook a prospective case-control study, enrolling hospitalized solid tumor patients with acute COVID-19, as well as age-, gender-, and comorbidity-matched COVID-19 patients without cancer as controls. Using biospecimens collected during hospitalization, we performed virologic measurements as well as in-depth immunophenotyping of cellular, antibody and cytokine responses. We enrolled 17 cancer patients (cases) admitted to Yale-New Haven Hospital between March 15 and June 30, 2020 with COVID-19, as well as 17 matched non-cancer patients (controls) admitted with COVID-19. No significant differences were observed between cases and controls based on patient characteristics (age, gender, race, co-morbidities, smoking history, days from symptom onset to COVID-19 diagnosis) or outcomes (COVID-19 severity, length of hospital stay, rate of intubation or mortality). The most common primary tumor sites were lung (4/17) and gastrointestinal (4/17);all cases had received cancer-directed therapy within 6 months of COVID-19 diagnosis, with 13/17 receiving treatment less than 1 month prior to hospitalization. Three of 17 cases had received immune checkpoint inhibitor therapies. Despite having similar SARS-CoV-2 viral RNA loads at the time of COVID-19 diagnosis when compared with controls, cancer cases had increased viral RNA abundance during hospitalization, suggesting slower clearance. Antibody responses against SARS-CoV-2 were preserved in cancer cases, with cases displaying similar levels of IgM and IgG antibodies directed against SARS-CoV-2 epitopes compared to controls. Cytokine profiling revealed higher plasma levels of CCL3, IL1A and CXCL12 in cancer cases compared to controls. Using flow cytometric immunophenotyping, we found that innate immune and non-T cell adaptive immune parameters were similar between cases and controls hospitalized with COVID-19. However, among cancer cases on conventional therapies, T cell lymphopenia was more profound, and these cases demonstrated higher levels of CD8+ exhausted (CD8+CD45RA-PD1+TIM3+ ), CD8+GranzymeB+ and CD4+CD38+HLA-DR+ and CD8+CD38+HLA-DR+ activated T cells when compared with controls;interestingly, these differences were not observed in patients who had received immune checkpoint inhibition. Thus, we found reduced viral RNA clearance and specific alterations in T cell and cytokine responses in cancer patients hospitalized with COVID-19 compared with matched controls with COVID-19. This dysregulated T cell response in cancer patients, which may reflect immune modulation due to chronic antigen stimulation as well as cancer therapies, may lead to altered virologic and clinical outcomes in this population.
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Background: Acute kidney injury (AKI) is common in patients with COVID-19 and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. Methods: We evaluated 19 urinary biomarkers of injury, inflammation, and repair in patients hospitalized with COVID-19 at 2 academic medical centers between April and June 2020. We associated biomarkers with a primary composite outcome of KDIGO stage 3 AKI, requirement for dialysis, or death within 60 days of admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. Results: Out of 157 patients, 24 (15.3%) experienced the primary outcome. Twofold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR: 1.53;95% CI: 1.33-1.76), monocyte chemoattractant protein (MCP-1) (HR: 1.86;95% CI: 1.48-2.33), and kidney injury molecule-1 (KIM-1) (HR: 2.32;95% CI: 1.69-3.18) were associated with highest risk of the primary outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR 0.52;95% CI: 0.40-0.69). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. Conclusions: Urinary biomarkers are associated with severe kidney complications in patients with COVID-19 and provide valuable information to monitor kidney disease recovery and progression.
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Background: This document provides evidence-based clinical practice guidelines on the diagnostic utility of nucleic acid-based testing of respiratory samples for viral pathogens other than influenza in adults with suspected community-acquired pneumonia (CAP). Methods: A multidisciplinary panel developed a Population-Intervention-Comparison-Outcome question, conducted a pragmatic systematic review, and applied Grading of Recommendations, Assessment, Development, and Evaluation methodology for clinical recommendations.
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Rationale: Similar to other human coronaviruses like MERS and SARS, severe manifestations of COVID-19 are associated with acute lung injury and sustained pulmonary dysfunction. A recent single-cell study of lung tissue from severe COVID-19 and idiopathic pulmonary fibrosis (IPF) patients suggested these diseases share common pro-fibrotic molecular pathways. To determine whether similar changes can be detected in the blood, we compared single-cell RNA-seq profiles of peripheral blood mononuclear cells (PBMCs) from patients with IPF or COVID-19, using influenza and healthy individuals as controls. Methods: 25 IPF, 18 COVID-19, and 13 healthy control PBMC samples were sequenced in our lab using 10X Genomics 5' single-cell technology. This data was processed using CellRanger and integrated with publicly available datasets of Covid-19, influenza, and healthy PBMC samples, yielding ∼300,000 single cells. Severe COVID-19 patients were treated in the ICU and succumbed to the disease, while severe IPF had transplant-free survival of fewer than three years. Downstream analysis was performed with the R package Seurat. The Louvain clustering algorithm generated 28 distinct cell clusters. Wilcoxon rank-sum test was used to determine significant cell type proportion differences and differentially expressed genes (DEGs). Significantly enriched pathways were found using EnrichR and Gene Set Enrichment Analysis (GSEA). Results: We report significantly increased platelets as a proportion of total cells in patients with severe COVID-19 (p = 0.0047) and severe IPF (p = 0.05) compared to healthy patients. Stable IPF and severe COVID-19 shared similar cell proportions of platelets (p=0.15) and monocytes (p=0.42). Across most cell types, COVID-19 and influenza patients had gene expression changes consistent with type I interferon activation while IPF patients exhibited changes in ribosomal upregulation and pro-fibrotic pathways relative to healthy controls. Using a composite pro-fibrotic score of TGFB1 targets and effectors, hierarchical clustering markedly differentiates between IPF and controls versus COVID-19 and influenza, perhaps distinctly highlighting mechanisms of disease. Within monocytes, we did not observe a significant pro-fibrotic phenotype (SPP1, MMP9, CHI3L1, PLA2G7) in samples of patients with any disease;hierarchical clustering of these genes again segregated IPF and controls from COVID-19 and influenza. Conclusions: Pro-fibrotic gene expression patterns could not be seen in PBMCs from patients with acute severe COVID-19 infection. More studies are needed in distinct COVID-19 patient populations, such as those with prolonged respiratory failure or with sustained respiratory dysfunction after recovery.
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RATIONALE: Biomarkers such as procalcitonin (PCT), ferritin, and D-dimer are widely used to guide the management of COVID-19. In particular, PCT has been utilized as an indicator for secondary bacterial infection, and D-dimer for venous thromboembolism. To better understand the clinical significance of these biomarkers, we studied their kinetics in two contrasting populations: patients with mild versus fulminant disease. METHODS: We conducted a retrospective cohort study of 739 adult patients hospitalized at Yale-New Haven Hospital with COVID-19 infection. Patients with mild disease were defined by recovery and eventual discharge;those with fulminant disease were defined by death during hospitalization. Patients were systematically tested for PCT, ferritin, and D-dimer;each was measured at least once every 30h on average. Biomarker data was subjected to transformation to satisfy the assumptions for linear regression analysis. The Mann-Whitney U test was used for comparison throughout given non-normal data distributions. RESULTS: Upon admission, PCT and D-dimer levels were significantly higher in patients admitted to the intensive care unit (median 0.21 ng/mL and 1.30 mg/L FEU) than in those admitted to general medical wards (median 0.10 ng/mL and 0.92 mg/L FEU) (p<0.001;p<0.001). Terminal PCT values during admission were 11.9 times higher in patients with fulminant versus mild disease (p<0.001) and terminal D-dimer values were 3.5 times higher (p<0.001). Linear regression analysis was used to assess the dynamics of PCT and D-dimer over time. During the first 21 days, both biomarkers decreased markedly in patients with mild disease (negative slopes of -0.12 ng/mL/day and -0.10 mg/L FEU/day) and increased in those with fulminant disease (positive slopes of 0.13 ng/mL/day and 0.51 mg/L FEU/day) (p<0.01;p<0.001). Rather than demonstrating divergent patterns determined by complications such as bacterial superinfection and thromboembolism, all three biomarkers trended closely together, as PCT correlated with both ferritin (R=0.39) and D-dimer (R=0.31). CONCLUSION: Our analysis of biomarker kinetics suggests that PCT, ferritin, and D-dimer may represent general indices of COVID-19 severity rather than specific markers of secondary complications. These results are consistent with decades of studies in sepsis, which have shown nonspecific elevation of inflammatory biomarkers. Further research is necessary to clarify their clinical relevance and diagnostic utility in COVID-19. ∗Nota bene: AC and GC contributed equally to this work and therefore may be listed in either order.
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Background: Initial CDC recommendations for passive monitoring of COVID-19 related symptoms among staff may not be sufficient in preventing the introduction and transmission of SARS-CoV-2 in healthcare settings. We therefore implemented active monitoring for SARS-CoV-2 infection in healthcare workers (HCWs) at an academic medical center during the COVID-19 epidemic in northeast US. Methods: We recruited a cohort of HCWs at Yale New Haven Hospital who worked in COVID-19 units and did not have COVID-19 related symptoms between March 28 and June 1, 2020. During follow-up, participants provided daily information on symptoms by responding to a web-based questionnaire, self-administered nasopharyngeal (NP) and saliva specimens every 3 days, and blood specimens every 14 days. We performed SARS-CoV-2 RT-PCR and an anti-spike protein IgM and IgG ELISA to identify virological and serological-confirmed infection, respectively. Results: We enrolled 525 (13%) amongst 4,136 HCW of whom daily information on symptoms and NP, saliva, and blood specimens were obtained for 66% (of 13208), 42% (or 1977), 44% (of 2071) and 65% (of 1099), respectively, of the follow-up measurement points. We identified 16 (3.0% of 525) HCWs with PCR-confirmed SARS-CoV-2 infection and an additional 12 (2.3% of 525) who were not tested by PCR or had negative PCR results but had serological evidence of infection. The overall cumulative incidence of SARS-CoV-2 infection was 5.3% (28 of 525) amongst HCWs. Cases were not identified by hospital protocols for passive staff self-monitoring for symptoms. Amongst 16 PCR-confirmed cases, 9 (56%) of the 16 PCR-confirmed HCW had symptoms during or after the date of initial detection. We did not identify an epidemiological link between the 28 confirmed cases. Conclusion: We found that a significant proportion (5.3%) of HCWs were infected with SARS-CoV-2 during the COVID-19 epidemic. In the setting of universal PPE use, infections were possibly acquired in the community rather than stemming from patient-HCW or HCW-HCW transmission. Passive monitoring of symptoms is inadequate in preventing introductions of SARS-CoV-2 into the healthcare setting due to asymptomatic and oligosymptomatic presentations.