Microbial diversity and antimicrobial resistance in faecal samples from acute medical patients assessed through metagenomic sequencing

Antimicrobial resistance (AMR) is a threat to global public health. However, unsatisfactory approaches to directly measuring the AMR burden carried by individuals has hampered efforts to assess interventions aimed at reducing selection for AMR. Metagenomics can provide accurate detection and quantification of AMR genes within an individual person’s faecal flora (their gut “resistome”). Using this approach, we aimed to test the hypothesis that differences in antimicrobial use across different hospitals in the United Kingdom will result in observable differences in the resistome of individual patients. Three National Health Service acute Hospital Trusts with markedly different antibiotic use and Clostridioides difficile infection rates collected faecal samples from anonymous patients which were discarded after C. difficile testing over a period of 9 to 15 months. Metagenomic DNA was extracted from these samples and sequenced using an Illumina NovaSeq 6000 platform. The resulting sequencing reads were analysed for taxonomic composition and for the presence of AMR genes. Among 683 faecal metagenomes we found huge variation between individuals in terms of taxonomic diversity (Shannon Index range 0.10–3.99) and carriage of AMR genes (Median 1.50 genes/cell/sample overall). We found no statistically significant differences in diversity (median Shannon index 2.16 (IQR 1.71–2.56), 2.15 (IQR 1.62–2.50) and 2.26 (IQR 1.55–2.51)) or carriage of AMR genes (median 1.37 genes/cell/sample (IQR 0.70–3.24), 1.70 (IQR 0.70–4.52) and 1.43 (IQR 0.55–3.71)) at the three trusts respectively. This was also the case across the sample collection period within the trusts. While we have not demonstrated differences over place or time using metagenomic sequencing of faecal discards, other sampling frameworks may be more suitable to determine whether organisational level differences in antibiotic use are associated with individual-level differences in burden of AMR carriage

Antibiotic Review Kit for Hospitals (ARK-Hospital): a stepped wedge cluster randomised controlled trial

Background: Strategies to reduce antibiotic overuse in hospitals depend on clinicians reviewing antibiotics which have been started empirically. There is a lack of evidence on how to do this effectively. We evaluated a multifaceted behaviour change intervention (ARK) aimed at reducing antibiotic consumption in hospitals by increasing prescriber decisions to stop antibiotics at clinical review. Methods: We performed a stepped-wedge, hospital-level, cluster -randomised controlled trial using computer-generated sequence randomisation of 39 acute hospitals to 7 calendar-time blocks (12/February/2018–01/July/2019). Co-primary outcomes were monthly antibiotic defined-dailydoses (DDD) per acute/medical admission (organisation-level, superiority) and all-cause 30-day mortality (patient-level, non-inferiority, margin 5%). Clusters were eligible if they admitted nonelective medical patients, could identify an intervention “champion” and provide pre-intervention data from February/2016. Sites were followed up for a minimum of 14 months. Intervention effects were assessed using interrupted time series analyses in each cluster. Overall effects were derived through random-effects meta-analysis, using meta-regression to assess heterogeneity in effects across prespecified factors. Trial registration was ISRCTN12674243. Findings: Adjusted estimates showed a year-on-year reduction in antibiotic consumption (-4.8%, 95%CI: -9.1%,-0.2%, p=0.042) following the ARK intervention. Among 7,160,421 acute/medicaladmissions, we observed a -2.7% (95%CI: -5.7%,+0.3%, p=0.079) immediate and +3.0% (95%CI: - 0.1%,+6.2%, p=0.060) sustained change in adjusted 30-day mortality. This mortality trend was not related to the magnitude of antibiotic reduction achieved (Spearman’s ρ=0.011, p=0.949). Whilst 90- day mortality odds appeared to increase over time (+3.9%, 95%CI:+0.5%,+7.4%, p=0.023), this was not observed among admissions before COVID-19 onset (+3.2%, 95%CI:-1.5%,+8.2%, p=0.182). Length of hospital stay was unaffected. Interpretation: The weak, inconsistent effects of the intervention on mortality are likely to be explained by the COVID-19 pandemic onset during the post-implementation phase. We conclude that the ARK-intervention resulted in sustained, safe reductions in hospital antibiotic use

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Impact of hospital antibiotic use on patient-level risk of death among 36,124,372 acute and medical admissions in England

Objectives: Initiatives to curb hospital antibiotic use might be associated with harm from under-treatment. We examined the extent to which variation in hospital antibiotic prescribing is associated with mortality risk in acute/general medicine inpatients. Methods: This ecological analysis examined Hospital Episode Statistics from 36,124,372 acute/general medicine admissions (≥16y) to 135 acute hospitals in England, 01/April/2010–31/March/2017. Random-effects meta-regression was used to investigate whether heterogeneity in adjusted 30-day mortality was associated with hospital-level antibiotic use, measured in defined-daily-doses (DDD)/1,000 bed-days. Models also considered DDDs/1,000 admissions and DDDs for narrow-spectrum/broad-spectrum antibiotics, parenteral/oral, and local interpretations of World Health Organization Access, Watch, and Reserve antibiotics. Results: Hospital-level antibiotic DDDs/1,000 bed-days varied 15-fold with comparable variation in broad-spectrum, parenteral, and Reserve antibiotic use. After extensive adjusting for hospital case-mix, the probability of 30-day mortality changed -0.010% (95% CI: -0.064,+0.044) for each increase of 500 hospital-level antibiotic DDDs/1,000 bed-days. Analyses of other metrics of antibiotic use showed no consistent association with mortality risk. Conclusions: We found no evidence that wide variation in hospital antibiotic use is associated with adjusted mortality risk in acute/general medicine inpatients. Using low-prescribing hospitals as benchmarks could help drive safe and substantial reductions in antibiotic consumption of up-to one-third in this population

Microbial diversity and antimicrobial resistance in faecal samples from acute medical patients assessed through metagenomic sequencing

Antimicrobial resistance (AMR) is a threat to global public health. However, unsatisfactory approaches to directly measuring the AMR burden carried by individuals has hampered efforts to assess interventions aimed at reducing selection for AMR. Metagenomics can provide accurate detection and quantification of AMR genes within an individual person’s faecal flora (their gut “resistome”). Using this approach, we aimed to test the hypothesis that differences in antimicrobial use across different hospitals in the United Kingdom will result in observable differences in the resistome of individual patients. Three National Health Service acute Hospital Trusts with markedly different antibiotic use and Clostridioides difficile infection rates collected faecal samples from anonymous patients which were discarded after C. difficile testing over a period of 9 to 15 months. Metagenomic DNA was extracted from these samples and sequenced using an Illumina NovaSeq 6000 platform. The resulting sequencing reads were analysed for taxonomic composition and for the presence of AMR genes. Among 683 faecal metagenomes we found huge variation between individuals in terms of taxonomic diversity (Shannon Index range 0.10–3.99) and carriage of AMR genes (Median 1.50 genes/cell/sample overall). We found no statistically significant differences in diversity (median Shannon index 2.16 (IQR 1.71–2.56), 2.15 (IQR 1.62–2.50) and 2.26 (IQR 1.55–2.51)) or carriage of AMR genes (median 1.37 genes/cell/sample (IQR 0.70–3.24), 1.70 (IQR 0.70–4.52) and 1.43 (IQR 0.55–3.71)) at the three trusts respectively. This was also the case across the sample collection period within the trusts. While we have not demonstrated differences over place or time using metagenomic sequencing of faecal discards, other sampling frameworks may be more suitable to determine whether organisational level differences in antibiotic use are associated with individual-level differences in burden of AMR carriage

Predicting the Need for Third-Line Antiretroviral Therapy by Identifying Patients at High Risk for Failing Second-Line Antiretroviral Therapy in South Africa

Although third-line antiretroviral therapy (ART) is available in South Africa’s public sector, its cost is substantially higher than first and second line. Identifying risk factors for failure on second-line treatment remains crucial to reduce the need for third-line drugs. We conducted a case–control study including 194 adult patients (‡18 years; 70 cases and 124 controls) who initiated second-line ART in Johannesburg, South Africa. Unconditional logistic regression was used to assess predictors of virologic failure (defined as 2 consecutive viral load measures ‡1000 copies/mL, ‡3months after switching to second line). Variables included a social instability index, ART adherence, self-reported as well as diagnosed adverse drug reactions (ADRs), HIV disclosure, depression, and factors affecting access to HIV clinics. Overall 60.0% of cases and 54.0% of controls were female. Mean ages of cases and controls were 41.8 – 9.6 and 43.3 – 8.0, respectively. Virologic failure was predicted by ART adherence <90% [odds ratio (OR) 4.7; 95% confidence interval (95% CI): 2.1–10.5], younger age (<40 years of age; OR 0.6; 95% CI: 0.3–1.1), high social instability (OR 3.8; 95% CI: 1.30–11.5), self-reported ADR (OR 1.9; 95% CI: 1.0–3.5), disclosure to friends/colleagues rather than partner/relatives (OR3.4; 95%CI: 1.3–9.1), andmedium/high depression compared to low/no depression (OR 4.4; 95% CI: 1.5–13.4). Our results suggest complex socioeconomic factors contributing to risk of virologic failure, possibly by impacting ART adherence, among patients on second-line therapy in South Africa. Identifying patients with possible indicators of nonadherence could facilitate targeted interventions to reduce the risk of second-line treatment failure and mitigate the demand for third-line regimens

Microbial diversity and antimicrobial resistance in faecalsamples from acute medical patients assessed through metagenomic sequencing

Antimicrobial resistance (AMR) is a threat to global public health. However, unsatisfactory approaches to directly measuring the AMR burden carried by individuals has hampered efforts to assess interventions aimed at reducing selection for AMR. Metagenomics can provide accurate detection and quantification of AMR genes within an individual person’s faecal flora (their gut “resistome”). Using this approach, we aimed to test the hypothesis that differences in antimicrobial use across different hospitals in the United Kingdom will result in observable differences in the resistome of individual patients. Three National Health Service acute Hospital Trusts with markedly different antibiotic use and Clostridioides difficile infection rates collected faecal samples from anonymous patients which were discarded after C. difficile testing over a period of 9 to 15 months. Metagenomic DNA was extracted from these samples and sequenced using an Illumina NovaSeq 6000 platform. The resulting sequencing reads were analysed for taxonomic composition and for the presence of AMR genes. Among 683 faecal metagenomes we found huge variation between individuals in terms of taxonomic diversity (Shannon Index range 0.10–3.99) and carriage of AMR genes (Median 1.50 genes/cell/sample overall). We found no statistically significant differences in diversity (median Shannon index 2.16 (IQR 1.71–2.56), 2.15 (IQR 1.62–2.50) and 2.26 (IQR 1.55–2.51)) or carriage of AMR genes (median 1.37 genes/cell/sample (IQR 0.70–3.24), 1.70 (IQR 0.70–4.52) and 1.43 (IQR 0.55–3.71)) at the three trusts respectively. This was also the case across the sample collection period within the trusts. While we have not demonstrated differences over place or time using metagenomic sequencing of faecal discards, other sampling frameworks may be more suitable to determine whether organisational level differences in antibiotic use are associated with individual-level differences in burden of AMR carriage