Dataset Information

Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19.

ABSTRACT: Plasma SARS-CoV-2 viral RNA (vRNA) levels are predictive of COVID-19 outcomes in hospitalized patients, but whether plasma vRNA reflects lower respiratory tract (LRT) vRNA levels is unclear. We compared plasma and LRT vRNA levels in simultaneously collected longitudinal samples from mechanically-ventilated patients with COVID-19. LRT and plasma vRNA levels were strongly correlated at first sampling (r=0.83, p<10 ^-8 ) and then declined in parallel except in non-survivors who exhibited delayed vRNA clearance in LRT samples. Plasma vRNA measurement may offer a practical surrogate of LRT vRNA burden in critically ill patients, especially early in severe disease.

SUBMITTER: Jacobs JL

PROVIDER: S-EPMC8764731 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19.

Jacobs Jana L JL Naqvi Asma A Shah Faraaz A FA Boltz Valerie F VF Kearney Mary F MF McVerry Bryan J BJ Ray Prabir P Schaefer Caitlin C Fitzpatrick Meghan M Methé Barbara B Lee Janet J Morris Alison A Mellors John W JW Kitsios Georgios D GD Bain William W

medRxiv : the preprint server for health sciences 20220111

Plasma SARS-CoV-2 viral RNA (vRNA) levels are predictive of COVID-19 outcomes in hospitalized patients, but whether plasma vRNA reflects lower respiratory tract (LRT) vRNA levels is unclear. We compared plasma and LRT vRNA levels in simultaneously collected longitudinal samples from mechanically-ventilated patients with COVID-19. LRT and plasma vRNA levels were strongly correlated at first sampling (r=0.83, p<10 <sup>-8</sup> ) and then declined in parallel except in non-survivors who exhibited ...[more]

PMID: 35043122

Similar Datasets

Project description:BackgroundAntimicrobial resistance (AMR) is rising at an alarming rate and complicating the management of infectious diseases including lower respiratory tract infections (LRTI). Metagenomic next-generation sequencing (mNGS) is a recently established method for culture-independent LRTI diagnosis, but its utility for predicting AMR has remained unclear. We aimed to assess the performance of mNGS for AMR prediction in bacterial LRTI and demonstrate proof of concept for epidemiological AMR surveillance and rapid AMR gene detection using Cas9 enrichment and nanopore sequencing.MethodsWe studied 88 patients with acute respiratory failure between 07/2013 and 9/2018, enrolled through a previous observational study of LRTI. Inclusion criteria were age ≥ 18, need for mechanical ventilation, and respiratory specimen collection within 72 h of intubation. Exclusion criteria were decline of study participation, unclear LRTI status, or no matched RNA and DNA mNGS data from a respiratory specimen. Patients with LRTI were identified by clinical adjudication. mNGS was performed on lower respiratory tract specimens. The primary outcome was mNGS performance for predicting phenotypic antimicrobial susceptibility and was assessed in patients with LRTI from culture-confirmed bacterial pathogens with clinical antimicrobial susceptibility testing (n = 27 patients, n = 32 pathogens). Secondary outcomes included the association between hospital exposure and AMR gene burden in the respiratory microbiome (n = 88 patients), and AMR gene detection using Cas9 targeted enrichment and nanopore sequencing (n = 10 patients).ResultsCompared to clinical antimicrobial susceptibility testing, the performance of respiratory mNGS for predicting AMR varied by pathogen, antimicrobial, and nucleic acid type sequenced. For gram-positive bacteria, a combination of RNA + DNA mNGS achieved a sensitivity of 70% (95% confidence interval (CI) 47-87%) and specificity of 95% (CI 85-99%). For gram-negative bacteria, sensitivity was 100% (CI 87-100%) and specificity 64% (CI 48-78%). Patients with hospital-onset LRTI had a greater AMR gene burden in their respiratory microbiome versus those with community-onset LRTI (p = 0.00030), or those without LRTI (p = 0.0024). We found that Cas9 targeted sequencing could enrich for low abundance AMR genes by > 2500-fold and enabled their rapid detection using a nanopore platform.ConclusionsmNGS has utility for the detection and surveillance of resistant bacterial LRTI pathogens.

Project description:BackgroundUnlike other viruses, the pathogenicity of human metapneumovirus (hMPV) in adults remains uncertain. To address this question, a retrospective monocentric cohort including all patients admitted to ICU with hMPV infection between January 1, 2010, and June 30, 2018 was performed. The characteristics of hMPV infected patients were studied and compared to matched influenza infected patients. Consecutively, a systematic review and meta-analyses investigating PUBMED, EMBASE and COCHRANE databases was conducted to explore the hMPV infections in adult patients (PROSPERO number: CRD42018106617). Trials, case series, and cohorts published between January 1, 2008 and August 31, 2019 compiling adults presenting hMPV infections were included. Pediatric studies were excluded. Data were extracted from published reports. Primary endpoint was the rate of low respiratory tract infections (LRTIs) among all hMPV infected patients.ResultsDuring the study period, 402 patients were tested positive for hMPV. Among them 26 (6.5%) patients were admitted to the ICU, 19 (4.7%) for acute respiratory failure. Twenty-four (92%) were immunocompromised. Bacterial coinfections were frequent 53.8%. Hospital mortality rate was 30.8%. In the case-control analysis, the clinical and imaging characteristics were not different between hMPV and influenza infected patients. The systematic review identified 156 studies and 69 of them (1849 patients) were eligible for analysis. Although there was heterogeneity between the studies, the rate of hMPV LRTIs was 45% (95% CI 31-60%; I2 = 98%). Intensive care unit (ICU) admission was required for 33% (95% CI 21-45%; I2 = 99%). Hospital mortality rate was 10% (95% CI 7-13%; I2 = 83%) and ICU mortality rate was 23% (95% CI 12-34%; I2 = 65%). Underlying malignancy was independently associated with increased mortality rate.ConclusionsThis preliminary work suggested that hMPV may be associated with severe infection and high mortality in patients with underlying malignancies. However, regarding the small size of the cohort and the heterogeneity of the review, more cohort studies are warranted.

Project description:BACKGROUNDLower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging because noninfectious respiratory illnesses appear clinically similar and because existing microbiologic tests are often falsely negative or detect incidentally carried microbes, resulting in antimicrobial overuse and adverse outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and treatment remains unclear.METHODSWe used tracheal aspirate RNA-Seq to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n = 117) or of noninfectious respiratory failure (n = 50). We then developed a classifier that integrates the host LRTI probability, abundance of respiratory viruses, and dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm.RESULTSThe host classifier achieved a median AUC of 0.967 by cross-validation, driven by activation markers of T cells, alveolar macrophages, and the interferon response. The integrated classifier achieved a median AUC of 0.986 and increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n = 94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those.CONCLUSIONLower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.FUNDINGSupport for this study was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Heart, Lung, and Blood Institute (UG1HD083171, 1R01HL124103, UG1HD049983, UG01HD049934, UG1HD083170, UG1HD050096, UG1HD63108, UG1HD083116, UG1HD083166, UG1HD049981, K23HL138461, and 5R01HL155418) as well as by the Chan Zuckerberg Biohub.

Project description:Objective: Critically ill patients with acute respiratory distress syndrome (ARDS) due to viral infection are at risk for secondary complications, including invasive aspergillosis. Our study aimed to characterize the clinical significance and outcome of Aspergillus species isolated from lower-respiratory-tract samples of critically ill OVID-19 patients at a single center. Design: We conducted a retrospective cohort study to evaluate the characteristics of patients with COVID-19 and aspergillus isolated from the lower respiratory tract and to identify predictors of outcomes in this population. Setting: The setting was a single-center hospital system within the metropolitan Detroit region. Results: The prevalence of Aspergillus isolated in hospitalized COVID-19 patients was 1.18% (30/2461 patients), and it was 4.6% in critically ill ICU patients with COVID-19. Probable COVID-19-associated invasive pulmonary aspergillosis (CAPA) was found in 21 critically ill patients, and 9 cases were classified as colonization. The in-hospital mortality of critically ill patients with CAPA and those with aspergillus colonization were high but not significantly different (76% vs. 67%, p = 1.00). Furthermore, the in-hospital mortality for ICU patients with or without Aspergillus isolated was not significantly different 73.3% vs. 64.5%, respectively (OR 1.53, CI 0.64-4.06, p = 0.43). In patients in whom Aspergillus was isolated, antifungal therapy (p = 0.035, OR 12.3, CI 1.74-252); vasopressors (0.016, OR 10.6, CI 1.75-81.8); and a higher mSOFA score (p = 0.043, OR 1.29 CI 1.03-1.72) were associated with a worse outcome. In a multivariable model adjusting for other significant variables, FiO2 was the only variable associated with in-hospital mortality in patients in whom Aspergillus was isolated (OR 1.07, 95% CI 1.01-1.27). Conclusions: The isolation of Aspergillus from lower-respiratory-tract samples of critically ill patients with COVID-19 is associated with high mortality. It is important to have a low threshold for superimposed infections such as CAPA in critically ill patients with COVID-19.

Dataset Information

Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19.

Publications

Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets