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Background Experimental studies support a link between obesity and pulmonary hypertension (PH), yet clinical studies have been limited. This study sought to determine the association of obesity and pulmonary hemodynamic measures and mortality in PH. Methods and Results We examined patients undergoing right‐sided heart catherization (2005–2016) in a hospital‐based cohort. Multivariable regression models tested associations of body mass index and pulmonary vascular hemodynamics, with PH defined as mean pulmonary artery pressure >20 mm Hg, and further subclassified into precapillary, postcapillary, and mixed PH. Multivariable Cox models were used to examine the effect of PH and obesity on mortality. Among 8940 patients (mean age, 62 years; 40% women), 52% of nonobese and 69% of obese individuals had evidence of PH. Higher body mass index was independently associated with greater odds of overall PH (odds ratio, 1.34; 95% CI, 1.29–1.40; P <0.001 per 5‐unit increase in body mass index) as well as each PH subtype ( P <0.001 for all). Patients with PH had greater risk of mortality compared with individuals without PH regardless of subgroup ( P <0.001 for all). We found that obesity was associated with 23% lower hazard of mortality among patients with PH (hazard ratio, 0.77; 95% CI, 0.69–0.85; P <0.001). The effect of obesity was greatest among those with precapillary PH (hazard ratio, 0.57; 95% CI, 0.46–0.70; P <0.001), where obesity modified the effect of PH on mortality ( P for interaction=0.02). Conclusions Obesity is independently associated with PH. PH is associated with greater mortality; this is modified by obesity such that obese patients with precapillary PH have lower mortality compared with nonobese counterparts. Further studies are needed to elucidate mechanisms underlying obesity‐related PH.

We carried out integrated host and pathogen metagenomic RNA and DNA next generation sequencing (mNGS) of whole blood (n = 221) and plasma (n = 138) from critically ill patients following hospital admission. We assigned patients into sepsis groups on the basis of clinical and microbiological criteria. From whole-blood gene expression data, we distinguished patients with sepsis from patients with non-infectious systemic inflammatory conditions using a trained bagged support vector machine (bSVM) classifier (area under the receiver operating characteristic curve (AUC) = 0.81 in the training set; AUC = 0.82 in a held-out validation set). Plasma RNA also yielded a transcriptional signature of sepsis with several genes previously reported as sepsis biomarkers, and a bSVM sepsis diagnostic classifier (AUC = 0.97 training set; AUC = 0.77 validation set). Pathogen detection performance of plasma mNGS varied on the basis of pathogen and site of infection. To improve detection of virus, we developed a secondary transcriptomic classifier (AUC = 0.94 training set; AUC = 0.96 validation set). We combined host and microbial features to develop an integrated sepsis diagnostic model that identified 99% of microbiologically confirmed sepsis cases, and predicted sepsis in 74% of suspected and 89% of indeterminate sepsis cases. In summary, we suggest that integrating host transcriptional profiling and broad-range metagenomic pathogen detection from nucleic acid is a promising tool for sepsis diagnosis.

Background Antimicrobial 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. Methods We 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). Results Compared 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. Conclusions mNGS has utility for the detection and surveillance of resistant bacterial LRTI pathogens.

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BackgroundMany individuals hospitalised with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection experience post-acute sequelae of SARS-CoV-2 infection (PASC), sometimes referred to as “long COVID”. Our objective was to conduct a systematic literature review and meta-analysis to identify PASC-associated symptoms in previously hospitalised patients and determine the frequency and temporal nature of PASC.MethodsSearches of MEDLINE, Embase, Cochrane Library (2019–2021), World Health Organization International Clinical Trials Registry Platform and reference lists were performed from November to December 2021. Articles were assessed by two reviewers against eligibility criteria and a risk of bias tool. Symptom data were synthesised by random effects meta-analyses.ResultsOf 6942 records, 52 studies with at least 100 patients were analysed; ∼70% were Europe-based studies. Most data were from the first wave of the pandemic. PASC symptoms were analysed from 28 days after hospital discharge. At 1–4 months post-acute SARS-CoV-2 infection, the most frequent individual symptoms were fatigue (29.3% (95% CI 20.1–40.6%)) and dyspnoea (19.6% (95% CI 12.8–28.7%)). Many patients experienced at least one symptom at 4–8 months (73.1% (95% CI 44.2–90.3%)) and 8–12 months (75.0% (95% CI 56.4–87.4%)).ConclusionsA wide spectrum of persistent PASC-associated symptoms were reported over the 1-year follow-up period in a significant proportion of participants. Further research is needed to better define PASC duration and determine whether factors such as disease severity, vaccination and treatments have an impact on PASC.

Staphylococcus argenteus is a novel staphylococcal species associated with invasive disease. We report the first case of daptomycin/vancomycin-resistant S. argenteus, initially speciated as S. aureus, that developed from repeated treatment with daptomycin for a complex vascular graft infection. Whole genome sequencing of longitudinally collected isolates identified acquisition of MprF S337L, a mutation predicted to increase surface charge and repel cationic molecules.