Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Jacobs JL
PROVIDER: S-EPMC8764731 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
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: Not available
| S-EPMC8168298 | biostudies-literature
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: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: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: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:Lower respiratory tract infections (LRTIs) are a major cause of morbidity and death. Because of changes in how LRTIs are defined coupled with the increasing prevalence of drug resistance, there is a gap in knowledge regarding the current burden of antimicrobial use for Centers for Disease Control and Prevention (CDC)-defined LRTIs. We describe the infection characteristics, antibiotic consumption, and clinical and economic outcomes of patients with Gram-negative (GN) LRTIs treated in intensive care units (ICUs).This was a retrospective, observational, cross-sectional study of adult patients treated in ICUs at two large academic medical centers in metropolitan Detroit, Michigan, from October 2013 to October 2015. To meet the inclusion criteria, patients must have had CDC-defined LRTI caused by a GN pathogen during ICU stay. Microbiological assessment of available Pseudomonas aeruginosa isolates included minimum inhibitory concentrations for key antimicrobial agents.Four hundred and seventy-two patients, primarily from the community (346, 73.3%), were treated in medical ICUs (272, 57.6%). Clinically defined pneumonia was common (264, 55.9%). Six hundred and nineteen GN organisms were identified from index respiratory cultures: P. aeruginosa was common (224, 36.2%), with 21.6% of these isolates being multidrug resistant. Cefepime (213, 45.1%) and piperacillin/tazobactam (174, 36.8%) were the most frequent empiric GN therapies. Empiric GN therapy was inappropriate in 44.6% of cases. Lack of in vitro susceptibility (80.1%) was the most common reason for inappropriateness. Patients with inappropriate empiric GN therapy had longer overall stay, which translated to a median total cost of care of $79,800 (interquartile range $48,775 to $129,600) versus $68,000 (interquartile range $38,400 to $116,175), p = 0.013. Clinical failure (31.5% vs 30.0%, p = 0.912) and in-hospital all-cause mortality (26.4% vs 25.9%, p = 0.814) were not different.Drug-resistant pathogens were frequently found and empiric GN therapy was inappropriate in nearly 50% of cases. Inappropriate therapy led to increased lengths of stay and was associated with higher costs of care.
| S-EPMC5840098 | biostudies-literature
Project description:BackgroundData on SARS-CoV-2 load in lower respiratory tract (LRT) are scarce. Our objectives were to describe the viral shedding and the viral load in LRT and to determine their association with mortality in critically ill COVID-19 patients.MethodsWe conducted a binational study merging prospectively collected data from two COVID-19 reference centers in France and Switzerland. First, we described the viral shedding duration (i.e., time to negativity) in LRT samples. Second, we analyzed viral load in LRT samples. Third, we assessed the association between viral presence in LRT and mortality using mixed-effect logistic models for clustered data adjusting for the time between symptoms' onset and date of sampling.ResultsFrom March to May 2020, 267 LRT samples were performed in 90 patients from both centers. The median time to negativity was 29 (IQR 23; 34) days. Prolonged viral shedding was not associated with age, gender, cardiac comorbidities, diabetes, immunosuppression, corticosteroids use, or antiviral therapy. The LRT viral load tended to be higher in non-survivors. This difference was statistically significant after adjusting for the time interval between onset of symptoms and date of sampling (OR 3.78, 95% CI 1.13-12.64, p = 0.03).ConclusionsThe viral shedding in LRT lasted almost 30 days in median in critically ill patients, and the viral load in the LRT was associated with the 6-week mortality.
| S-EPMC7562762 | biostudies-literature
Project description:Pairs of SARS-CoV-2 genomes from upper and lower respiratory tract of different individuals
| PRJEB42830 | ENA