Nosocomial Endocarditis Caused by Corynebacterium amycolatum and Other Nondiphtheriae Corynebacteria

The nondiphtheriae corynebacteria are uncommon but increasingly recognized as important agents of community-acquired endocarditis in patients with underlying structural heart disease, as well as of prosthetic-valve endocarditis. We describe three cases of nondiphtheriae corynebacterial endocarditis, including the first reported case of endocarditis caused by Corynebacterium amycolatum, occurring over an 18-month period, all in association with indwelling intravascular devices

The safe insertion of peripheral intravenous catheters : a mixed methods descriptive study of the availability of the equipment needed

Background: Intravenous cannulation is undertaken in a high proportion of hospitalised patients. Much international attention has been given to the use of care bundles to reduce the incidence of infection in these patients. However, less attention has been given to the systems required to ensure availability of the equipment needed to support these care bundles. Our objectives were to assess how reliably the equipment recommended for a peripheral intravenous care bundle was available for use, and to explore factors which contributed to its non-availability. Methods: We studied 350 peripheral cannula insertions in three NHS hospital organisations across the UK. Staff inserting cannulae were asked to report details of all equipment problems. Key staff were then interviewed to identify the causes of problems with equipment availability, using semi-structured qualitative interviews and a standard coding frame. Results: 47 equipment problems were recorded during 46 of 350 cannulations, corresponding to a reliability of 87%, or 94% if problems with sharps disposal were excluded. Overall reliability was similar in all three organisations, but the types of problem varied. Interviews revealed a variety of causes including issues associated with purchasing policies, storage facilities, and lack of teamwork and communication in relation to reordering. The many human factors related to the supply chain were highlighted. Often staff had adopted work-arounds to deal with these problems. Conclusions: Overall, 87% of cannulations had the correct and functional equipment available. Different problems were identified in different organisations, suggesting that each had resolved some issues. Supply chain management principles may be useful to support best practice in care bundle delivery. Keywords: Cannulation, Patient safety, Equipment, Care bundles, Hospital acquired bacteraemia, Systems reliabilit

Informing antimicrobial management in the context of COVID-19:Understanding the longitudinal dynamics of C-reactive protein and procalcitonin

Background: To characterise the longitudinal dynamics of C-reactive protein (CRP) and Procalcitonin (PCT) in a cohort of hospitalised patients with COVID-19 and support antimicrobial decision-making. Methods: Longitudinal CRP and PCT concentrations and trajectories of 237 hospitalised patients with COVID-19 were modelled. The dataset comprised of 2,021 data points for CRP and 284 points for PCT. Pairwise comparisons were performed between: (i) those with or without significant bacterial growth from cultures, and (ii) those who survived or died in hospital. Results: CRP concentrations were higher over time in COVID-19 patients with positive microbiology (day 9: 236 vs 123 mg/L, p < 0.0001) and in those who died (day 8: 226 vs 152 mg/L, p < 0.0001) but only after day 7 of COVID-related symptom onset. Failure for CRP to reduce in the first week of hospital admission was associated with significantly higher odds of death. PCT concentrations were higher in patients with COVID-19 and positive microbiology or in those who died, although these differences were not statistically significant. Conclusions: Both the absolute CRP concentration and the trajectory during the first week of hospital admission are important factors predicting microbiology culture positivity and outcome in patients hospitalised with COVID-19. Further work is needed to describe the role of PCT for co-infection. Understanding relationships of these biomarkers can support development of risk models and inform optimal antimicrobial strategies

Machine learning and synthetic outcome estimation for individualised antimicrobial cessation.

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

Validating a prediction tool to determine the risk of nosocomial multidrug-resistant Gram-negative bacilli infection in critically ill patients: A retrospective case–control study

BACKGROUND:The Singapore GSDCS score was developed to enable clinicians predict the risk of nosocomial multidrug-resistant Gram-negative bacilli (RGNB) infection in critically ill patients. We aimed to validate this score in a UK setting. METHOD:A retrospective case-control study was conducted including patients who stayed for more than 24h in intensive care units (ICUs) across two tertiary National Health Service hospitals in London, UK (April 2011-April 2016). Cases with RGNB and controls with sensitive Gram-negative bacilli (SGNB) infection were identified. RESULTS:The derived GSDCS score was calculated from when there was a step change in antimicrobial therapy in response to clinical suspicion of infection as follows: prior Gram-negative organism, Surgery, Dialysis with end-stage renal disease, prior Carbapenem use and intensive care Stay of more than 5 days. A total of 110 patients with RGNB infection (cases) were matched 1:1 to 110 geotemporally chosen patients with SGNB infection (controls). The discriminatory ability of the prediction tool by receiver operating characteristic curve analysis in our validation cohort was 0.75 (95% confidence interval 0.65-0.81), which is comparable with the area under the curve of the derivation cohort (0.77). The GSDCS score differentiated between low- (0-1.3), medium- (1.4-2.3) and high-risk (2.4-4.3) patients for RGNB infection (P<0.001) in a UK setting. CONCLUSION:A simple bedside clinical prediction tool may be used to identify and differentiate patients at low, medium and high risk of RGNB infection prior to initiation of prompt empirical antimicrobial therapy in the intensive care setting

Surveillance and Epidemiology of Drug Resistant Infections Consortium (SEDRIC): Supporting the transition from strategy to action.

In recognition of the central importance of surveillance and epidemiology in the control of antimicrobial resistance and the need to strengthen surveillance at all levels, Wellcome has brought together a new international expert group SEDRIC (Surveillance and Epidemiology of Drug Resistant Infections Consortium). SEDRIC aims to advance and transform the ways of tracking, sharing and analysing rates of infection and drug resistance, burden of disease, information on antibiotic use, opportunities for preventative measures such as vaccines, and contamination of the environment. SEDRIC will strengthen the availability of information needed to monitor and track risks, including an evaluation of access to, and utility of data generated by pharma and research activities, and will support the translation of surveillance data into interventions, changes in policy and more effective practices. Ways of working will include the provision of independent scientific analysis, advocacy and expert advice to groups, such as the Wellcome Drug Resistant Infection Priority Programme. A priority for SEDRIC's first Working Group is to review mechanisms to strengthen the generation, collection, collation and dissemination of high quality data, together with the need for creativity in the use of existing data and proxy measures, and linking to existing in-country networking infrastructure. SEDRIC will also promote the translation of technological innovations into public health solutions

Use of medical face masks versus particulate respirators as a component of personal protective equipment for health care workers in the context of the COVID-19 pandemic

Currently available evidence supports that the predominant route of human-to-human transmission of the SARS-CoV-2 is through respiratory droplets and/or contact routes. The report by the World Health Organization (WHO) Joint Mission on Coronavirus Disease 2019 (COVID-19) in China supports person-to-person droplet and fomite transmission during close unprotected contact with the vast majority of the investigated infection clusters occurring within families, with a household secondary attack rate varying between 3 and 10%, a finding that is not consistent with airborne transmission. The reproduction number (R0) for the SARS-CoV-2 is estimated to be between 2.2–2.7, compatible with other respiratory viruses associated with a droplet/contact mode of transmission and very different than an airborne virus like measles with a R0 widely cited to be between 12 and 18. Based on the scientific evidence accumulated to date, our view is that SARS-CoV-2 is not spread by the airborne route to any significant extent and the use of particulate respirators offers no advantage over medical masks as a component of personal protective equipment for the routine care of patients with COVID-19 in the health care setting. Moreover, prolonged use of particulate respirators may result in unintended harms. In conjunction with appropriate hand hygiene, personal protective equipment (PPE) used by health care workers caring for patients with COVID-19 must be used with attention to detail and precision of execution to prevent lapses in adherence and active failures in the donning and doffing of the PPE

The prevalence and incidence of mental ill-health in adults with autism and intellectual disabilities

The prevalence, and incidence, of mental ill-health in adults with intellectual disabilities and autism were compared with the whole population with intellectual disabilities, and with controls, matched individually for age, gender, ability-level, and Down syndrome. Although the adults with autism had a higher point prevalence of problem behaviours compared with the whole adult population with intellectual disabilities, compared with individually matched controls there was no difference in prevalence, or incidence of either problem behaviours or other mental ill-health. Adults with autism who had problem behaviours were less likely to recover over a two-year period than were their matched controls. Apparent differences in rates of mental ill-health are accounted for by factors other than autism, including Down syndrome and ability level