Imperial College London

DrTimothy MilesRawson

Faculty of MedicineDepartment of Infectious Disease

Honorary Clinical Lecturer
 
 
 
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timothy.rawson07 Website

 
 
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Commonwealth BuildingHammersmith Campus

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Summary

 

Publications

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122 results found

Kherabi Y, Thy M, Bouzid D, Antcliffe D, Rawson TM, Peiffer-Smadja Net al., 2024, Machine learning to predict antimicrobial resistance: future applications in clinical practice?, Infectious Diseases Now

Journal article

Riezk A, Wilson RC, Cass AEG, Holmes AH, Rawson TMet al., 2024, A low-volume LC/MS method for highly sensitive monitoring of phenoxymethylpenicillin, benzylpenicillin, and probenecid in human serum, Analytical Methods: advancing methods and applications, Vol: 16, Pages: 558-565, ISSN: 1759-9660

Background: The optimization of antimicrobial dosing plays a crucial role in improving the likelihood of achieving therapeutic success while reducing the risks associated with toxicity and antimicrobial resistance. Probenecid has shown significant potential in enhancing the serum exposure of phenoxymethylpenicillin, thereby allowing for lower doses of phenoxymethylpenicillin to achieve similar pharmacokinetic/pharmacodynamic (PK/PD) targets. We developed a triple quadrupole liquid chromatography mass spectrometry (TQ LC/MS) analysis of, phenoxymethylpenicillin, benzylpenicillin and probenecid using benzylpenicillin-d7 and probenecid-d14 as IS in single low-volumes of human serum, with improved limit of quantification to support therapeutic drug monitoring. Methods: Sample clean-up was performed by protein precipitation using acetonitrile. Reverse phase chromatography was performed using TQ LC/MS. The mobile phase consisted of 55% methanol in water + 0.1% formic acid, with a flow rate of 0.4 mL min-1. Antibiotic stability was assessed at different temperatures. Results: Chromatographic separation was achieved within 2 minutes, allowing simultaneous measurement of phenoxymethylpenicillin, benzylpenicillin and probenecid in a single 15 μL blood sample. Validation indicated linearity over the range 0.0015-10 mg L-1, with accuracy of 96-102% and a LLOQ of 0.01 mg L-1. All drugs demonstrated good stability under different storage conditions. Conclusion: The developed method is simple, rapid, accurate and clinically applicable for the quantification of phenoxymethylpenicillin, benzylpenicillin and probenecid in tandem.

Journal article

Bolton W, Wilson R, Gilchrist M, Georgiou P, Holmes A, Rawson Tet al., 2024, Personalising intravenous to oral antibiotic switch decision making through fair interpretable machine learning, Nature Communications, Vol: 15, ISSN: 2041-1723

Antimicrobial resistance (AMR) and healthcare associated infections pose a significant threat globally. One key prevention strategy is to follow antimicrobial stewardship practices, in particular, to maximise targeted oral therapy and reduce the use of indwelling vascular devices for intravenous (IV) administration. Appreciating when an individual patient can switch from IV to oral antibiotic treatment is often non-trivial and not standardised. To tackle this problem we created a machine learning model to predict when a patient could switch based on routinely collected clinical parameters. 10,362 unique intensive care unit stays were extracted and two informative feature sets identified. Our best model achieved a mean AUROC of 0.80 (SD 0.01) on the hold-out set while not being biased to individuals protected characteristics. Interpretability methodologies were employed to create clinically useful visual explanations. In summary, our model provides individualised, fair, and interpretable predictions for when a patient could switch from IV-to-oral antibiotic treatment. Prospectively evaluation of safety and efficacy is needed before such technology can be applied clinically.

Journal article

Satta G, Rawson TM, Moore LSP, 2023, Coronavirus disease 2019 (COVID-19) impact on central-line-associated bloodstream infections (CLABSI): a systematic review., Infect Prev Pract, Vol: 5

INTRODUCTION: Central line-associated bloodstream infections (CLABSI) are an important clinical and public health issue, impacted by the purported increase in healthcare-associated infections (including CLABSI) during the COVID-19 pandemic. This review evaluates the impact of COVID-19 on CLABSI at a global level, to determine risk factors, effective preventive measures and microbiological epidemiology. METHODS: A systematic literature review was performed using a PECO framework, with COVID-19 infection as the exposure measure and CLABSI rates as the main outcome of interest, pre- and during the pandemic. RESULTS: Overall, most studies (17 of N=21) found a significant increase in CLABSI incidence/rates during the pandemic. Four studies showed a reduction (N=1) or no increase (N=3). High workload, redeployment, and 'overwhelmed' healthcare staff were recurrent risk-factor themes, likely to have negatively influenced basic infection control practices, including compliance with hand hygiene and line care bundles. Microbiological epidemiology was also impacted, with an increase in enterococcal infections and other pathogens. CONCLUSION: The COVID-19 pandemic significantly impacted CLABSI incidence/rates. Observations from the different studies highlight significant gaps in healthcare associated infections (HCAI) knowledge and practice during the pandemic, and the importance of identifying preventive measures effective in reducing CLABSI, essential to health system resilience for future pandemics. Central to this are changes to CLABSI surveillance, as reporting is not mandatory in many healthcare systems. An audit tool combined with regular assessments of the compliance with infection control measures and line care bundles also remains an essential step in the prevention of CLABSI.

Journal article

Moore L, Villegas MV, Wenzler E, Rawson T, Oladele R, Doi Y, Apisarnthanarak Aet al., 2023, Rapid diagnostic test value and implementation in antimicrobial stewardship across low-to-middle and high-income countries: a mixed-methods review, Infectious Diseases and Therapy, Vol: 12, Pages: 1445-1463, ISSN: 2193-8229

Despite technological advancements in infectious disease rapid diagnostic tests (RDTs) and use to direct therapy at the per-patient level, RDT utilisation in antimicrobial stewardship programmes (ASPs) is variable across low-to-middle income and high-income countries. Key insights from a panel of seven infectious disease experts from Colombia, Japan, Nigeria, Thailand, the UK, and the USA, combined with evidence from a literature review, were used to assess the value of RDTs in ASPs. From this, a value framework is proposed which aims to define the benefits of RDT use in ASPs, separate from per-patient benefits. Expert insights highlight that, to realise the value of RDTs within ASPs, effective implementation is key; actionable advice for choosing an RDT is proposed. Experts advocate the inclusion of RDTs in the World Health Organization Model List of essential in vitro diagnostics and in iterative development of national action plans.

Journal article

Rawson TM, Moore LSP, 2023, Understanding how diagnostics influence antimicrobial decision-making is key to successful clinical trial design, CLINICAL MICROBIOLOGY AND INFECTION, Vol: 29, Pages: 666-669, ISSN: 1198-743X

Journal article

Rawson TM, Antcliffe D, Wilson R, Abdolrasouli A, Moore Let al., 2023, Management of bacterial and fungal infections in the ICU: diagnosis, treatment, and prevention recommendations, Infection and Drug Resistance, Vol: 16, Pages: 2709-2726, ISSN: 1178-6973

Bacterial and fungal infections are common issues for patients in the intensive care unit (ICU). Large, multinational point prevalence surveys have identified that up to 50% of ICU patients have a diagnosis of bacterial or fungal infection at any one time. Infection in the ICU is associated with its own challenges. Causative organisms often harbour intrinsic and acquired mechanisms of drug-resistance, making empiric and targeted antimicrobial selection challenging. Infection in the ICU is associated with worse clinical outcomes for patients. We review the epidemiology of bacterial and fungal infection in the ICU. We discuss risk factors for acquisition, approaches to diagnosis and management, and common strategies for the prevention of infection.

Journal article

Vasikasin V, Rawson TM, Holmes AH, Otter Jet al., 2023, Can precision antibiotic prescribing help prevent the spread of carbapenem-resistant organisms in the hospital setting?, JAC-Antimicrobial Resistance, Vol: 5, Pages: 1-13, ISSN: 2632-1823

The emergence of carbapenem-resistant organisms (CROs) is a significant global threat. Reduction of carbapenem consumption can decrease CROs. In the global endemic era of ESBL-producing bacteria, carbapenems are considered the treatment of choice, leading to challenge in limiting carbapenem use. This review describes the role of precision prescribing for prevention of CROs. This involves improving antibiotic selection, dosing and shortening duration. The effect of different antibiotics, dosing and duration on CRO development are explored. Available options for precision prescribing, gaps in the scientific evidence, and areas for future research are also presented.

Journal article

Riezk A, Vasikasin V, Wilson RCC, Rawson TMM, McLeod JGG, Dhillon R, Duckers J, Cass AEG, Holmes AHHet al., 2023, Triple quadrupole LC/MS method for the simultaneous quantitative measurement of cefiderocol and meropenem in serum, Analytical Methods: advancing methods and applications, Vol: 15, Pages: 746-751, ISSN: 1759-9660

Background: therapeutic drug monitoring is a crucial aspect of the management of hospitalized patients. The correct dosage of antibiotics is imperative to ensure their adequate exposure specially in critically ill patients. The aim of this study is to establish and validate a robust and fast liquid chromatography-tandem mass spectrometry (LC/MS) method for the simultaneous quantification of two important antibiotics in critically ill patients, cefiderocol and meropenem in human plasma. Methods: sample clean-up was performed by protein precipitation using acetonitrile. Reverse phase chromatography was performed using triple quadrupole LC/MS. The mobile phase was consisted of 55% methanol in water +0.1% formic acid, with flow rate of 0.4 ml min−1. Antibiotics stability was assessed at different temperatures. Serum protein binding was assessed using ultrafiltration devices. Results: chromatographic separation was achieved within 1.5 minutes for all analytes. Validation has demonstrated the method to be linear over the range 0.0025–50 mg L−1 for cefiderocol and 0.00028–50 mg L−1 for meropenem, with accuracy of 94–101% and highly sensitive, with LLOQ ≈ 0.02 mg L−1 and 0.003 mg L−1 for cefiderocol and meropenem, respectively. Both cefiderocol and meropenem showed a good stability at room temperature over 6 h, and at (4 °C) over 24 h. Cefiderocol and meropenem demonstrated a protein binding of 49–60% and 98%, respectively in human plasma. Conclusion: the developed method is simple, rapid, accurate and clinically applicable for the quantification of cefiderocol and meropenem.

Journal article

Riezk A, Wilson RC, Rawson TM, Vasikasin V, Arkel P, Ferris TJ, Haigh LD, Cass AEG, Holmes AHet al., 2023, A rapid, simple, high-performance liquid chromatography method for the clinical measurement of beta-lactam antibiotics in serum and interstitial fluid, Analytical Methods: advancing methods and applications, Vol: 15, Pages: 829-836, ISSN: 1759-9660

Background: enhanced methods of therapeutic drug monitoring are required to support the individualisation of antibiotic dosing based on pharmacokinetics (PK) parameters. PK studies can be hampered by limited total serum volume, especially in neonates, or by sensitivity in the case of critically ill patients. We aimed to develop a liquid chromatography–mass spectrometry (LC/MS) analysis of benzylpenicillin, phenoxymethylpenicillin and amoxicillin in single low volumes of human serum and interstitial fluid (ISF) samples, with an improved limit of detection (LOD) and limit of quantification (LOQ), compared with previously published assays. Methods: sample clean-up was performed by protein precipitation using acetonitrile. Reverse phase chromatography was performed using triple quadrupole LC/MS. The mobile phase consisted of 55% methanol in water + 0.1% formic acid, with a flow rate of 0.4 mL min−1. Antibiotics stability was assessed at different temperatures. Results: chromatographic separation was achieved within 3 minutes for all analytes. Three common penicillins can now be measured in a single low-volume blood and ISF sample (15 μL) for the first time. Validation has demonstrated the method to be linear over the range 0.0015–10 mg L−1, with an accuracy of 93–104% and high sensitivity, with LOD ≈ 0.003 mg L−1 and LOQ ≈ 0.01 mg L−1 for all three analytes, which is critical for use in dose optimisation/individualisation. All evaluated penicillins indicated good stability at room temperature over 4 h, at (4 °C) over 24 h and at −80 °C for 6 months. Conclusion: the developed method is simple, rapid, accurate and clinically applicable for the quantification of three penicillin classes.

Journal article

Mistry R, Rawson T, Troise O, Mughal N, Moore L, Hughes Set al., 2022, Haematological and hepatic adverse effects of ceftriaxone in ambulatory care: a dual-centre retrospective observational analysis of standard vs high dose, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334

BackgroundEuropean Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoint criteria for methicillin-susceptible Staphylococcus aureus (MSSA) treatment with ceftriaxone are based upon high dose (4g/day) rather than standard dose (2g/day) posology. This is particularly relevant for invasive infections, and for patients managed via Outpatient Parenteral Antimicrobial Therapy (OPAT), but may result in increased drug toxicity. We quantified the incidence of neutropenia, thrombocytopenia and raised liver enzymes between standard and high dose ceftriaxone in adult patients. MethodAdult outpatients prescribed ≥ 7 days of ceftriaxone therapy were identified, and clinical, pharmacological, and laboratory parameters extracted from electronic health records between May 2021 and December 2021. Incidence and median time to haematological and hepto-toxicity were analysed. Univariate odds ratios were calculated for neutrophil count and ALT levels with 95% confidence level and Chi squared/Fisher’s exact test used to identify statistical significance.ResultsIncidence of neutropenia was comparable between both groups; 8/47 (17%) in the 2g group vs 6/39 (15.4%) in the 4g group (OR 0.89 (95% CI 0.26-2.63), p > 0.999). Median time to neutropenia was 12 and 17 days in the 2g and 4g groups respectively. Thrombocytopenia was observed in 0/47 in the 2g group compared with 3/39 (7.7%) in the 4g group (p 0.089). Median time to thrombocytopenia was 7 days in the 4g group. Elevated liver enzymes did not clearly correlate with ceftriaxone dosing; present in 5/47 (10.6%) and 2/39 (5.1%) for 2g and 4g respectively (OR 0.45 (95% CI 0.87 – 2.36), p 0.448). Treatment cessation due to any adverse effect was similar between both groups 2/47 (4.3%) for 2g and 3/39 (7.7%) for 4g (OR 1.86 (95% CI 0.36 – 10.92), p 0.655).ConclusionsIncreased adverse effects with 4g (over 2g) daily dosing of ceftriaxone was not observed in an OPAT population. However absolute developm

Journal article

Bolton W, Rawson T, Hernandez B, Wilson R, Antcliffe D, Georgiou P, Holmes Aet al., 2022, Machine learning and synthetic outcome estimation for individualised antimicrobial cessation, Frontiers in Digital Health, Vol: 4, Pages: 1-12, ISSN: 2673-253X

The decision on when it is appropriate to stop antimicrobial treatment in an individual patient is complex and under-researched. Ceasing too early can drive treatment failure, while excessive treatment risks adverse events. Under- and over-treatment can promote the development of antimicrobial resistance (AMR). We extracted routinely collected electronic health record data from the MIMIC-IV database for 18,988 patients (22,845 unique stays) who received intravenous antibiotic treatment during an intensive care unit (ICU) admission. A model was developed that utilises a recurrent neural network autoencoder and a synthetic control-based approach to estimate patients’ ICU length of stay (LOS) and mortality outcomes for any given day, under the alternative scenarios of if they were to stop vs. continue antibiotic treatment. Control days where our model should reproduce labels demonstrated minimal difference for both stopping and continuing scenarios indicating estimations are reliable (LOS results of 0.24 and 0.42 days mean delta, 1.93 and 3.76 root mean squared error, respectively). Meanwhile, impact days where we assess the potential effect of the unobserved scenario showed that stopping antibiotic therapy earlier had a statistically significant shorter LOS (mean reduction 2.71 days, p-value <0.01). No impact on mortality was observed. In summary, we have developed a model to reliably estimate patient outcomes under the contrasting scenarios of stopping or continuing antibiotic treatment. Retrospective results are in line with previous clinical studies that demonstrate shorter antibiotic treatment durations are often non-inferior. With additional development into a clinical decision support system, this could be used to support individualised antimicrobial cessation decision-making, reduce the excessive use of antibiotics, and address the problem of AMR.

Journal article

Kherabi Y, Ming D, Rawson TM, Peiffer-Smadja Net al., 2022, Challenges in implementing clinical decision support systems for the management of infectious diseases, Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems, Pages: 151-160, ISBN: 9781668450925

The increased availability of routine healthcare data collected through electronic medical record (EMR) systems provide opportunities for a much greater data-driven approach to healthcare. In infectious diseases, a number of Clinical Decision Support Systems (CDSSs) have shown promising results to improve quality and safety of healthcare management. However, most CDSSs have not been evaluated in real-world clinical settings and are not implemented into clinical practice. The aim of this chapter is to highlight the major challenges in translating CDSS research in infectious diseases into effective tools suitable for use in the clinical setting. Exemplars of real-world implementations and experience of introducing CDSS in infectious diseases are provided, and discussion on measurable outcomes, integration, and framework for clinical implementation proposed.

Book chapter

Bolton WJ, Badea C, Georgiou P, Holmes A, Rawson TMet al., 2022, Developing moral AI to support decision-making about antimicrobial use, NATURE MACHINE INTELLIGENCE, Vol: 4, Pages: 912-915

Journal article

Herrero Vinas P, Wilson R, Armiger R, Roberts J, Holmes A, Georgiou P, Rawson Tet al., 2022, Closed-loop control of continuous piperacillin delivery: an in silico study, Frontiers in Bioengineering and Biotechnology, Vol: 10, ISSN: 2296-4185

Background and objective: Sub-therapeutic dosing of piperacillin-tazobactam in critically-ill patients is associated with poor clinical outcomes and may promote the emergence of drug-resistant infections. In this paper, an in silico investigation of whether closed-loop control can improve pharmacokinetic-pharmacodynamic (PK-PD) target attainment is described.Method: An in silico platform was developed using PK data from 20 critically-ill patients receiving piperacillin-tazobactam where serum and tissue interstitial fluid (ISF) PK were defined. Intra-day variability on renal clearance, ISF sensor error, and infusion constraints were taken into account. Proportional-integral-derivative (PID) control was selected for drug delivery modulation. Dose adjustment was made based on ISF sensor data with a 30-minute sampling period, targeting a serum piperacillin concentration between 32-64 mg/L. A single tuning parameter set was employed across the virtual population. The PID controller was compared to standard therapy, including bolus and continuous infusion of piperacillin-tazobactam.Results: Despite significant inter-subject and simulated intra-day PK variability and sensor error, PID demonstrated a significant improvement in target attainment compared to traditional bolus and continuous infusion approaches. Conclusion: A PID controller driven by ISF drug concentration measurements has the potential to precisely deliver piperacillin-tazobactam in critically-ill patients undergoing treatment for sepsis.

Journal article

Arkell P, Wilson R, Watkins K, Antcliffe DB, Gilchrist M, Wilson M, Rawson TM, Holmes Aet al., 2022, Application of therapeutic drug monitoring to the treatment of bacterial central nervous system infection: a scoping review, Journal of Antimicrobial Chemotherapy, Vol: 77, Pages: 3408-3413, ISSN: 0305-7453

BackgroundBacterial central nervous system (CNS) infection is challenging to treat and carries high risk of recurrence, morbidity, and mortality. Low CNS penetration of antibiotics may contribute to poor clinical outcomes from bacterial CNS infections. The current application of therapeutic drug monitoring (TDM) to management of bacterial CNS infection was reviewed.MethodsStudies were included if they described adults treated for a suspected/confirmed bacterial CNS infection and had antibiotic drug concentration(s) determined that affected individual treatment.ResultsOne-hundred-and-thirty-six citations were retrieved. Seventeen manuscripts were included describing management of 68 patients. TDM for vancomycin (58/68) and the beta-lactams (29/68) was most common. Timing of clinical sampling varied widely between studies and across different antibiotics. Methods for setting individual PK-PD targets, determining parameters and making treatment changes varied widely and were sometimes unclear.DiscussionDespite increasing observational data showing low CNS penetration of various antibiotics, there are few clinical studies describing practical implementation of TDM in management of CNS infection. Lack of consensus around clinically relevant CSF PK-PD targets and protocols for dose-adjustment may contribute. Standardised investigation of TDM as a tool to improve treatment is required, especially as innovative drug concentration-sensing and PK-PD modelling technologies are emerging. Data generated at different centres offering TDM should be open access and aggregated to enrich understanding and optimize application.

Journal article

Bolton W, Badea C, Georgiou P, Holmes A, Rawson Tet al., 2022, Developing Moral AI to Support Antimicrobial Decision Making, Nature Machine Intelligence, ISSN: 2522-5839

Journal article

Wilson R, Arkell P, Riezk A, Wheeler G, Gilchrist M, Hope W, Holmes A, Rawson TMet al., 2022, Addition of probenecid to oral beta-lactam antibiotics: a systematic review and meta-analysis, Journal of Antimicrobial Chemotherapy, Vol: 77, Pages: 2364-2372, ISSN: 0305-7453

Objective: Explore literature comparing the pharmacokinetic and clinical outcomes from addition of probenecid to oral beta-lactams.Data sources: Medline and EMBASE were searched from inception to December 2021.Study eligibility criteria: All English language studies comparing the addition of probenecid (intervention) to an oral beta-lactam (flucloxacillin, penicillin-V, amoxicillin(+/-clavulanate), cephalexin, cefuroxime-axetil) alone (comparator).Risk of bias: Risk of Bias in Non-randomised studies of interventions (ROBINS-I) and Risk of Bias for Randomised studies 2 (ROB-2) tools were used.Methods of data synthesis: Data on antibiotic therapy, infection diagnosis, primary and secondary outcomes relating to pharmacokinetics and clinical outcomes plus adverse events were extracted and reported descriptively. For a subset of studies comparing treatment failure between probenecid and control groups, meta-analysis was performed. Results: Overall, 18/295 (6%) abstracts screened were included. Populations, methodology, and outcome data were heterogenous. Common populations included healthy volunteer (9/18;50%) and gonococcal infection (6/18;33%). Most studies were cross-over trials (11/18;61%) or parallel arm randomised trial (4/18;22%). Where pharmacokinetic analyses were performed, addition of probenecid to oral beta-lactams increased total AUC (7/7;100¬%), peak observed concentration (Cmax,5/8;63%), and serum half-life (t1/2,6/8;75%). Probenecid improved PTA (2/2;100%). Meta-analysis of 3105 (2258 intervention, 847 control) patients treated for gonococcal disease demonstrated a relative risk of treatment failure in the random effects model of 0.33 (95%CI:0.20-0.55; I2=7%), favouring probenecid. Conclusion: Probenecid boosted beta-lactam therapy is associated with improved outcomes in gonococcal disease. Pharmacokinetic data suggest that probenecid boosted oral beta-lactam therapy may have a broader application, but appropriately powered mechanistic and efficacy st

Journal article

Rawson TM, Eigo T, Wilson R, Husson F, Dhillon R, Seddon O, Holmes A, Gilchrist Met al., 2022, Exploring patient acceptance of research within Complex oral and IV Outpatient Parenteral Antimicrobial Therapy (COpAT) networks, JAC-Antimicrobial Resistance, Vol: 4, ISSN: 2632-1823

Journal article

Zhu J, Holmes A, 2022, Changing patterns of bloodstream infections in the community and acute care across two COVID-19 epidemic waves: a retrospective analysis using data linkage, Clinical Infectious Diseases, Vol: 75, Pages: e1082-e1091, ISSN: 1058-4838

BackgroundWe examined the epidemiology of community- and hospital-acquired bloodstream infections (BSIs) in COVID-19 and non-COVID-19 patients across two epidemic waves.MethodsWe analysed blood cultures of patients presenting and admitted to a London hospital group between January 2020 and February 2021. We reported BSI incidence, as well as changes in sampling, case mix, healthcare capacity, and COVID-19 variants.Results34,044 blood cultures were taken. We identified 1,047 BSIs; 653 (62.4%) community-acquired and 394 (37.6%) hospital-acquired. Important changes in patterns were seen. Among community-acquired BSIs, Escherichia coli BSIs remained lower than pre-pandemic level during COVID-19 waves, however peaked following lockdown easing in May 2020, deviating from the historical trend of peaking in August. The hospital-acquired BSI rate was 100.4 per 100,000 patient-days across the pandemic, increasing to 132.3 during the first wave and 190.9 during the second, with significant increase seen in elective inpatients. Patients who developed a hospital-acquired BSI, including those without COVID-19, experienced 20.2 excess days of hospital stay and 26.7% higher mortality, higher than reported in pre-pandemic literature. In intensive care, the BSI rate was 421.0 per 100,000 patient-ICU days during the second wave, compared to 101.3 pre-COVID. The BSI incidence in those infected with the SARS-CoV-2 Alpha variant was similar to that seen with earlier variants.ConclusionsThe pandemic and national responses have impacted the patterns of community- and hospital-acquired BSIs, in COVID-19 and non-COVID-19 patients. Factors driving the observed patterns are complex. Infection surveillance needs to consider key aspects of pandemic response and changes in healthcare access and practice.

Journal article

Rawson TM, Brzeska-Trafny I, Maxfield R, Almeida M, Gilchrist M, Gonzalo X, Moore L, Donaldson H, Davies Fet al., 2022, A practical laboratory method to determine ceftazidime-avibactam-aztreonam synergy in patients with New Delhi Metallo-beta-lactamase (NDM) producing Enterobacterales infection, Journal of Global Antimicrobial Resistance, Vol: 29, Pages: 558-562, ISSN: 2213-7165

Background:In response to infection with New Delhi Metallo-beta-lactamase (NDM) producing Enterobacterales, combination antimicrobial therapy with ceftazidime/avibactam (CAZ/AVI) plus aztreonam (ATM) has been explored. This study evaluated a practical laboratory method of testing for clinically significant synergy between CAZ/AVI+ATM in NDM producing Enterobacterales.Methods:Minimum inhibitory concentration (MIC) of clinical NDM producing isolates were determined for ATM alone and CAZ/AVI+ATM using broth dilution. Restoration of ATM breakpoint following the addition of CAZ/AVI was explored. A CAZ/AVI E-test/ATM disc method was compared to broth dilution.Results:Of 43 isolates, 33/43 (77%) isolates were ATM resistant (median [range] MIC=56 [16 – 512] mg/L). Addition of CAZ/AVI restored the ATM breakpoint (MIC <4mg/L) in 29/33 (89%) of resistant isolates. Overall, the E-test/disc method correlated with findings from broth dilution in 35/43 (81%) of cases. E-test/disc sensitivity was 77% and specificity 85%. Positive predictive value was 92% and negative predictive value 61%.Conclusion:CAZ/AVI+ATM demonstrated significant synergy in most ATM resistant NDM producing Enterobacterales. The E-test/disc method is a quick, reproducible, and reliable method of testing for clinically relevant synergy in the microbiology laboratory.

Journal article

Arkell P, Wilson R, Antcliffe DB, Gilchrist M, Noel AR, Wilson M, Barnes SC, Watkins K, Holmes A, Rawson TMet al., 2022, A pilot observational study of CSF vancomycin therapeutic drug monitoring during the treatment of nosocomial ventriculitis., Journal of Infection, ISSN: 0163-4453

Journal article

Mehta R, Chekmeneva E, Jackson H, Sands C, Mills E, Arancon D, Li HK, Arkell P, Rawson T, Hammond R, Amran M, Haber A, Cooke G, Noursadeghi M, Kaforou M, Lewis M, Takats Z, Sriskandan Set al., 2022, Antiviral metabolite 3’-Deoxy-3’,4’-didehydro-cytidine is detectable in serum and identifies acute viral infections including COVID-19, Med, Vol: 3, Pages: 204-215.e6, ISSN: 2666-6340

Background:There is a critical need for rapid viral infection diagnostics to enable prompt case identification in pandemic settings and support targeted antimicrobial prescribing.Methods:Using untargeted high-resolution liquid chromatography coupled with mass spectrometry, we compared the admission serum metabolome of emergency department patients with viral infections including COVID-19, bacterial infections, inflammatory conditions, and healthy controls. Sera from an independent cohort of emergency department patients admitted with viral or bacterial infections underwent profiling to validate findings. Associations between whole-blood gene expression and the identified metabolite of interest were examined.Findings:3'-Deoxy-3',4'-didehydro-cytidine (ddhC), a free base of the only known human antiviral small molecule ddhC-triphosphate (ddhCTP), was detected for the first time in serum. When comparing 60 viral to 101 non-viral cases in the discovery cohort, ddhC was the most differentially abundant metabolite, generating an area under the receiver operating characteristic curve (AUC) of 0.954 (95% CI: 0.923-0.986). In the validation cohort, ddhC was again the most significantly differentially abundant metabolite when comparing 40 viral to 40 bacterial cases, generating an AUC of 0.81 (95% CI 0.708-0.915). Transcripts of viperin and CMPK2, enzymes responsible for ddhCTP synthesis, were amongst the five genes most highly correlated to ddhC abundance.Conclusions:The antiviral precursor molecule ddhC is detectable in serum and an accurate marker for acute viral infection. Interferon-inducible genes viperin and CMPK2 are implicated in ddhC production in vivo. These findings highlight a future diagnostic role for ddhC in viral diagnosis, pandemic preparedness, and acute infection management.

Journal article

Mehta R, Chekmeneva E, Jackson H, Sands C, Mills E, Arancon D, Li HK, Arkell P, Rawson TM, Hammond R, Amran M, Haber A, Cooke GS, Noursadeghi M, Kaforou M, Lewis MR, Takats Z, Sriskandan Set al., 2022, Antiviral metabolite 3'-deoxy-3',4'-didehydro-cytidine is detectable in serum and identifies acute viral infections including COVID-19., Med (New York, N.Y.), Vol: 3, Pages: 204-215.e6, ISSN: 2666-6359

<h4>Background</h4>There is a critical need for rapid viral infection diagnostics to enable prompt case identification in pandemic settings and support targeted antimicrobial prescribing.<h4>Methods</h4>Using untargeted high-resolution liquid chromatography coupled with mass spectrometry, we compared the admission serum metabolome of emergency department patients with viral infections (including COVID-19), bacterial infections, inflammatory conditions, and healthy controls. Sera from an independent cohort of emergency department patients admitted with viral or bacterial infections underwent profiling to validate findings. Associations between whole-blood gene expression and the identified metabolite of interest were examined.<h4>Findings</h4>3'-Deoxy-3',4'-didehydro-cytidine (ddhC), a free base of the only known human antiviral small molecule ddhC-triphosphate (ddhCTP), was detected for the first time in serum. When comparing 60 viral with 101 non-viral cases in the discovery cohort, ddhC was the most significantly differentially abundant metabolite, generating an area under the receiver operating characteristic curve (AUC) of 0.954 (95% CI: 0.923-0.986). In the validation cohort, ddhC was again the most significantly differentially abundant metabolite when comparing 40 viral with 40 bacterial cases, generating an AUC of 0.81 (95% CI 0.708-0.915). Transcripts of viperin and <i>CMPK2</i>, enzymes responsible for ddhCTP synthesis, were among the five genes most highly correlated with ddhC abundance.<h4>Conclusions</h4>The antiviral precursor molecule ddhC is detectable in serum and an accurate marker for acute viral infection. Interferon-inducible genes viperin and <i>CMPK2</i> are implicated in ddhC production <i>in vivo</i>. These findings highlight a future diagnostic role for ddhC in viral diagnosis, pandemic preparedness, and acute infection management.<h4>Funding</h

Journal article

Rawson TM, Peiffer-Smadja N, Holmes A, 2022, Artificial Intelligence in Infectious Diseases, Artificial Intelligence in Medicine, Pages: 1327-1340, ISBN: 9783030645724

The management of infectious diseases lends itself to the application of artificial intelligence. The treatment of infection is complex, requiring the consideration of a large number of dynamic variables to inform decision-making. This includes considering organism, host, and drug factors in the context of local disease epidemiology and potential long-term consequences of anti-infective use, such as the development of antimicrobial resistance. The heterogeneity of clinical presentation caused by the same pathogen means that in many cases there is a paucity of data available to guide decision-making in real time, with individualized decisions made based on the individual patient and available data. Within this chapter we explore current applications of artificial intelligence in (i) the laboratory detection of microorganisms, (ii) the clinical diagnosis and management of infectious diseases, and (iii) the surveillance of infection. This chapter will not address other potential areas for the application of AI in infectious diseases that include anti-infective drug development, targeting infection prevention activity, and public health decision-making. We highlight potential future directions for AI in infectious diseases within the areas explored by this chapter and current barriers to wider adoption of such systems.

Book chapter

Al-Hindawi A, Abdulaal A, Rawson T, Alqahtani S, Mughal N, Moore Let al., 2021, COVID-19 prognostic models: a pro-con debate for machine learning vs traditional statistics, Frontiers in Digital Health, Vol: 3, Pages: 1-6, ISSN: 2673-253X

The SARS-CoV-2 virus causing the COVID-19 pandemic has had an unprecedented impact on healthcare requiring multi-disciplinary innovation and novel thinking to minimise impact and improve outcomes. Wide ranging disciplines have collaborated including diverse clinicians (radiology, microbiology, critical care) working increasingly closely with data-science. This has been leveraged through the democratisation of data-science with increasing availability of easy to access open datasets, tutorials, programming languages and hardware it is significantly easier to create mathematical models. To address the COVID-19 pandemic, such data-science has enabled modelling of the impact of the virus on the population and on individuals for diagnostic, prognostic, and epidemiological ends. This has led to two large systematic reviews on this topic that have highlighted the two different ways in which this feat has been attempted: one using classical statistics and the other using more novel machine learning techniques. In this review, we debate the relative strengths and weaknesses of each method towards the specific task of predicting COVID-19 outcomes

Journal article

Rawson TM, Wilson RC, O'Hare D, Herrero P, Kambugu A, Lamorde M, Ellington M, Georgiou P, Cass A, Hope WW, Holmes AHet al., 2021, Optimizing antimicrobial use: challenges, advances and opportunities, NATURE REVIEWS MICROBIOLOGY, Vol: 19, Pages: 747-758, ISSN: 1740-1526

Journal article

Rawson TM, Wilson R, Moore L, Macgowan A, Lovering A, Bayliss M, Kyriakides M, Gilchrist M, Roberts J, Hope W, Holmes Aet al., 2021, Exploring the pharmacokinetics of phenoxymethylpenicillin (Penicillin-V) in adults: a healthy volunteer study, Open Forum Infectious Diseases, Vol: 8, Pages: 1-4, ISSN: 2328-8957

This healthy volunteer study aimed to explore Phenoxymethylpenicillin (Penicillin-V) pharmacokinetics (PK) to support the planning of large, dosing studies in adults. Volunteers were dosed with penicillin-V at steady state. Total and unbound penicillin-V serum concentration was determined and a base population PK model were fitted to the data.

Journal article

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