Lower respiratory tract and plasma SARS-CoV-2 RNA load in critically ill adult COVID-19 patients: Relationship with biomarkers of disease severity.
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ABSTRACT:
SUBMITTER: Olea B
PROVIDER: S-EPMC8168298 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
Publications
Lower respiratory tract and plasma SARS-CoV-2 RNA load in critically ill adult COVID-19 patients: Relationship with biomarkers of disease severity.
Olea Beatriz B Albert Eliseo E Torres Ignacio I Gozalbo-Rovira Roberto R Carbonell Nieves N Ferreres José J Poujois Sandrine S Costa Rosa R Colomina Javier J Rodríguez Jesús J Blasco María Luisa ML Navarro David D
The Journal of infection 20210601 3
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Project description:COVID-19 infection may predispose to secondary bacterial infection which is associated with poor clinical outcome especially among critically ill patients. We aimed to characterize the lower respiratory tract bacterial microbiome of COVID-19 critically ill patients in comparison to COVID-19-negative patients. We performed a 16S rRNA profiling on bronchoalveolar lavage (BAL) samples collected between April and May 2020 from 24 COVID-19 critically ill subjects and 24 patients with non-COVID-19 pneumonia. Lung microbiome of critically ill patients with COVID-19 was characterized by a different bacterial diversity (PERMANOVA on weighted and unweighted UniFrac Pr(> F) = 0.001) compared to COVID-19-negative patients with pneumonia. Pseudomonas alcaligenes, Clostridium hiranonis, Acinetobacter schindleri, Sphingobacterium spp., Acinetobacter spp. and Enterobacteriaceae, characterized lung microbiome of COVID-19 critically ill patients (LDA score > 2), while COVID-19-negative patients showed a higher abundance of lung commensal bacteria (Haemophilus influenzae, Veillonella dispar, Granulicatella spp., Porphyromonas spp., and Streptococcus spp.). The incidence rate (IR) of infections during COVID-19 pandemic showed a significant increase of carbapenem-resistant Acinetobacter baumannii (CR-Ab) infection. In conclusion, SARS-CoV-2 infection and antibiotic pressure may predispose critically ill patients to bacterial superinfection due to opportunistic multidrug resistant pathogens.
| S-EPMC8115177 | biostudies-literature
Project description:BACKGROUND. Lower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging since non-infectious respiratory illnesses appear clinically similar and existing microbiologic tests are often falsely negative or detect incidentally-carried microbes common in children. These challenges result in antimicrobial overuse and adverse patient 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 precision treatment remains unclear. METHODS. We used tracheal aspirate RNA-sequencing to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a random forest gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n=117) or of non-infectious respiratory failure (n=50). We then developed a classifier that integrates the: i) host LRTI probability, ii) abundance of respiratory viruses, and iii) dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm. RESULTS. The host classifier achieved a median AUC of 0.967 by 5-fold 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 significantly 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. CONCLUSIONS. Lower 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.
2022-12-06 | GSE212532 | GEO
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.
| S-EPMC9275031 | biostudies-literature
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.
| S-EPMC10026215 | biostudies-literature
Project description:BackgroundIncreasing evidence has associated positive fluid balance of critically ill patients with poor outcomes. The aim of this study was to explore the pattern of daily fluid balances and their association with outcomes in critically ill children with lower respiratory tract viral infection.MethodsA retrospective single-center study was conducted, in children supported with high-flow nasal cannula, non-invasive ventilation, or invasive ventilation. Median (interquartile range) daily fluid balances, cumulative fluid overload (FO) and peak FO variation, indexed as the % of admission body weight, over the first week of Pediatric Intensive Care Unit admission, and their association with the duration of respiratory support were assessed.ResultsOverall, 94 patients with a median age of 6.9 (1.9-18) months, and a respiratory support duration of 4 (2-7) days, showed a median (interquartile range) daily fluid balance of 18 (4.5-19.5) ml/kg at day 1, which decreased up to day 3 to 5.9 (- 14 to 24.9) ml/kg and increased to 13 (- 11 to 29.9) ml/kg at day 7 (p = 0.001). Median cumulative FO% was 4.6 (- 0.8 to 11) and peak FO% was 5.7 (1.9-12.4). Daily fluid balances, once patients were stratified according to the respiratory support, were significantly lower in those requiring mechanical ventilation (p = 0.003). No correlation was found between all examined fluid balances and respiratory support duration or oxygen saturation, even after subgroup analysis of patients with invasive mechanical ventilation, or respiratory comorbidities, or bacterial coinfection, or of patients under 1 year old.ConclusionsIn a cohort of children with bronchiolitis, fluid balance was not associated with duration of respiratory support or other parameters of pulmonary function.
| S-EPMC10141805 | biostudies-literature
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.
| S-EPMC10065066 | biostudies-literature
Project description:Among critically ill patients with lower respiratory tract (LRT)-confirmed influenza, we retrospectively observed worse 28-day clinical outcomes in upper respiratory tract (URT)-negative versus URT-positive subjects. This finding may reflect disease progression and highlights the need for influenza testing of both URT and LRT specimens to improve diagnostic yield and possibly inform prognosis.
| S-EPMC4784015 | biostudies-literature
Project description:Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.
| S-EPMC6310811 | biostudies-literature
Project description: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 serially collected samples from mechanically ventilated patients with COVID-19. LRT and plasma vRNA levels were strongly correlated at first sampling (n = 33, r = 0.83, P < 10-9) and then declined in parallel in available serial samples except in nonsurvivors 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 after ICU admission.
| S-EPMC10205612 | biostudies-literature
Project description: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.
| S-EPMC8764731 | biostudies-literature