Impact of antibiotic timing on mortality from Gram-negative bacteraemia in an English district general hospital: the importance of getting it right every time.

OBJECTIVES: There is limited evidence that empirical antimicrobials affect patient-oriented outcomes in Gram-negative bacteraemia. We aimed to establish the impact of effective antibiotics at four consecutive timepoints on 30 day all-cause mortality and length of stay in hospital. METHODS: We performed a multivariable survival analysis on 789 patients with Escherichia coli, Klebsiella spp. and Pseudomonas aeruginosa bacteraemias. Antibiotic choices at the time of the blood culture (BC), the time of medical clerking and 24 and 48 h post-BC were reviewed. RESULTS: Patients that received ineffective empirical antibiotics at the time of the BC had higher risk of mortality before 30 days (HR = 1.68, 95% CI = 1.19-2.38, P = 0.004). Mortality was higher if an ineffective antimicrobial was continued by the clerking doctor (HR = 2.73, 95% CI = 1.58-4.73, P < 0.001) or at 24 h from the BC (HR = 1.83, 95% CI = 1.05-3.20, P = 0.033) when compared with patients who received effective therapy throughout. Hospital-onset infections, 'high inoculum' infections and elevated C-reactive protein, lactate and Charlson comorbidity index were independent predictors of mortality. Effective initial antibiotics did not statistically significantly reduce length of stay in hospital (-2.98 days, 95% CI = -6.08-0.11, P = 0.058). The primary reasons for incorrect treatment were in vitro antimicrobial resistance (48.6%), initial misdiagnosis of infection source (22.7%) and non-adherence to hospital guidelines (15.7%). CONCLUSIONS: Consecutive prescribing decisions affect mortality from Gram-negative bacteraemia.

Mid-regional proadrenomedullin (MR-proADM), C-reactive protein (CRP) and other biomarkers in the early identification of disease progression in patients with COVID-19 in the acute NHS setting.

AIMS: There is a lack of biomarkers validated for assessing clinical deterioration in patients with COVID-19 on presentation to secondary or tertiary care. This evaluation looked at the potential clinical application of C reactive protein (CRP), procalcitonin, mid-regional proadrenomedullin (MR-proADM) and white cell count to support prediction of clinical outcomes. METHODS: 135 patients presenting to Hampshire Hospitals NHS Foundation Trust between April and June 2020 confirmed to have COVID-19 via reverse-transcription-qPCR were included. Biomarkers from within 24 hours of presentation were used to predict disease progression by Cox regression and area under the receiver operating characteristic curves. The endpoints assessed were 30-day all-cause mortality, intubation and ventilation, critical care admission and non-invasive ventilation (NIV) use. RESULTS: Elevated MR-proADM was shown to have the greatest ability to predict 30-day mortality adjusting for age, cardiovascular disease, renal disease and neurological disease. A significant association was also noted between raised MR-proADM and CRP concentrations and the requirement for critical care admission and NIV. CONCLUSIONS: The measurement of MR-proADM and CRP in patients with confirmed COVID-19 infection on admission shows significant potential to support clinicians in identifying those at increased risk of disease progression and need for higher level care, subsequently enabling prompt escalation in clinical interventions.

Exploring the views of infection consultants in England on a novel delinked funding model for antimicrobials: the SMASH study.

Objectives: A novel 'subscription-type' funding model was launched in England in July 2022 for ceftazidime/avibactam and cefiderocol. We explored the views of infection consultants on important aspects of the delinked antimicrobial funding model. Methods: An online survey was sent to all infection consultants in NHS acute hospitals in England. Results: The response rate was 31.2% (235/753). Most consultants agreed the model is a welcome development (69.8%, 164/235), will improve treatment of drug-resistant infections (68.5%, 161/235) and will stimulate research and development of new antimicrobials (57.9%, 136/235). Consultants disagreed that the model would lead to reduced carbapenem use and reported increased use of cefiderocol post-implementation. The presence of an antimicrobial pharmacy team, requirement for preauthorization by infection specialists, antimicrobial stewardship ward rounds and education of infection specialists were considered the most effective antimicrobial stewardship interventions. Under the new model, 42.1% (99/235) of consultants would use these antimicrobials empirically, if risk factors for antimicrobial resistance were present (previous infection, colonization, treatment failure with carbapenems, ward outbreak, recent admission to a high-prevalence setting).Significantly higher insurance and diversity values were given to model antimicrobials compared with established treatments for carbapenem-resistant infections, while meropenem recorded the highest enablement value. Use of both 'subscription-type' model drugs for a wide range of infection sites was reported. Respondents prioritized ceftazidime/avibactam for infections by bacteria producing OXA-48 and KPC and cefiderocol for those producing MBLs and infections with Stenotrophomonas maltophilia, Acinetobacter spp. and Burkholderia cepacia. Conclusions: The 'subscription-type' model was viewed favourably by infection consultants in England.

Antibiotic review kit for hospitals (ARK-Hospital): a stepped-wedge cluster-randomised controlled trial.

BACKGROUND: Strategies to reduce antibiotic overuse in hospitals depend on prescribers taking decisions to stop unnecessary antibiotic use. There is scarce evidence for how to support these decisions. We evaluated a multifaceted behaviour change intervention (ie, the antibiotic review kit) designed to reduce antibiotic use among adult acute general medical inpatients by increasing appropriate decisions to stop antibiotics at clinical review. METHODS: We performed a stepped-wedge, cluster (hospital)-randomised controlled trial using computer-generated sequence randomisation of eligible hospitals in seven calendar-time blocks in the UK. Hospitals were eligible for inclusion if they admitted adult non-elective general or medical inpatients, had a local representative to champion the intervention, and could provide the required study data. Hospital clusters were randomised to an implementation date occurring at 1-2 week intervals, and the date was concealed until 12 weeks before implementation, when local preparations were designed to start. The intervention effect was assessed using data from pseudonymised routine electronic health records, ward-level antibiotic dispensing, Clostridioides difficile tests, prescription audits, and an implementation process evaluation. Co-primary outcomes were monthly antibiotic defined daily doses per adult acute general medical admission (hospital-level, superiority) and all-cause mortality within 30 days of admission (patient level, non-inferiority margin of 5%). Outcomes were assessed in the modified intention-to-treat population (ie, excluding sites that withdrew before implementation). Intervention effects were assessed by use of interrupted time series analyses within each site, estimating overall effects through random-effects meta-analysis, with heterogeneity across prespecified potential modifiers assessed by use of meta-regression. This trial is completed and is registered with ISRCTN, ISRCTN12674243. FINDINGS: 58 hospital organisations expressed an interest in participating. Three pilot sites implemented the intervention between Sept 25 and Nov 20, 2017. 43 further sites were randomised to implement the intervention between Feb 12, 2018, and July 1, 2019, and seven sites withdrew before implementation. 39 sites were followed up for at least 14 months. Adjusted estimates showed reductions in total antibiotic defined daily doses per acute general medical admission (-4·8% per year, 95% CI -9·1 to -0·2) following the intervention. Among 7 160 421 acute general medical admissions, the ARK intervention was associated with an immediate change of -2·7% (95% CI -5·7 to 0·3) and sustained change of 3·0% (-0·1 to 6·2) in adjusted 30-day mortality. INTERPRETATION: The antibiotic review kit intervention resulted in sustained reductions in antibiotic use among adult acute general medical inpatients. The weak, inconsistent intervention effects on mortality are probably explained by the onset of the COVID-19 pandemic. Hospitals should use the antibiotic review kit to reduce antibiotic overuse. FUNDING: UK National Institute for Health and Care Research.

Long-term outcome and risk factors for late mortality in Gram-negative bacteraemia: a retrospective cohort study.

OBJECTIVES: The long-term outcomes of patients following Gram-negative bacteraemia (GNB) are poorly understood. Here we describe a cohort of patients with GNB over a 2-year period and determine factors associated with late mortality (death between Days 31 and 365 after detection of bacteraemia). METHODS: This was a single-centre, retrospective, observational cohort study of 789 patients with confirmed Escherichia coli, Klebsiella spp. or Pseudomonas aeruginosa bacteraemia with a follow-up of 1 year. Multivariable survival analysis was used to determine risk factors for late mortality in patients who survived the initial 30-day period of infection. RESULTS: Overall, 1-year all-cause mortality was 36.2%, with 18.1% of patients dying within 30 days and 18.1% of patients suffering late mortality. An adverse antimicrobial resistance profile [hazard ratio (HR) = 1.095 per any additional antimicrobial category, 95% confidence interval (CI) 1.018-1.178; P = 0.014] and infection with P. aeruginosa (HR = 2.08, 95% CI 1.11-3.88; P = 0.022) were independent predictors of late mortality. Other significant factors included Charlson comorbidity index and length of hospitalisation after the index blood culture. CONCLUSION: Patients with GNB have a poor long-term prognosis. Risk factors for greater mortality at 1 year include co-morbidity, length of hospitalisation, and infecting organism and its resistance profile.