Trajectories of host-response biomarkers and inflammatory subphenotypes in COVID-19 patients across the spectrum of respiratory support. (preprint)

Purpose: Enhanced understanding of the dynamic changes in the dysregulated inflammatory response in COVID-19 may help improve patient selection and timing for immunomodulatory therapies. Methods: We enrolled 323 COVID-19 inpatients on different levels of baseline respiratory support: i) Low Flow Oxygen (37%), ii) Non-Invasive Ventilation or High Flow Oxygen (NIV_HFO, 29%), iii) Invasive Mechanical Ventilation (IMV, 27%), and iv) Extracorporeal Membrane Oxygenation (ECMO, 7%). We collected plasma samples upon enrollment and days 5 and 10 to measure host-response biomarkers. We classified subjects into inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker and subphenotype trajectories and outcomes during hospitalization. Results: IL-6, procalcitonin, and Angiopoietin-2 were persistently elevated in patients at higher levels of respiratory support, whereas sRAGE displayed the inverse pattern. Patients on NIV_HFO at baseline had the most dynamic clinical trajectory, with 26% eventually requiring intubation and exhibiting worse 60-day mortality than IMV patients at baseline (67% vs. 35%, p<0.0001). sRAGE levels predicted NIV failure and worse 60-day mortality for NIV_HFO patients, whereas IL-6 levels were predictive in IMV or ECMO patients. Hyper-inflammatory subjects at baseline (<10% by both models) had worse 60-day survival (p<0.0001) and 50% of them remained classified as hyper-inflammatory on follow-up sampling at 5 days post-enrollment. Receipt of combined immunomodulatory therapies (steroids and anti-IL6 agents) was associated with markedly increased IL-6 and lower Angiopoietin-2 levels (p<0.05). Conclusions: Longitudinal study of systemic host responses in COVID-19 revealed substantial and predictive inter-individual variability, influenced by baseline levels of respiratory support and concurrent immunomodulatory therapies.

Noninvasive diagnosis of secondary infections in COVID-19 by sequencing of plasma microbial cell-free DNA. (preprint)

Background: Secondary infection (SI) diagnosis in COVID-19 is challenging, due to overlapping clinical presentations, practical limitations in obtaining samples from the lower respiratory tract (LRT), and low sensitivity of microbiologic cultures. Research Question: Can metagenomic sequencing of plasma microbial cell-free DNA (mcfDNA-Seq) help diagnose SIs complicating COVID-19? Study Design and Methods: We enrolled 42 inpatients with COVID-19 classified as microbiologically-confirmed SI (Micro-SI, n=8), clinically-diagnosed SI (Clinical-SI, n=13, i.e. empiric antimicrobials), or no clinical suspicion for SI (No-Suspected-SI, n=21) at time of enrollment. From baseline and follow-up plasma samples (days 5 and 10 post-enrollment), we quantified mcfDNA for all detected microbes by mcfDNA sequencing and measured nine host-response biomarkers. From LRT samples among intubated subjects, we quantified bacterial burden with 16S rRNA gene quantitative PCR. Results: We performed mcfDNA-Seq in 82 plasma samples. Sequencing was successful in 60/82 (73.2%) samples, which had significantly lower levels of human cfDNA than failed samples (p<0.0001). McfDNA detection was significantly higher in Micro-SI (15/16 [94%]) compared to Clinical-SI samples (8/14 [57%], p=0.03), and unexpectedly common in No-Suspected-SI samples (25/30 [83%]), similar to detection rate in Micro-SI. We detected culture-concordant mcfDNA species in 13/16 Micro-SI samples (81%) and mcfDNA levels tracked with SI outcome (resolution or persistence) under antibiotic therapy. McfDNA levels correlated significantly with LRT bacterial burden (r=0.74, p=0.02) as well as plasma biomarkers of host response (white blood cell count, IL-6, IL-8, and SPD, all p<0.05). Baseline mcfDNA levels were predictive of worse 90-day survival (hazard ratio 1.30 [1.02-1.64] for each log10 mcfDNA, p=0.03). Interpretation: High circulating levels of mcfDNA in a substantial proportion of patients with COVID-19 without clinical suspicion for SI suggest that SIs may often remain undiagnosed. McfDNA-Seq, when clinically available, can offer a non-invasive diagnostic tool for pathogen identification, with prognostic value on host inflammatory response and clinical outcomes.

Radiographic Assessment of Lung Edema (RALE) Scores are Highly Reproducible and Prognostic of Clinical Outcomes for Inpatients with COVID-19 (preprint)

INTRODUCTION: Chest imaging is necessary for diagnosis of COVID-19 pneumonia, but current risk stratification tools do not consider radiographic severity. We quantified radiographic heterogeneity among inpatients with COVID-19 with the Radiographic Assessment of Lung Edema (RALE) score on Chest X-rays (CXRs). METHODS: We performed independent RALE scoring by [≥]2 reviewers on baseline CXRs from 425 inpatients with COVID-19 (discovery dataset), we recorded clinical variables and outcomes, and measured plasma host-response biomarkers and SARS-CoV-2 RNA load from subjects with available biospecimens. RESULTS: We found excellent inter-rater agreement for RALE scores (intraclass correlation co-efficient=0.93). The required level of respiratory support at the time of baseline CXRs (supplemental oxygen or non-invasive ventilation [n=178]; invasive-mechanical ventilation [n=234], extracorporeal membrane oxygenation [n=13]) was significantly associated with RALE scores (median [interquartile range]: 20.0[14.1-26.7], 26.0[20.5-34.0] and 44.5[34.5-48.0], respectively, p<0.0001). Among invasively-ventilated patients, RALE scores were significantly associated with worse respiratory mechanics (plateau and driving pressure) and gas exchange metrics (PaO2/FiO2 and ventilatory ratio), as well as higher plasma levels of IL-6, sRAGE and TNFR1 levels (p<0.05). RALE scores were independently associated with 90-day survival in a multivariate Cox proportional hazards model (adjusted hazard ratio 1.04[1.02-1.07], p=0.002). We validated significant associations of RALE scores with baseline severity and mortality in an independent dataset of 415 COVID-19 inpatients. CONCLUSION: Reproducible assessment of radiographic severity revealed significant associations with clinical and physiologic severity, host-response biomarkers and clinical outcome in COVID-19 pneumonia. Incorporation of radiographic severity assessments may provide prognostic and treatment allocation guidance in patients hospitalized with COVID-19.