415 results found
Vasikasin V, Panuvatvanich B, Rawson TM, et al., 2023, Towards optimizing carbapenem selection in stewardship strategies: a prospective propensity score-matched study of ertapenem versus class 2 carbapenems for empirical treatment of third-generation cephalosporin-resistant Enterobacterales bacteraemia., J Antimicrob Chemother
BACKGROUND: Third-generation cephalosporin-resistant Enterobacterales (3GCRE) are increasing in prevalence, leading to greater carbapenem consumption. Selecting ertapenem has been proposed as a strategy to reduce carbapenem resistance development. However, there are limited data for the efficacy of empirical ertapenem for 3GCRE bacteraemia. OBJECTIVES: To compare the efficacy of empirical ertapenem and class 2 carbapenems for the treatment of 3GCRE bacteraemia. METHODS: A prospective non-inferiority observational cohort study was performed from May 2019 to December 2021. Adult patients with monomicrobial 3GCRE bacteraemia receiving carbapenems within 24 h were included at two hospitals in Thailand. Propensity scores were used to control for confounding, and sensitivity analyses were performed in several subgroups. The primary outcome was 30 day mortality. This study is registered with clinicaltrials.gov (NCT03925402). RESULTS: Empirical carbapenems were prescribed in 427/1032 (41%) patients with 3GCRE bacteraemia, of whom 221 received ertapenem and 206 received class 2 carbapenems. One-to-one propensity score matching resulted in 94 pairs. Escherichia coli was identified in 151 (80%) of cases. All patients had underlying comorbidities. Septic shock and respiratory failure were the presenting syndromes in 46 (24%) and 33 (18%) patients, respectively. The overall 30 day mortality rate was 26/188 (13.8%). Ertapenem was non-inferior to class 2 carbapenems in 30 day mortality (12.8% versus 14.9%; mean difference -0.02; 95% CI: -0.12 to 0.08). Sensitivity analyses were consistent regardless of aetiological pathogens, septic shock, source of infection, nosocomial acquisition, lactate levels or albumin levels. CONCLUSIONS: Ertapenem may be of comparable efficacy to class 2 carbapenems in the empirical treatment of 3GCRE bacteraemia.
Karolcik S, Ming D, Yacoub S, et al., 2023, A multi-site, multi-wavelength PPG platform for continuous non-invasive health monitoring in hospital settings, IEEE Transactions on Biomedical Circuits and Systems, Vol: 17, Pages: 349-361, ISSN: 1932-4545
This paper presents a novel PPG acquisition platform capable of synchronous multi-wavelength signal acquisition from two measurement locations with up to 4 independent wavelengths from each in parallel. The platform is fully configurable and operates at 1ksps, accommodating a wide variety of transmitters and detectors to serve as both a research tool for experimentation and a clinical tool for disease monitoring. The sensing probes presented in this work acquire 4 PPG channels from the wrist and 4 PPG channels from the fingertip, with wavelengths such that surrogates for pulse wave velocity and haematocrit can be extracted.For conventional PPG sensing, we have achieved the mean error of 4.08 ± 3.72 bpm for heart-rate and a mean error of 1.54 ± 1.04% for SpO2 measurement, with the latter lying within the FDA limits for commercial pulse oximeters. We have further evaluated over 700 individual peak-to-peak time differences between wrist and fingertip signals, achieving a normalized weighted average PWV of 5.80 ± 1.58 m/s, matching with values of PWV found for this age group in literature. Lastly, we introduced and computed a haematocrit ratio (Rhct) between the deep IR and deep red wavelength from the fingertip sensor, finding a significant difference between male and female values (median of 1.9 and 2.93 respectively) pointing to devices sensitivity to Hct.
Vasikasin V, Rawson TM, Holmes AH, et 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.
Freeman DME, Ming DK, Wilson R, et al., 2023, Continuous Measurement of Lactate Concentration in Human Subjects through Direct Electron Transfer from Enzymes to Microneedle Electrodes, ACS SENSORS, ISSN: 2379-3694
Mao Y, Miglietta L, Kreitmann L, et al., 2023, Deep domain adaptation enhances Amplification Curve Analysis for single-channel multiplexing in real-time PCR, IEEE Journal of Biomedical and Health Informatics, ISSN: 2168-2208
Data-driven approaches for molecular diagnostics are emerging as an alternative to perform an accurate and inexpensive multi-pathogen detection. A novel technique called Amplification Curve Analysis (ACA) has been recently developed by coupling machine learning and real-time Polymerase Chain Reaction (qPCR) to enable the simultaneous detection of multiple targets in a single reaction well. However, target classification purely relying on the amplification curve shapes currently faces several challenges, such as distribution discrepancies between different data sources of synthetic DNA and clinical samples (i.e., training vs testing). Optimisation of computational models is required to achieve higher performance of ACA classification in multiplex qPCR through the reduction of those discrepancies. Here, we proposed a novel transformer-based conditional domain adversarial network (T-CDAN) to eliminate data distribution differences between the source domain (synthetic DNA data) and the target domain (clinical isolate data). The labelled training data from the source domain and unlabelled testing data from the target domain are fed into the T-CDAN, which learns both domains' information simultaneously. After mapping the inputs into a domain-irrelevant space, T-CDAN removes the feature distribution differences and provides a clearer decision boundary for the classifier, resulting in a more accurate pathogen identification. Evaluation of 198 clinical isolates containing three types of carbapenem-resistant genes ( bla NDM , bla IMP and bla OXA-48 ) illustrates a curve-level accuracy of 93.1% and a sample-level accuracy of 97.0% using T-CDAN, showing an accuracy improvement of 20.9% and 4.9% respectively, compared with previous methods. This research emphasises the importance of deep domain adaptation to enable high-level multiplexing in a single qPCR reaction, providing a solid approach to extend qPCR instruments' capabilities without hardware modification in real-world cli
Kreitmann L, Miglietta L, Xu K, et al., 2023, Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR, TrAC Trends in Analytical Chemistry, Vol: 160, Pages: 1-11, ISSN: 0165-9936
Real-time polymerase chain reaction (qPCR) enables accurate detection and quantification of nucleic acids and has become a fundamental tool in biological sciences, bioengineering and medicine. By combining multiple primer sets in one reaction, it is possible to detect several DNA or RNA targets simultaneously, a process called multiplex PCR (mPCR) which is key to attaining optimal throughput, cost-effectiveness and efficiency in molecular diagnostics, particularly in infectious diseases. Multiple solutions have been devised to increase multiplexing in qPCR, including single-well techniques, using target-specific fluorescent oligonucleotide probes, and spatial multiplexing, where segregation of the sample enables parallel amplification of multiple targets. However, these solutions are mostly limited to three or four targets, or highly sophisticated and expensive instrumentation. There is a need for innovations that will push forward the multiplexing field in qPCR, enabling for a next generation of diagnostic tools which could accommodate high throughput in an affordable manner.To this end, the use of machine learning (ML) algorithms (data-driven solutions) has recently emerged to leverage information contained in amplification and melting curves (AC and MC, respectively) – two of the most standard bio-signals emitted during qPCR – for accurate classification of multiple nucleic acid targets in a single reaction. Therefore, this review aims to demonstrate and illustrate that data-driven solutions can be successfully coupled with state-of-the-art and common qPCR platforms using a variety of amplification chemistries to enhance multiplexing in qPCR.Further, because both ACs and MCs can be predicted from sequence data using thermodynamic databases, it has also become possible to use computer simulation to rationalize and optimize the design of mPCR assays where target detection is supported by data-driven technologies. Thus, this review also discusses recent
Mbamalu O, Surendran S, Nampoothiri V, et al., 2023, Survey of healthcare worker perceptions of changes in infection control and antimicrobial stewardship practices in India and South Africa during the COVID-19 pandemic., IJID Reg, Vol: 6, Pages: 90-98
OBJECTIVE: To identify perceptions and awareness of changes in infection prevention and control (IPC) and antimicrobial stewardship (AMS) practices among healthcare workers (HCWs) during the COVID-19 pandemic in India and South Africa (SA). METHOD: A self-administered online survey which included participant demographics, knowledge and sources of COVID-19 infection, perceived risks and barriers, and self-efficacy. Data were analysed using descriptive statistics. RESULTS: The study received 321 responses (response rate: 89.2%); 131/321 (40.8%) from India and 190/321 (59.2%) from SA; male to female response rate was 3:2, with majority of respondents aged 40-49 (89/321, 27.7%) and 30-39 (87/321, 27.1%) years. Doctors comprised 47.9% (57/119) of respondents in India and 74.6% (135/181) in SA. Majority of respondents in India (93/119, 78.2%) and SA (132/181, 72.9%) were from the private and public sectors, respectively, with more respondents in SA (123/174, 70.7%) than in India (38/104, 36.5%) involved in antimicrobial prescribing.Respondents reported increased IPC practices since the pandemic and noted a need for more training on case management, antibiotic and personal protective equipment (PPE) use. While they noted increased antibiotic prescribing since the pandemic, they did not generally associate their practice with such an increase. A willingness to be vaccinated, when vaccination becomes available, was expressed by 203/258 (78.7%) respondents. CONCLUSIONS: HCWs reported improved IPC practices and changes in antibiotic prescribing during the COVID-19 pandemic. Targeted education on correct use of PPE was an identified gap. Although HCWs expressed concerns about antimicrobial resistance, their self-perceived antibiotic prescribing practices seemed unchanged. Additional studies in other settings could explore how our findings fit other contexts.
Charani ESMITA, Mendelson M, Pallett S, et al., 2023, An analysis of existing National Action Plans for antimicrobial resistance – gaps and opportunities in strategies optimising antibiotic use in human populations, The Lancet Global Health, Vol: 11, Pages: e466-e474, ISSN: 2214-109X
At the 2015 World Health Assembly, UN member states adopted a resolution that committed to the development of national action plans (NAPs) for antimicrobial resistance (AMR). The political determination to commit to NAPs and the availability of robust governance structures to assure sustainable translation of the identified NAP objectives from policy to practice remain major barriers to progress. Inter-country variability in economic and political resilience and resource constraints could be fundamental barriers to progressing AMR NAPs. Although there have been regional and global analyses of NAPs from a One Health and policy perspective, a global assessment of the NAP objectives targeting antimicrobial use in human populations is needed. In this Health Policy, we report a systematic evidence synthesis of existing NAPs that are aimed at tackling AMR in human populations. We find marked gaps and variability in maturity of NAP development and operationalisation across the domains of: (1) policy and strategic planning; (2) medicines management and prescribing systems; (3) technology for optimised antimicrobial prescribing; (4) context, culture, and behaviours; (5) operational delivery and monitoring; and (6) patient and public engagement and involvement. The gaps identified in these domains highlight opportunities to facilitate sustainable delivery and operationalisation of NAPs. The findings from this analysis can be used at country, regional, and global levels to identify AMR-related priorities that are relevant to infrastructure needs and contexts.
Hernandez Perez B, Stiff O, Ming D, et al., 2023, Learning meaningful latent space representations for patient risk stratification: model development and validation for dengue and other acute febrile illness, Frontiers in Digital Health, Vol: 5, Pages: 1-16, ISSN: 2673-253X
Background: Increased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, their adoption remains low due to concerns regarding the quality of recommendations, and a lack of clarity on how results are best obtained and presented.Methods: We used autoencoders capable of reducing the dimensionality of complex datasets in order to produce a 2D representation denoted as latent space to support understanding of complex clinical data. In this output, meaningful representations of individual patient profiles are spatially mapped in an unsupervised manner according to their input clinical parameters. This technique was then applied to a large real-world clinical dataset of over 12,000 patients with an illness compatible with dengue infection in Ho Chi Minh City, Vietnam between 1999 and 2021. Dengue is a systemic viral disease which exerts significant health and economic burden worldwide, and up to 5% of hospitalised patients develop life-threatening complications.Results: The latent space produced by the selected autoencoder aligns with established clinical characteristics exhibited by patients with dengue infection, as well as features of disease progression. Similar clinical phenotypes are represented close to each other in the latent space and clustered according to outcomes broadly described by the World Health Organisation dengue guidelines. Balancing distance metrics and density metrics produced results covering most of the latent space, and improved visualisation whilst preserving utility, with similar patients grouped closer together. In this case, this balance is achieved by using the sigmoid activation function and one hidden layer with three neurons, in addition to the latent dimension layer, which produces the output (Pearson, 0.840; Spearman
Ming D, Nguyen QH, An LP, et al., 2023, Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools, BMC Medical Informatics and Decision Making, Vol: 23, Pages: 1-9, ISSN: 1472-6947
BackgroundDengue is a common viral illness and severe disease results in life-threatening complications. Healthcare services in low- and middle-income countries treat the majority of dengue cases worldwide. However, the clinical decision-making processes which result in effective treatment are poorly characterised within this setting. In order to improve clinical care through interventions relating to digital clinical decision-support systems (CDSS), we set out to establish a framework for clinical decision-making in dengue management to inform implementation.MethodsWe utilised process mapping and task analysis methods to characterise existing dengue management at the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. This is a tertiary referral hospital which manages approximately 30,000 patients with dengue each year, accepting referrals from Ho Chi Minh city and the surrounding catchment area. Initial findings were expanded through semi-structured interviews with clinicians in order to understand clinical reasoning and cognitive factors in detail. A grounded theory was used for coding and emergent themes were developed through iterative discussions with clinician-researchers.ResultsKey clinical decision-making points were identified: (i) at the initial patient evaluation for dengue diagnosis to decide on hospital admission and the provision of fluid/blood product therapy, (ii) in those patients who develop severe disease or other complications, (iii) at the point of recurrent shock in balancing the need for fluid therapy with complications of volume overload. From interviews the following themes were identified: prioritising clinical diagnosis and evaluation over existing diagnostics, the role of dengue guidelines published by the Ministry of Health, the impact of seasonality and caseload on decision-making strategies, and the potential role of digital decision-support and disease scoring tools.ConclusionsThe study highlights the contemporary priorities i
Otter JA, Zhou J, Price JR, et al., 2023, SARS-CoV-2 surface and air contamination in an acute healthcare setting during the first and second pandemic waves, JOURNAL OF HOSPITAL INFECTION, Vol: 132, Pages: 36-45, ISSN: 0195-6701
Nampoothiri V, Mbamalu O, Surendran S, et al., 2023, The elephant in the room: Exploring the influence and participation of patients in infection-related care across surgical pathways in South Africa and India, HEALTH EXPECTATIONS, ISSN: 1369-6513
Riezk A, Vasikasin V, Wilson RCC, et al., 2023, Triple quadrupole LC/MS method for the simultaneous quantitative measurement of cefiderocol and meropenem in serum, ANALYTICAL METHODS, Vol: 15, Pages: 746-751, ISSN: 1759-9660
Riezk A, Wilson RC, Rawson TM, et 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, Vol: 15, Pages: 829-836, ISSN: 1759-9660
Birgand G, Ahmad R, Bulabula ANH, et al., 2022, Innovation for infection prevention and control-revisiting Pasteur's vision, LANCET, Vol: 400, Pages: 2250-2260, ISSN: 0140-6736
Zhang S, Chen Y-C, Riezk A, et al., 2022, Rapid measurement of lactate in exhaled breath condensate: biosensor optimisation and in-human proof-of-concept, ACS Sensors, Vol: 7, Pages: 3809-3816, ISSN: 2379-3694
Lactate concentration is of increasing interest as a diagnostic for sepsis, septic shock, and trauma. Compared with the traditional blood sample media, the exhaled breath condensate (EBC) has the advantages of non-invasiveness and higher user acceptance. An amperometric biosensor was developed and its application in EBC lactate detection was investigated in this paper. The sensor was modified with PEDOT:PSS-PB, and two different lactate oxidases (LODs). A rotating disk electrode and Koutecky–Levich analysis were applied for the kinetics analysis and gel optimization. The optimized gel formulation was then tested on disposable screen-printed sensors. The disposable sensors exhibited good performance and presented a high stability for both LOD modifications. Finally, human EBC analysis was conducted from a healthy subject at rest and after 30 min of intense aerobic cycling exercise. The sensor coulometric measurements showed good agreement with fluorometric and triple quadrupole liquid chromatography mass spectrometry reference methods. The EBC lactate concentration increased from 22.5 μM (at rest) to 28.0 μM (after 30 min of cycling) and dropped back to 5.3 μM after 60 min of rest.
Bolton W, Rawson T, Hernandez B, et 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.
Bolton WJ, Badea C, Georgiou P, et al., 2022, Developing moral AI to support decision-making about antimicrobial use, NATURE MACHINE INTELLIGENCE, Vol: 4, Pages: 912-915
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Ahmad R, Gordon AC, Aylin P, et al., 2022, Effective knowledge mobilisation: creating environments for quick generation, dissemination, and use of evidence., The BMJ, Vol: 379, Pages: 1-5, ISSN: 1759-2151
Ahuja S, Singh S, Charani E, et al., 2022, An evaluation of the implementation of interventions to reduce post-operative infections and optimise antibiotic use across the surgical pathway in India: A mixed methods exploratory study protocol, Pilot and Feasibility Studies, Vol: 8, ISSN: 2055-5784
Introduction:Postoperative infections represent a significant burden of disease, demanding antibiotic prescriptions, and are contributing to antimicrobial resistance. The burden of infection as a surgical complication is greater in low- and middle-income countries (LMICs). We report the protocol of a pilot study for the co-design, implementation and evaluation of two infection prevention and control (IPC) and antimicrobial stewardship (AMS) interventions across the surgical pathway in a teaching hospital in India.Methods and analysis:The two interventions developed following in-depth qualitative enquiry are (i) surveillance and feedback of postoperative infections to optimise the use of antibiotics in two surgical departments (gastrointestinal and cardiovascular and thoracic surgery) and (ii) raising awareness amongst patients, carers and members of public about IPC and AMS. We will conduct a prospective study, formatively evaluating the implementation process of delivering the two co-designed interventions using implementation science frameworks. The study will systematically assess the context of intervention delivery, so that implementation support for the interventions may be adapted to the needs of stakeholders throughout the study. Analysis of implementation logs and interviews with stakeholders upon completion of the implementation period, will offer insights into the perceived acceptability, appropriateness, feasibility and sustainability of the interventions and their implementation support. Implementation costs will be captured descriptively. Feasibility of clinical data collection to investigate effectiveness of interventions will also be assessed for a future larger study. Thematic framework analysis and descriptive statistics will be used to report the qualitative and quantitative data, respectively.Strengths and limitations of this study:• The paired interventions have been co-designed from their inception with involvement of stakeholders at diffe
Herrero Vinas P, Wilson R, Armiger R, et 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.
Miglietta L, Xu K, Chhaya P, et al., 2022, Adaptive filtering framework to remove nonspecific and low-efficiency reactions in multiplex digital PCR based on sigmoidal trends., Analytical Chemistry, Vol: 94, Pages: 14159-14168, ISSN: 0003-2700
Real-time digital polymerase chain reaction (qdPCR) coupled with machine learning (ML) methods has shown the potential to unlock scientific breakthroughs, particularly in the field of molecular diagnostics for infectious diseases. One promising application of this emerging field explores single fluorescent channel PCR multiplex by extracting target-specific kinetic and thermodynamic information contained in amplification curves, also known as data-driven multiplexing. However, accurate target classification is compromised by the presence of undesired amplification events and not ideal reaction conditions. Therefore, here, we proposed a novel framework to identify and filter out nonspecific and low-efficient reactions from qdPCR data using outlier detection algorithms purely based on sigmoidal trends of amplification curves. As a proof-of-concept, this framework is implemented to improve the classification performance of the recently reported data-driven multiplexing method called amplification curve analysis (ACA), using available published data where the ACA is demonstrated to screen carbapenemase-producing organisms in clinical isolates. Furthermore, we developed a novel strategy, named adaptive mapping filter (AMF), to adjust the percentage of outliers removed according to the number of positive counts in qdPCR. From an overall total of 152,000 amplification events, 116,222 positive amplification reactions were evaluated before and after filtering by comparing against melting peak distribution, proving that abnormal amplification curves (outliers) are linked to shifted melting distribution or decreased PCR efficiency. The ACA was applied to assess classification performance before and after AMF, showing an improved sensitivity of 1.2% when using inliers compared to a decrement of 19.6% when using outliers (p-value < 0.0001), removing 53.5% of all wrong melting curves based only on the amplification shape. This work explores the correlation between the kinetics
Arkell P, Wilson R, Watkins K, et 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.
Bolton W, Badea C, Georgiou P, et al., 2022, Developing Moral AI to Support Antimicrobial Decision Making, Nature Machine Intelligence, ISSN: 2522-5839
Surendran S, Castro-Sanchez E, Nampoothiri V, et al., 2022, Indispensable yet invisible: A qualitative study of carer roles in infection prevention in a South Indian hospital, International Journal of Infectious Diseases, Vol: 123, Pages: 84-91, ISSN: 1201-9712
Objectives We investigated the roles of patient carers in infection-related care on surgical wards in a South Indian hospital, from the perspective of healthcare workers (HCW), patients, and their carers. Methods Ethnographic study including ward-round observations (138 hours) and face-to-face interviews (44 HCW, 6 patients/carers). Data (field notes, interview transcripts) were coded in NVivo 12 and thematically analysed. Data collection and analysis were iterative, recursive and continued until thematic saturation. Results Carers have important, unrecognised roles. In the study site, institutional expectations are formalised in policies demanding a carer to always accompany inpatients. Such intense presence embeds families in the patient care environment, as demonstrated by their high engagement in direct personal (bathing patients) and clinical care (wound care). Carers actively participate in discussions on patient progress with HCWs, including therapeutic options. There is a misalignment between how carers are positioned by the organisation (through policy mandates, institutional practices, and HCWs expectations), and the role that they play in practice, resulting in their role, though indispensable, remaining unrecognised. Conclusion Current models of patient and carer involvement in infection prevention and control (IPC) are poorly aligned with socio-cultural and contextual aspects of care. Culture-sensitive IPC policies which embrace the roles that carers play are urgently needed.
Moser N, Yu L-S, Rodriguez Manzano J, et al., 2022, Quantitative detection of dengue serotypes using a smartphone-connected handheld Lab-on-Chip platform, Frontiers in Bioengineering and Biotechnology, Vol: 10, Pages: 1-14, ISSN: 2296-4185
Dengue is one of the most prevalent infectious diseases in the world. Rapid, accurate and scalable diagnostics are key to patient management and epidemiological surveillance of the dengue virus (DENV), however current technologies do not match required clinical sensitivity and specificity or rely on large laboratory equipment. In this work, we report the translation of our smartphone-connected handheld Lab-on-Chip (LoC) platform for the quantitative detection of twodengue serotypes. At its core, the approach relies on the combination of Complementary Metal Oxide-Semiconductor (CMOS) microchip technology to integrate an array of 78x56 potentiometric sensors, and a label-free reverse-transcriptase loop mediated isothermal amplification (RT-LAMP) assay. The platform communicates to a smartphone app which synchronises results in real time with a secure cloud server hosted by Amazon Web Services (AWS) for epidemiological surveillance. The assay on our LoC platform (RT-eLAMP) was shown to match performance on a gold-standard fluorescence-based real-time instrument (RT-qLAMP) with synthetic DENV-1 and DENV-2 RNA and extracted RNA from 9 DENV-2 clinical isolates, achieving quantitative detection in under 15 minutes. To validate the portability of the platform and the geo-tagging capabilities, we led our study in the laboratories at Imperial College London, UK, and Kaohsiung Medical Hospital, Taiwan. This approach carries high potential for application in low resource settings at the point-of-care (PoC).
Stirrup O, Blackstone J, Mapp F, et al., 2022, Effectiveness of rapid SARS-CoV-2 genome sequencing in supporting infection control for hospital-onset COVID-19 infection: Multicentre, prospective study, ELIFE, Vol: 11, ISSN: 2050-084X
Wilson R, Arkell P, Riezk A, et 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
Rawson TM, Eigo T, Wilson R, et 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
Boyd SE, Holmes A, Peck R, et al., 2022, OXA-48-like β-lactamases: global epidemiology, treatment options, and development pipeline, Antimicrobial Agents and Chemotherapy, Vol: 66, ISSN: 0066-4804
Modern medicine is threatened by the rising tide of antimicrobial resistance, especially among Gram-negative bacteria, where resistance to β-lactams is most often mediated by β-lactamases. The penicillin and cephalosporin ascendancies were, in their turn, ended by the proliferation of TEM penicillinases and CTX-M extended-spectrum β-lactamases. These class A β-lactamases have long been considered the most important. For carbapenems, however, the threat is increasingly from the insidious rise of a class D carbapenemase, OXA-48, and its close relatives. Over the past 20 years, OXA-48 and "OXA-48-like" enzymes have proliferated to become the most prevalent enterobacterial carbapenemases across much of Europe, Northern Africa, and the Middle East. OXA-48-like enzymes are notoriously difficult to detect because they often cause only low-level in vitro resistance to carbapenems, meaning that the true burden is likely underestimated. Despite this, they are associated with carbapenem treatment failures. A highly conserved incompatibility complex IncL plasmid scaffold often carries blaOXA-48 and may carry other antimicrobial resistance genes, leaving limited treatment options. High conjugation efficiency means that this plasmid is sometimes carried by multiple Enterobacterales in a single patient. Producers evade most β-lactam-β-lactamase inhibitor combinations, though promising agents have recently been licensed, notably ceftazidime-avibactam and cefiderocol. The molecular machinery enabling global spread, current treatment options, and the development pipeline of potential new therapies for Enterobacterales that produce OXA-48-like β-lactamases form the focus of this review.
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