Search

Introduction. The term 'diagnostic stewardship' is relatively new, with a recent surge in its use within the literature. Despite its increasing popularity, a precise definition remains elusive. Various attempts have been made to define it, with some viewing it as an integral part of antimicrobial stewardship. The World Health Organization offers a broad definition, emphasizing the importance of timely, accurate diagnostics. However, inconsistencies in the use of this term still persist, necessitating further clarification. Gap Statement. There are currently inconsistencies in the definition of diagnostic stewardship used within the academic literature. Aim. This scoping review aims to categorize the use of diagnostic stewardship approaches and define this approach by identifying common characteristics and factors of its use within the literature. Methodology. This scoping review undertook a multi-database search from date of inception until October 2022. Any observational or experimental study where the authors define the intervention to be diagnostic stewardship from any clinical area was included. Screening of all papers was undertaken by a single reviewer with 10% verification by a second reviewer. Data extraction was undertaken by a single reviewer using a pre-piloted form. Given the wide variation in study design and intervention outcomes, a narrative synthesis approach was applied. Studies were clustered around common diagnostic stewardship interventions where appropriate. Results. After duplicate removal, a total of 1310 citations were identified, of which, after full-paper screening, 105 studies were included in this scoping review. The classification of an intervention as taking a diagnostic stewardship approach is a relatively recent development, with the first publication in this field dating back to 2017. The majority of research in this area has been conducted within the USA, with very few studies undertaken outside this region. Visual inspection of the citation map reveals that the current evidence base is interconnected, with frequent references to each other's work. The interventions commonly adopt a restrictive approach, utilizing hard and soft stops within the pre-analytical phase to restrict access to testing. Upon closer examination of the outcomes, it becomes evident that there is a predominant focus on reducing the number of tests rather than enhancing the current test protocol. This is further reflected in the limited number of studies that report on test performance (including protocol improvements, specificity and sensitivity). Conclusion. Diagnostic stewardship seems to have deviated from its intended course, morphing into a rather rudimentary instrument wielded not to enhance but to constrict the scope of testing. Despite the World Health Organization's advocacy for an ideology that promotes a more comprehensive approach to quality improvement, it may be more appropriate to consider alternative regional narratives when categorizing these types of quality improvement interventions.

In this paper we present the design for a smart-mask to mitigate the impact of an airborne virus such as COVID-19. The design utilises recent results from feedback control theory over a distributed ledger that have been developed to enforce compliance in a pseudo-anonymous manner. The design is based on the use of the IOTA distributed ledger. A hardware-in-the-loop simulation based on indoor positioning, paired with Monte-Carlo simulations, is developed to demonstrate the efficacy of the designed prototype., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: To determine if the Charlson comorbidity index (CCI) is an accurate predictor of unplanned readmissions for patients using outpatient parenteral antimicrobial therapy (OPAT) services., Methods: Retrospective analysis of patients >16 years of age who had received OPAT at Lancashire Teaching Hospitals between 2019 and 2021. The number of unplanned hospitalizations was measured and categorized as OPAT related or non-OPAT related. The CCI for each patient group was calculated using an online tool, and logistic regression was used to assess the association between risk factors and risk of being readmitted., Results: The cohort consisted of 741 patients. Unplanned readmission was seen in 112 patients (15.1%). The mean CCI score for patients with OPAT-related readmissions was 4.22, 0.92 higher than the mean for patients who were not readmitted (3.30). The mean CCI score for patients with non-OPAT-related readmissions was higher still at 4.89. The logistic regression showed that increased CCI, age, male gender and home location compared with clinic were associated with increased odds of readmission, although these effects did not meet statistical significance., Conclusions: These results suggest that a higher CCI score is associated with a non-statistically significant increased risk of unplanned hospitalization. We concluded that the CCI may therefore be used in future decision-making regarding the acceptance of patients to OPAT and requires further investigation., (© The Author(s) 2023. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging mixed-reality technologies. This paper presents novel advances in the development of the interaction platform to generate 3D models using both constructive solid geometry and artificial intelligence. In specific, by taking advantage of the generative capabilities of deep neural networks, the system has been automated to generate 3D models inferred from a single 2D image captured by the user. Furthermore, a novel generative neural architecture, SliceGen, has been proposed and integrated with the system to overcome the limitation of single-type genus 3D model generation imposed by differentiable-rendering-based deep neural architectures. The system also enables the user to adjust the dimensions of the 3D models with respect to their physical workspace. The effectiveness of the system is demonstrated by generating 3D models of furniture (e.g., chairs and tables) and fitting them into the physical space in a mixed reality environment. The presented developmental advances provide a novel and immersive form of interaction to facilitate the inclusion of a consumer into the design process for personal fabrication., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Malik et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

It is well known that two-sided markets are unfair in a number of ways. For example, female drivers on ride-hailing platforms earn less than their male colleagues per mile driven. Similar observations have been made for other minority subgroups in other two-sided markets. Here, we suggest a novel market-clearing mechanism for two-sided markets, which promotes equalization of the pay per hour worked across multiple subgroups, as well as within each subgroup. In the process, we introduce a novel notion of subgroup fairness (which we call Inter-fairness), which can be combined with other notions of fairness within each subgroup (called Intra-fairness), and the utility for the customers (Customer-Care) in the objective of the market-clearing problem. Although the novel non-linear terms in the objective complicate market clearing by making the problem non-convex, we show that a certain non-convex augmented Lagrangian relaxation can be approximated to any precision in time polynomial in the number of market participants using semidefinite programming, thanks to its "hidden convexity". This makes it possible to implement the market-clearing mechanism efficiently. On the example of driver-ride assignment in an Uber-like system, we demonstrate the efficacy and scalability of the approach and trade-offs between Inter- and Intra-fairness., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The recent uptake in popularity in vehicles with zero tailpipe emissions is a welcome development in the fight against traffic induced airborne pollutants. As vehicle fleets become electrified, and tailpipe emissions become less prevalent, non-tailpipe emissions (from tires and brake disks) will become the dominant source of traffic related emissions, and will in all likelihood become a major concern for human health. This trend is likely to be exacerbated by the heavier weight of electric vehicles, their increased power, and their increased torque capabilities, when compared with traditional vehicles. While the problem of emissions from tire wear is well-known, issues around the process of tire abrasion, its impact on the environment, and modelling and mitigation measures, remain relatively unexplored. Work on this topic has proceeded in several discrete directions including: on-vehicle collection methods; vehicle tire-wear abatement algorithms and controlling the ride characteristics of a vehicle, all with a view to abating tire emissions. Additional approaches include access control mechanisms to manage aggregate tire emissions in a geofenced area with other notable work focussing on understanding the particle size distribution of tire generated PM, the degree to which particles become airborne, and the health impacts of tire emissions. While such efforts are already underway, the problem of developing models to predict the aggregate picture of a network of vehicles at the scale of a city, has yet to be considered. Our objective in this paper is to present one such model, built using ideas from Markov chains. Applications of our modelling approach are given toward the end of this note, both to illustrate the utility of the proposed method, and to illustrate its application as part of a method to collect tire dust particles., Competing Interests: The authors have declared that no competing interests exist.

Objectives: Since its emergence in late 2019, SARS-CoV-2 has caused a global pandemic that has significantly challenged healthcare systems. Healthcare workers have previously been shown to have experienced higher rates of infection than the general population. We aimed to assess the extent of infection in staff working in our healthcare setting., Design: A retrospective analysis of antibody results, compared with staff demographic data, and exposure to patients with COVID-19 infection., Setting: A large teaching hospital in the North West of England., Participants: 4474 staff in diverse clinical and non-patient facing roles who volunteered for SARS-CoV-2 antibody testing by the Roche Elecsys assay between 29 May and 4 July 2020., Results: Seroprevalence was 17.4%. Higher rates were seen in Asian/Asian British (OR 1.61, 95% CI 1.27 to 2.04) and Black/Black British (OR 2.08, 95% CI 1.25 to 3.45) staff. Staff working in any clinical location were more likely to be seropositive (OR 2.68, 95% 2.27 to 3.15). Staff were at an increased risk of seropositivity as the 'per 100 COVID-19 bed-days change' increased in the clinical area in which they worked (OR 1.12, 95% 1.10 to 1.14). Staff working in critical care were no more likely to have detectable antibodies than staff working in non-clinical areas. Symptoms compatible with COVID-19 were reported in 41.8% and antibodies were detected in 30.7% of these individuals. In staff who reported no symptoms, antibodies were detected in 7.7%. In all staff who had detectable antibodies, 25.2% reported no symptoms., Conclusions: Staff working in clinical areas where patients with COVID-19 were nursed were more likely to have detectable antibodies. The relationship between seropositivity in healthcare workers and the increase in 'per 100 COVID-19 bed-days' of the area in which they worked, although statistically significant, was weak, suggesting other contributing factors to the risk profile. Of staff with detectable antibodies and therefore evidence of prior infection, a quarter self-reported that they had experienced no compatible symptoms. This has implications for potential unrecorded transmission in both staff and patients., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

COVID-19 abatement strategies have risks and uncertainties which could lead to repeating waves of infection. We show-as proof of concept grounded on rigorous mathematical evidence-that periodic, high-frequency alternation of into, and out-of, lockdown effectively mitigates second-wave effects, while allowing continued, albeit reduced, economic activity. Periodicity confers (i) predictability, which is essential for economic sustainability, and (ii) robustness, since lockdown periods are not activated by uncertain measurements over short time scales. In turn-while not eliminating the virus-this fast switching policy is sustainable over time, and it mitigates the infection until a vaccine or treatment becomes available, while alleviating the social costs associated with long lockdowns. Typically, the policy might be in the form of 1-day of work followed by 6-days of lockdown every week (or perhaps 2 days working, 5 days off) and it can be modified at a slow-rate based on measurements filtered over longer time scales. Our results highlight the potential efficacy of high frequency switching interventions in post lockdown mitigation. All code is available on Github at https://github.com/V4p1d/FPSP_Covid19. A software tool has also been developed so that interested parties can explore the proof-of-concept system., Competing Interests: The authors have declared that no competing interests exist.

The recent COVID-19 outbreak has motivated an extensive development of non-pharmaceutical intervention policies for epidemics containment. While a total lockdown is a viable solution, interesting policies are those allowing some degree of normal functioning of the society, as this allows a continued, albeit reduced, economic activity and lessens the many societal problems associated with a prolonged lockdown. Recent studies have provided evidence that fast periodic alternation of lockdown and normal-functioning days may effectively lead to a good trade-off between outbreak abatement and economic activity. Nevertheless, the correct number of normal days to allocate within each period in such a way to guarantee the desired trade-off is a highly uncertain quantity that cannot be fixed a priori and that must rather be adapted online from measured data. This adaptation task, in turn, is still a largely open problem, and it is the subject of this work. In particular, we study a class of solutions based on hysteresis logic. First, in a rather general setting, we provide general convergence and performance guarantees on the evolution of the decision variable. Then, in a more specific context relevant for epidemic control, we derive a set of results characterizing robustness with respect to uncertainty and giving insight about how a priori knowledge about the controlled process may be used for fine-tuning the control parameters. Finally, we validate the results through numerical simulations tailored on the COVID-19 outbreak., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)

Testing, tracking and tracing abilities have been identified as pivotal in helping countries to safely reopen activities after the first wave of the COVID-19 virus. Contact tracing apps give the unprecedented possibility to reconstruct graphs of daily contacts, so the question is: who should be tested? As human contact networks are known to exhibit community structure, in this paper we show that the Kemeny constant of a graph can be used to identify and analyze bridges between communities in a graph. Our 'Kemeny indicator' is the value of the Kemeny constant in the new graph that is obtained when a node is removed from the original graph. We show that testing individuals who are associated with large values of the Kemeny indicator can help in efficiently intercepting new virus outbreaks, when they are still in their early stage. Extensive simulations provide promising results in early identification and in blocking the possible 'super-spreaders' links that transmit disease between different communities., Competing Interests: The authors have declared that no competing interests exist.

A male patient in his mid-60s presented with a severe pneumonia following return to the UK after travel to Crete. He was diagnosed with Legionnaire's disease (caused by an uncommon serogroup of Legionella pneumophila ). He was pancytopenic on admission, and during a long stay on critical care he was diagnosed with a disseminated Aspergillus infection. Bone marrow aspiration revealed an underlying hairy cell leukaemia that undoubtedly contributed to his acute presentation and subsequent invasive fungal infection., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

The Xpert MTB/RIF assay can rapidly diagnose tuberculosis, but sputum samples cannot be safely processed unless in a lab. The septum sample pot allows safe handling of sputum and has allowed a mobile TB unit to run the assay in community settings. http://ow.ly/HOA130mS6LG., Competing Interests: Conflict of interest: H.D. Gliddon has nothing to disclose. Conflict of interest: R.J. Shorten reports personal fees from Cepheid (sponsored attendance at an international conference in 2016), outside the submitted work. Conflict of interest: A.C. Hayward has nothing to disclose. Conflict of interest: A. Story has nothing to disclose.

The 2014 to 2016 Ebola virus disease (EVD), through the sheer size of the outbreak and combined experience within both resource-rich and resource-poor settings, allowed for more information to be gained about the clinical and pathologic features of EVD. This review highlights the range of aspects of EVD that the authors find are relevant to laboratory medicine, including the need for robust prediagnostic and laboratory processing algorithms to inform sampling of suspect patients, the vast majority of whom, in resource-rich settings, will have another diagnosis., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The Ebola virus disease (EVD) outbreak in West Africa was unprecedented in scale and location. Limited access to both diagnostic and supportive pathology assays in both resource-rich and resource-limited settings had a detrimental effect on the identification and isolation of cases as well as individual patient management. Limited access to such assays in resource-rich settings resulted in delays in differentiating EVD from other illnesses in returning travellers, in turn utilising valuable resources until a diagnosis could be made. This had a much greater impact in West Africa, where it contributed to the initial failure to contain the outbreak. This review explores diagnostic assays of use in EVD in both resource-rich and resource-limited settings, including their respective limitations, and some novel assays and approaches that may be of use in future outbreaks., Competing Interests: The authors have declared that no competing interests exist.

Background: The largest outbreak of isoniazid-resistant (INH-R) Mycobacterium tuberculosis in Western Europe is centred in North London, with over 400 cases diagnosed since 1995. In the current study, we evaluated the genetic variation in a subset of clinical samples from the outbreak with the hypothesis that these isolates have unique biological characteristics that have served to prolong the outbreak., Methods: Fitness assays, mutation rate estimation, and whole-genome sequencing were performed to test for selective advantage and compensatory mutations., Results: This detailed analysis of the genetic variation of these INH-R samples suggests that this outbreak consists of successful, closely related, circulating strains with heterogeneous resistance profiles and little or no associated fitness cost or impact on their mutation rate., Conclusions: Specific deletions and SNPs could be a peculiar feature of these INH-R M. tuberculosis isolates, and could potentially explain their persistence over the years.

As pathology services become more centralized and automated, the measurement of therapeutic antimicrobial drugs concentrations is increasingly performed in clinical biochemistry or 'blood science' laboratories. This review outlines key groups of antimicrobial agents: aminoglycosides, glycopeptides, antifungal agents and antituberculosis agents, their role in managing infectious diseases, and the reasons why serum concentration measurement is important., (© The Author(s) 2016.)

The rapid identification of antimicrobial resistance is essential for effective treatment of highly resistant Mycobacterium tuberculosis. Whole-genome sequencing provides comprehensive data on resistance mutations and strain typing for monitoring transmission, but unlike for conventional molecular tests, this has previously been achievable only from cultures of M. tuberculosis. Here we describe a method utilizing biotinylated RNA baits designed specifically for M. tuberculosis DNA to capture full M. tuberculosis genomes directly from infected sputum samples, allowing whole-genome sequencing without the requirement of culture. This was carried out on 24 smear-positive sputum samples, collected from the United Kingdom and Lithuania where a matched culture sample was available, and 2 samples that had failed to grow in culture. M. tuberculosis sequencing data were obtained directly from all 24 smear-positive culture-positive sputa, of which 20 were of high quality (>20× depth and >90% of the genome covered). Results were compared with those of conventional molecular and culture-based methods, and high levels of concordance between phenotypical resistance and predicted resistance based on genotype were observed. High-quality sequence data were obtained from one smear-positive culture-negative case. This study demonstrated for the first time the successful and accurate sequencing of M. tuberculosis genomes directly from uncultured sputa. Identification of known resistance mutations within a week of sample receipt offers the prospect for personalized rather than empirical treatment of drug-resistant tuberculosis, including the use of antimicrobial-sparing regimens, leading to improved outcomes., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

We describe an integrated person-specific standardized vulnerability assessment model designed to facilitate patient management in health and social care. Such a system is not meant to replace existing health and social assessment models but rather to complement them by providing a holistic picture of the vulnerabilities faced by a given patient. In fact, it should be seen as a screening tool for health and social care workers. One key aspect of the modeling framework is the ability to provide personalized yet standardized multi-dimensional assessments of risk based on incomplete information about the patient status, as is the case in screening situations. Specifically, we integrate a Markov chain model describing the evolution of patients in and out of vulnerable states over time with a Bayesian network that serves to customize the dynamic model. We present an application in the context of elder care.

We report a novel approach utilising a real-time PCR screening assay targeting a 53 bp tandemly repeated element present at various loci within the Mycobacterium tuberculosis (Mtb) genome. Positive samples were identified within a discriminatory melting curve range of 90-94°C, with results obtained in under one hour directly from decontaminated sputum samples without extraction. A panel of 89 smear-positive sputa were used for analytical validation of the assay with 100% concordance, with sensitivity matching that of culture. Cross reactivity was detected within a narrow range of mycobacteria other than tuberculosis (MOTT) (five sputa, three in silico), with the highest sensitivity within M. avium complex (MAC). A year-long head to head evaluation of the test with the GeneXpert platform was carried out with 104 consecutive samples at the Royal Free Hospital, UK. Receiver operating characteristics (ROC) analysis of the data revealed that the two tests are approximately equivalent in sensitivity, with the area under the curve being 0.85 and 0.80 for the GeneXpert and our assay, respectively, indicating that the test would be a cost effective screen prior to GeneXpert testing.

Background: Pleural infection is common, and has a >30% major morbidity and mortality-particularly when infection is caused by Gram-negative, Staphylococcus aureus or mixed aerobic pathogens. Standard pleural fluid culture is negative in ∼40% of cases. Culturing pleural fluid in blood culture bottles may increase microbial yield, and is cheap and easy to perform., Objectives: To determine whether inoculating pleural fluid into blood culture bottles increases the culture positivity of pleural infection over standard laboratory culture, and to assess the optimum volume of inoculum to introduce., Methods: 62 patients with pleural infection were enrolled. Pairs of aerobic and anaerobic blood culture bottles were inoculated at the bedside with 2, 5 or 10 ml of pleural fluid, and two pleural fluid specimens were sent for standard culture. Pleural fluid from nine control patients was cultured to test for 'false-positive' results., Results: The addition of blood culture bottle culture to standard culture increased the proportion of patients with identifiable pathogens by 20.8% (20/53 (37.7%) to 31/53 (58.5%) (difference 20.8%, 95% CI difference 8.9% to 20.8%, p<0.001)). The second standard culture did not similarly improve the culture positivity (19/49 (38.8%) to 22/49 (44.9%) (difference 6.1%, 95% CI difference -2.5% to 6.1%, p=0.08)). The culture inoculum volume did not influence bacterial isolation frequency. The control fluids were culture negative., Conclusions: Blood culture bottle culture of infected pleural fluid increases microbial yield when used in addition to standard culture. This technique should be part of routine care.