A Phase I trial of Non-invasive Ventilation and seizure prophylaxis with levetiracetam In Children with Cerebral Malaria Trial (NOVICE-M Trial).

Background: African children with cerebral malaria and seizures caused Plasmodium falciparum are at greater risk of poor outcomes including death and neurological sequelae. The agonal events are severe hypoventilation and respiratory arrest often triggered by seizures. We hypothesised that prophylactic anti-seizure medication (ASM) could avert 'spikes' of intracranial pressure during or following seizures and that adequate ventilation could be supported by biphasic Cuirass Ventilation (BCV) which requires no intubation. Methods: A Phase I trial conducted in Kilifi, Kenya designed to provide data on safety, feasibility and preliminary data on seizure control using prophylactic ASM (levetiracetam) and BCV as non-invasive ventilatory support in children with cerebral malaria. Children aged 3 months to 12-years hospitalised with P falciparum malaria (positive rapid diagnostic test or a malaria slide), a Blantyre Coma Score ≤2 and a history of acute seizures in this illness are eligible for the trial. In a phased evaluation we will study i) BCV alone for respiratory support (n=10); ii) prophylactic LVT: 40mg/kg loading dose then 30mg/kg every 12 hours given via nasogastric tube for 72 hours (or until fully conscious) plus BCV support (n=10) and; iii) prophylactic LVT: 60mg/kg loading dose then 45mg/kg every 12 hours given via nasogastric tube for 72 hours (or until fully conscious) plus BCV support (n=10). Primary outcome measure: cumulative time with a clinically detected seizures or number of observed seizures over 36 hours. Secondary outcomes will be assessed by feasibility or ability to implement BCV, and recovery from coma within 36 hours. Safety endpoints include: aspiration during admission; death at 28 days and 180 days; and de-novo neurological impairments at 180 days. Conclusions: This is a Phase I trial largely designed to test the feasibility, tolerability and safety of using non-invasive ventilatory support and LVT prophylaxis in cerebral malaria. Registration: ISRCTN76942974 (5.02.2019); PACTR202112749708968 (20.12.2021).

Unfortunately, children with cerebral malaria continue to have very poor outcomes including severe hypoventilation and respiratory arrest (i.e. breathing is too slow or stops) during hospitalization which is often triggered by seizures. We will explore the potential benefits of a special type of ventilation that applies suction or negative pressure to the chest (meaning keeping children breathing by pushing air in and out of their lungs) in combination with anticonvulsants given before children have had any fits We will use a device called biphasic Cuirass Ventilation (BCV) that can be used by non-specialists to help children breath. BCV applies both negative and positive pressure to the chest, covering both inspiration (breathing in) and expiration (breathing out) phases of breathing, which is more appropriate for periods of when the breathing is too slow or stops for a period of time. We will also use an anticonvulsant drug, called levetiracetam to prevent seizures. It has been safely used in Malawian children and shown to improve outcomes. This will be given directly into the stomach via a nasogastric tube (tubes down the nose into the stomach) The study will be carried out at Kilifi County Hospital, Kenya and plans to enrol 30 children aged 3 months to 12 years with cerebral malaria and a positive malaria test The first ten children with have the BCV device only to assist respiration until they recover from their coma. The next twenty children in the trial will have the BCV device in addition with anticonvulsants given before children have had any fits as a preventive strategy to stop fits. All children will have regular monitoring during the period of coma/ventilation and will be followed up on days 28 and 180. The study aims to generate feasibility and safety data to support future trials.

Dissemination and persistence of antimicrobial resistance (AMR) along the wastewater-river continuum.

Antimicrobial resistance (AMR) is a global health hazard. Although clinical and agricultural environments are well-established contributors to the evolution and dissemination of AMR, research on wastewater treatment works (WwTWs) has highlighted their potential role as disseminators of AMR in freshwater environments. Using metagenomic sequencing and analysis, we investigated the changes in resistomes and associated mobile genetic elements within untreated wastewater influents and treated effluents of five WwTWs, and sediments collected from corresponding river environments in Oxfordshire, UK, across three seasonal periods within a year. Our analysis demonstrated a high diversity and abundance of antimicrobial resistance genes (ARGs) in untreated wastewater influents, reflecting the varied anthropogenic and environmental origins of wastewater. WwTWs effectively reduced AMR in the final effluent, with an average 87 % reduction in normalised ARG abundance and an average 63 % reduction in richness. However, wastewater effluents significantly impacted the antimicrobial resistome of the receiving rivers, with an average 543 % increase in ARG abundance and a 164 % increase in richness from upstream sediments to downstream sediments. The normalised abundance of the human gut-associated bacteriophage crAssphage was highly associated with both ARG abundance and richness. We observed seasonal variation in the resistome of raw influent which was not found in the effluent-receiving sediments. We illustrate the potential of WwTWs as focal points for disseminating ARGs and resistance-selecting chemicals, contributing to the elevation of environmental AMR. Our study emphasises the need for a comprehensive understanding of the anthropogenic impacts on AMR evolution and dissemination in wastewater and river environments, informing efforts to mitigate this growing public health crisis.

Determining sample size in a personalized randomized controlled (PRACTical) trial.

In clinical settings with no commonly accepted standard-of-care, multiple treatment regimens are potentially useful, but some treatments may not be appropriate for some patients. A personalized randomized controlled trial (PRACTical) design has been proposed for this setting. For a network of treatments, each patient is randomized only among treatments which are appropriate for them. The aim is to produce treatment rankings that can inform clinical decisions about treatment choices for individual patients. Here we propose methods for determining sample size in a PRACTical design, since standard power-based methods are not applicable. We derive a sample size by evaluating information gained from trials of varying sizes. For a binary outcome, we quantify how many adverse outcomes would be prevented by choosing the top-ranked treatment for each patient based on trial results rather than choosing a random treatment from the appropriate personalized randomization list. In simulations, we evaluate three performance measures: mean reduction in adverse outcomes using sample information, proportion of simulated patients for whom the top-ranked treatment performed as well or almost as well as the best appropriate treatment, and proportion of simulated trials in which the top-ranked treatment performed better than a randomly chosen treatment. We apply the methods to a trial evaluating eight different combination antibiotic regimens for neonatal sepsis (NeoSep1), in which a PRACTical design addresses varying patterns of antibiotic choice based on disease characteristics and resistance. Our proposed approach produces results that are more relevant to complex decision making by clinicians and policy makers.

Improving the representativeness of UK's national COVID-19 Infection Survey through spatio-temporal regression and post-stratification.

Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we used spatio-temporal regression and post-stratification models to UK's national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21 percentage points), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.

Biomarkers of mortality in adults and adolescents with advanced HIV in sub-Saharan Africa.

One-third of people with HIV in sub-Saharan Africa start antiretroviral therapy (ART) with advanced disease. We investigated associations between immune biomarkers and mortality in participants with advanced HIV randomised to cotrimoxazole or enhanced antimicrobial prophylaxis in the Reduction of Early Mortality in HIV-Infected Adults and Children Starting Antiretroviral Therapy (REALITY) trial (ISRCTN43622374). Biomarkers were assayed using ELISA and Luminex. Associations between baseline values and all-cause 24-week mortality were analysed using Cox models, and for cause-specific mortality used Fine & Gray models, including prophylaxis randomisation, viral load, CD4, WHO stage, age, BMI, and site as covariates; and weighted according to inverse probability of selection into the substudy. Higher baseline CRP, IFN-γ, IL-6 and IP-10 were associated with higher all-cause mortality; and higher IL-23, IL-2 and RANTES with lower all-cause mortality. Associations varied by cause of death: tuberculosis-associated mortality was most strongly associated with higher CRP and sST2, and cryptococcosis-associated mortality with higher IL-4 and lower IL-8. Changes in I-FABP (p = 0.002), faecal alpha-1 antitrypsin (p = 0.01) and faecal myeloperoxidase (p = 0.005) between baseline and 4 weeks post-ART were greater in those receiving enhanced versus cotrimoxazole prophylaxis. Our findings highlight how the immune milieu shapes outcomes following ART initiation, and how adjunctive antimicrobials can modulate the gut environment in advanced HIV.

Overcoming challenges in the economic evaluation of interventions to optimise antibiotic use.

Bacteria are becoming increasingly resistant to antibiotics, reducing our ability to treat infections and threatening to undermine modern health care. Optimising antibiotic use is a key element in tackling the problem. Traditional economic evaluation methods do not capture many of the benefits from improved antibiotic use and the potential impact on resistance. Not capturing these benefits is a major obstacle to optimising antibiotic use, as it fails to incentivise the development and use of interventions to optimise the use of antibiotics and preserve their effectiveness (stewardship interventions). Estimates of the benefits of improving antibiotic use involve considerable uncertainty as they depend on the evolution of resistance and associated health outcomes and costs. Here we discuss how economic evaluation methods might be adapted, in the face of such uncertainties. We propose a threshold-based approach that estimates the minimum resistance-related costs that would need to be averted by an intervention to make it cost-effective. If it is probable that without the intervention costs will exceed the threshold then the intervention should be deemed cost-effective.

Distinct patterns of vital sign and inflammatory marker responses in adults with suspected bloodstream infection.

OBJECTIVES: To identify patterns in inflammatory marker and vital sign responses in adult with suspected bloodstream infection (BSI) and define expected trends in normal recovery. METHODS: We included patients ≥16 y from Oxford University Hospitals with a blood culture taken between 1-January-2016 and 28-June-2021. We used linear and latent class mixed models to estimate trajectories in C-reactive protein (CRP), white blood count, heart rate, respiratory rate and temperature and identify CRP response subgroups. Centile charts for expected CRP responses were constructed via the lambda-mu-sigma method. RESULTS: In 88,348 suspected BSI episodes; 6908 (7.8%) were culture-positive with a probable pathogen, 4309 (4.9%) contained potential contaminants, and 77,131(87.3%) were culture-negative. CRP levels generally peaked 1-2 days after blood culture collection, with varying responses for different pathogens and infection sources (p < 0.0001). We identified five CRP trajectory subgroups: peak on day 1 (36,091; 46.3%) or 2 (4529; 5.8%), slow recovery (10,666; 13.7%), peak on day 6 (743; 1.0%), and low response (25,928; 33.3%). Centile reference charts tracking normal responses were constructed from those peaking on day 1/2. CONCLUSIONS: CRP and other infection response markers rise and recover differently depending on clinical syndrome and pathogen involved. However, centile reference charts, that account for these differences, can be used to track if patients are recovering line as expected and to help personalise infection.

No evidence of difference in mortality with amoxicillin versus co-amoxiclav for hospital treatment of community-acquired pneumonia.

OBJECTIVES: Current guidelines recommend broad-spectrum antibiotics for high-severity community-acquired pneumonia (CAP), potentially contributing to antimicrobial resistance (AMR). We aim to compare outcomes in CAP patients treated with amoxicillin (narrow-spectrum) versus co-amoxiclav (broad-spectrum), to understand if narrow-spectrum antibiotics could be used more widely. METHODS: We analysed electronic health records from adults (≥16 y) admitted to hospital with a primary diagnosis of pneumonia between 01-January-2016 and 30-September-2023 in Oxfordshire, United Kingdom. Patients receiving baseline ([-12 h,+24 h] from admission) amoxicillin or co-amoxiclav were included. The association between 30-day all-cause mortality and baseline antibiotic was examined using propensity score (PS) matching and inverse probability treatment weighting (IPTW) to address confounding by baseline characteristics and disease severity. Subgroup analyses by disease severity and sensitivity analyses with missing covariates imputed were also conducted. RESULTS: Among 16,072 admissions with a primary diagnosis of pneumonia, 9685 received either baseline amoxicillin or co-amoxiclav. There was no evidence of a difference in 30-day mortality between patients receiving initial co-amoxiclav vs. amoxicillin (PS matching: marginal odds ratio 0.97 [0.76-1.27], p = 0.61; IPTW: 1.02 [0.78-1.33], p = 0.87). Results remained similar across stratified analyses of mild, moderate, and severe pneumonia. Results were also similar with missing data imputed. There was also no evidence of an association between 30-day mortality and use of additional macrolides or additional doxycycline. CONCLUSIONS: There was no evidence of co-amoxiclav being advantageous over amoxicillin for treatment of CAP in 30-day mortality at a population-level, regardless of disease severity. Wider use of narrow-spectrum empirical treatment of moderate/severe CAP should be considered to curb potential for AMR.

Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine-learning approaches.

Background: Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis; however, antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA, encoding an enzyme that converts pyrazinamide into its active form. Methods: We curated a dataset of 664 non-redundant, missense amino acid mutations in PncA with associated high-confidence phenotypes from published studies and then trained three different machine-learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features. Results: The best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4027 samples harbouring 367 unique missense mutations in pncA derived from 24 231 clinical isolates. Conclusions: This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs.

Employment outcomes of people with Long Covid symptoms: community-based cohort study.

BACKGROUND: Evidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and employment outcomes. METHODS: This was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16-64 years and not in education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks. RESULTS: Of 206 299 participants (mean age 45 years, 54% female, 92% white), 15% were ever labour market inactive and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks [adjusted odds ratio (aOR): 1.45; 95% CI: 1.17-1.81] or 40 to <52 weeks (aOR: 1.34; 95% CI: 1.05-1.72) post-infection. Combining with official statistics on Long Covid prevalence, and assuming a correct statistical model, our estimates translate to 27 000 (95% CI: 6000-47 000) working-age adults in the UK being inactive because of Long Covid in July 2022. CONCLUSIONS: Long Covid is likely to have contributed to reduced participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.

The plasmidome associated with Gram-negative bloodstream infections: A large-scale observational study using complete plasmid assemblies.

Plasmids carry genes conferring antimicrobial resistance and other clinically important traits, and contribute to the rapid dissemination of such genes. Previous studies using complete plasmid assemblies, which are essential for reliable inference, have been small and/or limited to plasmids carrying antimicrobial resistance genes (ARGs). In this study, we sequenced 1,880 complete plasmids from 738 isolates from bloodstream infections in Oxfordshire, UK. The bacteria had been originally isolated in 2009 (194 isolates) and 2018 (368 isolates), plus a stratified selection from intervening years (176 isolates). We demonstrate that plasmids are largely, but not entirely, constrained to a single host species, although there is substantial overlap between species of plasmid gene-repertoire. Most ARGs are carried by a relatively small number of plasmid groups with biological features that are predictable. Plasmids carrying ARGs (including those encoding carbapenemases) share a putative 'backbone' of core genes with those carrying no such genes. These findings suggest that future surveillance should, in addition to tracking plasmids currently associated with clinically important genes, focus on identifying and monitoring the dissemination of high-risk plasmid groups with the potential to rapidly acquire and disseminate these genes.

Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population.

SARS-CoV-2 reinfections increased substantially after Omicron variants emerged. Large-scale community-based comparisons across multiple Omicron waves of reinfection characteristics, risk factors, and protection afforded by previous infection and vaccination, are limited. Here we studied ~45,000 reinfections from the UK's national COVID-19 Infection Survey and quantified the risk of reinfection in multiple waves, including those driven by BA.1, BA.2, BA.4/5, and BQ.1/CH.1.1/XBB.1.5 variants. Reinfections were associated with lower viral load and lower percentages of self-reporting symptoms compared with first infections. Across multiple Omicron waves, estimated protection against reinfection was significantly higher in those previously infected with more recent than earlier variants, even at the same time from previous infection. Estimated protection against Omicron reinfections decreased over time from the most recent infection if this was the previous or penultimate variant (generally within the preceding year). Those 14-180 days after receiving their most recent vaccination had a lower risk of reinfection than those >180 days from their most recent vaccination. Reinfection risk was independently higher in those aged 30-45 years, and with either low or high viral load in their most recent previous infection. Overall, the risk of Omicron reinfection is high, but with lower severity than first infections; both viral evolution and waning immunity are independently associated with reinfection.

Epidemiology and microbiology of recurrent UTI in women in the community in Oxfordshire, UK.

Background: Recurrent urinary tract infection (rUTI) contributes to significant morbidity and antibiotic usage. Objectives: To characterize the age of women experiencing rUTI, the microbiology of rUTIs, and the risk of further rUTIs in Oxfordshire, UK. Patients and methods: We retrospectively analysed de-identified linked microbiology and hospital admissions data (Infections in Oxfordshire Research Database), between 2008 and 2019, including positive urine cultures from women aged ≥16 years in community settings. We defined rUTI as ≥2 positive urine cultures within 6 months or ≥3 within 12 months. Results: Of 201 927 women with urine culture performed, 84 809 (42%) had ≥1 positive culture, and 15 617 (18%) of these experienced ≥1 rUTI over a median (IQR) follow-up of 6 (3-9) years. Women with rUTI were 17.0 (95% CI: 16.3-17.7) years older on average. rUTI was commonest (6204; 40%) in those aged 70-89 years. Post-rUTI, the risk of further UTI within 6 months was 29.4% (95% CI: 28.7-30.2). Escherichia coli was detected in 65% of positive cultures. Among rUTIs where the index UTI was E. coli associated, the second UTI was also E. coli associated in 81% of cases. Conclusions: rUTIs represent a substantial healthcare burden, particularly in women >60 years. One-third of women experiencing rUTI have a further microbiologically confirmed UTI within 6 months.

When should factorial designs be used for late-phase randomised controlled trials?

BACKGROUND: A 2×2 factorial design evaluates two interventions (A versus control and B versus control) by randomising to control, A-only, B-only or both A and B together. Extended factorial designs are also possible (e.g. 3×3 or 2×2×2). Factorial designs often require fewer resources and participants than alternative randomised controlled trials, but they are not widely used. We identified several issues that investigators considering this design need to address, before they use it in a late-phase setting. METHODS: We surveyed journal articles published in 2000-2022 relating to designing factorial randomised controlled trials. We identified issues to consider based on these and our personal experiences. RESULTS: We identified clinical, practical, statistical and external issues that make factorial randomised controlled trials more desirable. Clinical issues are (1) interventions can be easily co-administered; (2) risk of safety issues from co-administration above individual risks of the separate interventions is low; (3) safety or efficacy data are wanted on the combination intervention; (4) potential for interaction (e.g. effect of A differing when B administered) is low; (5) it is important to compare interventions with other interventions balanced, rather than allowing randomised interventions to affect the choice of other interventions; (6) eligibility criteria for different interventions are similar. Practical issues are (7) recruitment is not harmed by testing many interventions; (8) each intervention and associated toxicities is unlikely to reduce either adherence to the other intervention or overall follow-up; (9) blinding is easy to implement or not required. Statistical issues are (10) a suitable scale of analysis can be identified; (11) adjustment for multiplicity is not required; (12) early stopping for efficacy or lack of benefit can be done effectively. External issues are (13) adequate funding is available and (14) the trial is not intended for licensing purposes. An overarching issue (15) is that factorial design should give a lower sample size requirement than alternative designs. Across designs with varying non-adherence, retention, intervention effects and interaction effects, 2×2 factorial designs require lower sample size than a three-arm alternative when one intervention effect is reduced by no more than 24%-48% in the presence of the other intervention compared with in the absence of the other intervention. CONCLUSIONS: Factorial designs are not widely used and should be considered more often using our issues to consider. Low potential for at most small to modest interaction is key, for example, where the interventions have different mechanisms of action or target different aspects of the disease being studied.

Development and validation of the Baseline Recurrence Risk in Cellulitis (BRRISC) score.

OBJECTIVES: Cellulitis is often treated with antibiotics for longer than recommended by guidelines. Prolonged therapy may reduce recurrence in certain patients, but it is not known which patients are at greatest risk. Our objective was to develop and temporally validate a risk prediction score to identify patients attending hospital with cellulitis at highest risk of recurrence. METHODS: We included UK adult patients with cellulitis attending hospital in an electronic health records (EHR) study to identify demographic, comorbid, physiological, and laboratory factors predicting recurrence (before death) within 90 days, using multivariable logistic regression with backwards elimination in complete cases. A points-based risk score integerised model coefficients for selected predictors. Performance was assessed using the C-index in development and temporal validation samples. RESULTS: The final model included 4938 patients treated for median 8 days (IQR 6-11); 8.8% (n = 436) experienced hospitalisation-associated recurrence. A risk score using eight variables (age, heart rate, urea, platelets, albumin, previous cellulitis, venous insufficiency, and liver disease) ranged from 0-15, with C-index = 0.65 (95%CI: 0.63-0.68). Categorising as low (score 0-1), medium (2-5) and high (6-15) risk, recurrence increased fourfold; 3.2% (95%CI: 2.3-4.4%), 9.7% (8.7-10.8%), and 16.6% (13.3-20.4%). Performance was maintained in the validation sample (C-index = 0.63 (95%CI: 0.58-0.67)). Among patients at high risk, four distinct clinical phenotypes were identified using hierarchical clustering 1) young, acutely unwell with liver disease; 2) comorbid with previous cellulitis and venous insufficiency; 3) chronic renal disease with severe renal impairment; and 4) acute severe illness, with substantial inflammatory responses. CONCLUSIONS: Risk of cellulitis recurrence varies markedly according to individual patient factors captured in the Baseline Recurrence Risk in Cellulitis (BRRISC) score. Further work is needed to optimise the score, considering baseline and treatment response variables not captured in EHR data, and establish the utility of risk-based approaches to guide optimal antibiotic duration.

Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on Escherichia coli.

Several bioinformatics genotyping algorithms are now commonly used to characterize antimicrobial resistance (AMR) gene profiles in whole-genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance and SRST2, run with the ResFinder database) and their outputs compared. For simulation tests where 3079 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for 3076 (99.9 %) simulations, ABRicate for 3054 (99.2 %), ARIBA for 2783 (90.4 %) and SRST2 for 2108 (68.5 %). For simulation tests where two closely related gene variants were inserted into random sequence constructs, KmerResistance identified the correct alleles in 35 338/46 318 (76.3 %) simulations, ABRicate identified them in 11 842/46 318 (25.6 %) simulations, ARIBA identified them in 1679/46 318 (3.6 %) simulations and SRST2 identified them in 2000/46 318 (4.3 %) simulations. In real data, across all methods, 1392/1818 (76 %) isolates had discrepant allele calls for at least 1 gene. In addition to highlighting areas for improvement in challenging scenarios, (e.g. identification of AMR genes at <10× coverage, identifying multiple closely related AMR genes present in the same sample), our evaluations identified some more systematic errors that could be readily soluble, such as repeated misclassification (i.e. naming) of genes as shorter variants of the same gene present within the reference resistance gene database. Such naming errors accounted for at least 2530/4321 (59 %) of the discrepancies seen in real data. Moreover, many of the remaining discrepancies were likely 'artefactual', with reporting of cut-off differences accounting for at least 1430/4321 (33 %) discrepants. Whilst we found that comparing outputs generated by running multiple algorithms on the same dataset could identify and resolve these algorithmic artefacts, the results of our evaluations emphasize the need for developing new and more robust genotyping algorithms to further improve accuracy and performance.

Risk of New-Onset Long COVID Following Reinfection With Severe Acute Respiratory Syndrome Coronavirus 2: A Community-Based Cohort Study.

Background: Little is known about the risk of long COVID following reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We estimated the likelihood of new-onset, self-reported long COVID after a second SARS-CoV-2 infection, compared to a first infection. Methods: We included UK COVID-19 Infection Survey participants who tested positive for SARS-CoV-2 between 1 November 2021 and 8 October 2022. The primary outcome was self-reported long COVID 12-20 weeks after each infection. Separate analyses were performed for those <16 years and ≥16 years. We estimated adjusted odds ratios (aORs) for new-onset long COVID using logistic regression, comparing second to first infections, controlling for sociodemographic characteristics and calendar date of infection, plus vaccination status in participants ≥16 years of age. Results: Overall, long COVID was reported by those ≥16 years after 4.0% and 2.4% of first and second infections, respectively; the corresponding estimates among those aged <16 years were 1.0% and 0.6%. The aOR for long COVID after second compared to first infections was 0.72 (95% confidence interval [CI], .63-.81) for those ≥16 years and 0.93 (95% CI, .57-1.53) for those <16 years. Conclusions: The risk of new-onset long COVID after a second SARS-CoV-2 infection is lower than that after a first infection for persons aged ≥16 years, though there is no evidence of a difference in risk for those <16 years. However, there remains some risk of new-onset long COVID after a second infection, with around 1 in 40 of those aged ≥16 years and 1 in 165 of those <16 years reporting long COVID after a second infection.

Impact of the COVID-19 pandemic on antimicrobial stewardship support for general practices in England: a qualitative interview study.

BACKGROUND: In England, clinical commissioning group (CCG; now replaced by Integrated Care Systems [ICSs]) and primary care network (PCN) professionals support primary care prescribers to optimise antimicrobial stewardship (AMS). AIM: To explore views and experiences of CCG and PCN staff in supporting AMS, and the impact of COVID-19 on this support. DESIGN & SETTING: Qualitative interview study in primary care in England. METHOD: Semi-structured interviews with staff from CCG and PCNs responsible for AMS were conducted at two timepoints via telephone. These were audio-recorded, transcribed, and analysed thematically. RESULTS: Twenty-seven interviews were conducted with 14 participants (nine CCG, five PCN) in December 2020-January 2021 and February-May 2021. The study found that AMS support was (1) deprioritised in order to keep general practice operational and deliver COVID-19 vaccines; (2) disrupted as social distancing made it harder to build relationships, conduct routine AMS activities, and challenge prescribing decisions; and (3) adapted, with opportunities identified for greater use of technology and changing patient and public perceptions of viruses and self-care. It was also found that resources to support AMS were valued if they were both novel, to counter AMS 'fatigue', and sufficiently familiar to fit with existing and/or future AMS. CONCLUSION: AMS needs to be reprioritised in general practice in the post-pandemic era and within the new ICSs in England. This should include interventions and strategies that combine novel elements with already familiar strategies to refresh prescribers' motivation and opportunities for AMS. Behaviour change interventions should be aimed at improving the culture and processes for how PCN pharmacists voice concerns about AMS to prescribers in general practice and take advantage of the changed patient and public perceptions of viruses and self-care.