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Background: Our multicentre, double-blind, randomised, placebo-controlled Azithromycin therapy for prevention of chronic lung disease of prematurity trial assessed if early 10-day azithromycin treatment improved survival without development of chronic lung disease of prematurity when compared with placebo in 796 preterm-born infants. Since antibiotic resistance remains a significant global health priority, we had preplanned macrolide-resistance assessment in recruited infants. We, therefore, identified baseline macrolide-resistant genes in respiratory samples and determined if this was altered by azithromycin treatment. Furthermore, we assessed if macrolide-resistant bacteria isolated from respiratory samples were also resistant to other common antibiotic classes.

Methods: Six common macrolide-resistant genes: erm(A), erm(B), erm(C), erm(F), mef(A/E) and msr(A) were identified by quantitative PCR (qPCR) from serial nasopharyngeal and endotracheal aspirates from recruited infants at baseline (pretreatment), day-5, day-10 and day-14 (post treatment). Azithromycin-resistant bacteria were assessed by culture in presence/absence of azithromycin and underlying resistance mechanisms were confirmed by qPCR. Resistance to other common antibiotics was also evaluated and molecular determinants were identified by whole genome sequencing.

Results: From 1108 (n=541 azithromycin, n=567 placebo) respiratory aspirates from 348 preterm infants, the overall prevalence of macrolide-resistant genes was similar in the placebo (63.7%) and azithromycin (63.9%) groups, with only erm(C) gene increased by azithromycin. Azithromycin-resistant bacteria were resistant to multiple clinically used antibiotics, being associated with several different underlying resistance mechanisms. Coagulase-negative staphylococci (CoNS) were the most recovered macrolide-resistant bacteria.

Conclusions: Macrolide-resistant genes were noticeably prevalent in the placebo group, with minimal increase with azithromycin treatment, suggesting that, regardless of the additional use of azithromycin, judicious use of antibiotics is required in preterm-born infants.

Introduction: Lung cancer is the leading cause of cancer-related death worldwide. Low-dose CT (LDCT) screening improves outcomes by detecting early-stage cancers as pulmonary nodules. As most are benign, diagnosing these nodules is challenging and often requires surveillance imaging. The aim of this study is to assess the frequency of cancer progression in a lung cancer screening study as measured by tumour stage (T-stage).

Methods: SUMMIT is a prospective cohort study assessing implementation of lung cancer screening with LDCT in a high-risk population. Screen-detected lung cancers with clinical tumour stage cT1a-c at time of referral were included. Upstaging was defined as an increase in T-stage from referral to treatment. The date of death was obtained from the National Cancer Registration and Analysis Service. Cox proportional hazards analysis with adjustment for age, sex, Charlson Comorbidity Index and pack years was used to assess mortality between groups.

Results: 390 screen-detected cancers were stage cT1a-c at time of referral. Upstaging occurred more frequently in cT1a (n=48, 56%) compared with cT1b (n=83, 38%) or cT1c (n=34, 40%), p=0.01. The proportion of part-solid nodules was similar between groups (upstaged-N=47, 27%, vs not upstaged-N=45, 21%, p=0.19). 43% of tumours increased T-stage from referral to first treatment (n=165). In participants upstaged, time from referral to treatment was longer (upstaged: 84 days, 46-298 vs not upstaged: 72 days, 43-211, p=0.04). Adjusted overall survival analyses showed an association between upstaging and mortality (HR 1.68, 95% CI 1.13 to 2.51, p=0.01).

Conclusion: Tumour upstaging occurred in nearly half of early-stage cases in a lung cancer screening population. Tumour upstaging was associated with longer time to treatment and poorer outcomes in this population.

Trial registration number: NCT03934866.

Background: Asthma is an umbrella diagnosis encompassing distinct pathophysiological mechanisms. While a global problem, our understanding of the interplay between respiratory microbiology and airway inflammation is largely from populations in high-income settings. As a result, treatment approaches align poorly with asthma characteristics in less studied populations.

Objective: To identify conserved and geographically distinct relationships between airway inflammation and microbiota characteristics in young people with and without asthma.

Methods: We conducted a cross-sectional study performing inflammatory phenotyping, microbiota analysis and enumeration of total bacteria, Haemophilus influenzae and Moraxella catarrhalis on 488 induced sputum samples from participants from Brazil (asthma: 68; non-asthma: 8), Ecuador (asthma: 89; non-asthma: 30), Uganda (asthma: 61; non-asthma: 8), New Zealand (asthma: 129; non-asthma: 58) and the UK (asthma: 25; non-asthma: 20). Microbiota characteristics were compared by country, asthma status and inflammatory characteristics, adjusting for age and sex.

Results: Asthma inflammatory phenotypes and microbiology differed between countries, with Uganda characterised by higher neutrophils, microbial diversity and bacterial abundance. Comparison of airway inflammation with microbiota characteristics showed conserved relationships across centres, with airway neutrophil proportion explaining variance in microbiota Bray-Curtis dissimilarity (p<0.001) and being positively associated with bacterial abundance, including H. influenzae and M. catarrhalis load (all p<0.05). In contrast, eosinophil proportion was less strongly associated with microbiota dissimilarity (p=0.033) and only associated with Streptococcus abundance. Country-specific associations between airway inflammation and microbiology were evident.

Conclusion: Both airway inflammation and microbiology varied geographically in young people with asthma. Associations between microbiota characteristics and neutrophilic phenotype were conserved.