GABAA/benzodiazepine receptor distribution and subunit mRNA expression in human temporal lobe epilepsy

The GABAA/central benzodiazepine receptor (cBZR) complex is a major inhibitory receptor in the vertebrate CNS. A functional impairment of GABAergic inhibition has been proposed as one mechanism which may underlie increased seizure susceptibility in human temporal lobe epilepsy (TLE). The objective of this study was to characterise abnormalities of the GABAA/cBZR in TLE with a correlative autoradiography, in-situ hybridisation, immunohistochemistry and quantitative neuropathology study. Hippocampal tissue was obtained at surgery from patients with intractable TLE due to hippocampal sclerosis (HS) and autopsies of neurologically normal controls. Neuronal densities were obtained using a 3-D counting method in paraffin-embedded sections. Saturation autoradiographic studies were performed on cryostat sections using [3H]-flumazenil and expression of mRNA encoding the α1-α6, β3 and γ2 subunits of the GABAA receptor was assessed using in-situ hybridisation histochemistry. Distribution of the receptor protein was also determined using immunohistochemistry with antibodies to the GABAA α1 and β2/3 subunits. A significant decrease in central benzodiazepine binding sites was demonstrated in all subfields of the human hippocampus in HS. This loss of cBZR binding sites would appear to be due primarily to changes in neuronal density characteristic of this pathology. However, in the CA 1 subfield, a reduced BZ receptor concentration was evident on surviving neurones in the HS group (p<0.05). Expression of mRNA encoding GABAA receptor subunits α1, α2, α4, α5, and γ2, was upregulated in surviving neurones of the granule cell layer of the dentate gyrus in HS. In addition, epilepsy-associated increases in the expression of mRNA encoding the α1 subunit were observed in the hilus and CA2 and α2 mRNA in the hilus and CA1. In contrast, an apparent decrease in expression of β3 mRNA per neurone was detected in CA1 in HS (p<0.07) and of γ2 in the CA2 in HS (p<0.10). These findings imply a functional abnormality of the GABAA/CBZR complex that may have a role in the pathophysiology of epileptogenicity in HS

Isolation and purification of recombinant immunoglobulin light chain variable domains from the periplasmic space of Escherichia coli

Immunoglobulin light chain amyloidosis is the most common form of systemic amyloidosis. However, very little is known about the underlying mechanisms that initiate and modulate the associated protein aggregation and deposition. Model systems have been established to investigate these disease-associated processes. One of these systems comprises two 114 amino acid light-chain variable domains of the kappa 4 IgG family, SMA and LEN. Despite high sequence identity (93%), SMA is amyloidogenic in vivo, but LEN adopts a stable dimer, displaying amyloidogenic properties only under destabilising conditions in vitro. We present here a refined and reproducible periplasmic expression and purification protocol for SMA and LEN that improves on existing methods and provides high yields of pure protein (10-50mg/L), particularly suitable for structural studies that demand highly concentrated and purified proteins. We confirm that recombinant SMA and LEN proteins have structure and dimerization capabilities consistent with the native proteins and employ fluorescence to probe internalization and cellular localization within cardiomyocytes. We propose periplasmic expression and simplified chromatographic steps outlined here as an optimized method for production of these and other variable light chain domains to investigate the underlying mechanisms of light chain amyloidosis. We show that SMA and LEN can be internalised within cardiomyocytes and were observed to localise to the perinuclear area, assessed by confocal microscopy as a possible mechanism for underlying cytotoxicity and pathogenesis associated with amyloidosis

Risk of emergency hospital admission related to adverse events after antibiotic treatment in adults with a common infection: impact of COVID-19 and derivation and validation of risk prediction models

Background: With the global challenge of antimicrobial resistance intensified during the COVID-19 pandemic, evaluating adverse events (AEs) post-antibiotic treatment for common infections is crucial. This study aims to examines the changes in incidence rates of AEs during the COVID-19 pandemic and predict AE risk following antibiotic prescriptions for common infections, considering their previous antibiotic exposure and other long-term clinical conditions. Methods: With the approval of NHS England, we used OpenSAFELY platform and analysed electronic health records from patients aged 18–110, prescribed antibiotics for urinary tract infection (UTI), lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), sinusitis, otitis externa, and otitis media between January 2019 and June 2023. We evaluated the temporal trends in the incidence rate of AEs for each infection, analysing monthly changes over time. The survival probability of emergency AE hospitalisation was estimated in each COVID-19 period (period 1: 1 January 2019 to 25 March 2020, period 2: 26 March 2020 to 8 March 2021, period 3: 9 March 2021 to 30 June 2023) using the Kaplan–Meier approach. Prognostic models, using Cox proportional hazards regression, were developed and validated to predict AE risk within 30 days post-prescription using the records in Period 1. Results: Out of 9.4 million patients who received antibiotics, 0.6% of UTI, 0.3% of URTI, and 0.5% of LRTI patients experienced AEs. UTI and LRTI patients demonstrated a higher risk of AEs, with a noted increase in AE incidence during the COVID-19 pandemic. Higher comorbidity and recent antibiotic use emerged as significant AE predictors. The developed models exhibited good calibration and discrimination, especially for UTIs and LRTIs, with a C-statistic above 0.70. Conclusions: The study reveals a variable incidence of AEs post-antibiotic treatment for common infections, with UTI and LRTI patients facing higher risks. AE risks varied between infections and COVID-19 periods. These findings underscore the necessity for cautious antibiotic prescribing and call for further exploration into the intricate dynamics between antibiotic use, AEs, and the pandemic

Exploring Prior Antibiotic Exposure Characteristics for COVID-19 Hospital Admission Patients: OpenSAFELY

Previous studies have demonstrated the association between antibiotic use and severe COVID-19 outcomes. This study aimed to explore detailed antibiotic exposure characteristics among COVID-19 patients. Using the OpenSAFELY platform, which integrates extensive health data and covers 40% of the population in England, the study analysed 3.16 million COVID-19 patients with at least two prior antibiotic prescriptions. These patients were compared to up to six matched controls without hospitalisation records. A machine learning model categorised patients into ten groups based on their antibiotic exposure history over the three years before their COVID-19 diagnosis. The study found that for COVID-19 patients, the total number of prior antibiotic prescriptions, diversity of antibiotic types, broad-spectrum antibiotic prescriptions, time between first and last antibiotics, and recent antibiotic use were associated with an increased risk of severe COVID-19 outcomes. Patients in the highest decile of antibiotic exposure had an adjusted odds ratio of 4.8 for severe outcomes compared to those in the lowest decile. These findings suggest a potential link between extensive antibiotic use and the risk of severe COVID-19. This highlights the need for more judicious antibiotic prescribing in primary care, primarily for patients with higher risks of infection-related complications, which may better offset the potential adverse effects of repeated antibiotic use

Evaluating the role of Primary Care Pharmacy Technicians in Antimicrobial Stewardship (AMS) and Acne Management using TARGET resources

Background: Inappropriate antibiotic prescribing is accelerating antimicrobial resistance (AMR)(1). Pharmacy professionals (Pharmacists and Pharmacy Technicians) promote good antibiotic prescribing practice. The traditional role of pharmacy technicians in supporting pharmacists and patients has expanded alongside the clinical expansion of pharmacist roles(2). This paper focuses on the opinion of pharmacy technicians and their role in the review of acne management and the evaluation of the UKHSA TARGET ‘How to review acne’ resources.Aims:To explore the impact of the TARGET resources on the capability, opportunity and motivation of pharmacy technicians in general practice in managing patients with acne, to evaluate the usefulness of the ‘How to review acne’ resources.Methods:A quantitative study using an electronic survey asking UK-based pharmacy technicians to rate their agreement on a 5-point Likert scale with 21 predefined statements, themed on the COM-B model and usefulness of the specific TARGET resources for acne.Findings:The survey found that capability and opportunity in managing acne in the group familiar with TARGET resources was higher than the group not familiar with TARGET resources. Scores for motivation in both groups were high; pharmacy technicians have the motivation to undertake infection management roles, whether or not they are familiar with the TARGET toolkit. The toolkit ‘How to review acne’ resources were overall rated as useful in supporting the review of patients with acne.Conclusion:The TARGET toolkit is an effective resource that helps to upskill pharmacy technicians in the area of AMS, increasing capability and opportunity in the management of acne

Adaptation of the WHO Essential Medicines List for national antibiotic stewardship policy in England: being AWaRe.

OBJECTIVES:Appropriate use of and access to antimicrobials are key priorities of global strategies to combat antimicrobial resistance (AMR). The WHO recently classified key antibiotics into three categories (AWaRe) to improve access (Access), monitor important antibiotics (Watch) and preserve effectiveness of 'last resort' antibiotics (Reserve). This classification was assessed for antibiotic stewardship and quality improvement in English hospitals. METHODS:Using an expert elicitation exercise, antibiotics used in England but not included in the WHO AWaRe index were added to an appropriate category following a workshop consensus exercise with national experts. The methodology was tested using national antibiotic prescribing data and presented by primary and secondary care. RESULTS:In 2016, 46/108 antibiotics included within the WHO AWaRe index were routinely used in England and an additional 25 antibiotics also commonly used in England were not included in the WHO AWaRe index. WHO AWaRe-excluded and -included antibiotics were reviewed and reclassified according to the England-adapted AWaRE index with the justification by experts for each addition or alteration. Applying the England-adapted AWaRe index, Access antibiotics accounted for the majority (60.9%) of prescribing, followed by Watch (37.9%) and Reserve (0.8%); 0.4% of antibiotics remained unclassified. There was unexplained 2-fold variation in prescribing between hospitals within each AWaRe category, highlighting the potential for quality improvement. CONCLUSIONS:We have adapted the WHO AWaRe index to create a specific index for England. The AWaRe index provides high-level understanding of antibiotic prescribing. Subsequent to this process the England AWaRe index is now embedded into national antibiotic stewardship policy and incentivized quality improvement schemes

Electronic prescribing system design priorities for antimicrobial stewardship: a cross-sectional survey of 142 UK infection specialists.

The implementation of electronic prescribing and medication administration (EPMA) systems is a priority for hospitals and a potential component of antimicrobial stewardship (AMS).Accepted manuscript, 12 month embarg

Impact of COVID-19 on broad-spectrum antibiotic prescribing for common infections in primary care in England: a time-series analyses using OpenSAFELY and effects of predictors including deprivation.

BACKGROUND: The COVID-19 pandemic impacted the healthcare systems, adding extra pressure to reduce antimicrobial resistance. Therefore, we aimed to evaluate changes in antibiotic prescription patterns after COVID-19 started. METHODS: With the approval of NHS England, we used the OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system in primary care and selected patients prescribed antibiotics from 2019 to 2021. To evaluate the impact of COVID-19 on broad-spectrum antibiotic prescribing, we evaluated prescribing rates and its predictors and used interrupted time series analysis by fitting binomial logistic regression models. FINDINGS: Over 32 million antibiotic prescriptions were extracted over the study period; 8.7% were broad-spectrum. The study showed increases in broad-spectrum antibiotic prescribing (odds ratio [OR] 1.37; 95% confidence interval [CI] 1.36-1.38) as an immediate impact of the pandemic, followed by a gradual recovery with a 1.1-1.2% decrease in odds of broad-spectrum prescription per month. The same pattern was found within subgroups defined by age, sex, region, ethnicity, and socioeconomic deprivation quintiles. More deprived patients were more likely to receive broad-spectrum antibiotics, which differences remained stable over time. The most significant increase in broad-spectrum prescribing was observed for lower respiratory tract infection (OR 2.33; 95% CI 2.1-2.50) and otitis media (OR 1.96; 95% CI 1.80-2.13). INTERPRETATION: An immediate reduction in antibiotic prescribing and an increase in the proportion of broad-spectrum antibiotic prescribing in primary care was observed. The trends recovered to pre-pandemic levels, but the consequence of the COVID-19 pandemic on AMR needs further investigation. FUNDING: This work was supported by Health Data Research UK and by National Institute for Health Research

The impact of COVID-19 on antibiotic prescribing in primary care in England: Evaluation and risk prediction of appropriateness of type and repeat prescribing.

BACKGROUND: This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19. METHODS: With the approval of NHS England, we used OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted patient's probability of receiving inappropriate antibiotic type or repeat antibiotic course for each common infection. RESULTS: The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%) and 8.6% had potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the 10 risk prediction models, good levels of calibration and moderate levels of discrimination were found. CONCLUSIONS: Our study found no evidence of changes in level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information

Measuring appropriate antibiotic prescribing in acute hospitals: Development of a national audit tool through a Delphi consensus

This study developed a patient-level audit tool to assess the appropriateness of antibiotic prescribing in acute National Health Service (NHS) hospitals in the UK. A modified Delphi process was used to evaluate variables identified from published literature that could be used to support an assessment of appropriateness of antibiotic use. At a national workshop, 22 infection experts reached a consensus to define appropriate prescribing and agree upon an initial draft audit tool. Following this, a national multidisciplinary panel of 19 infection experts, of whom only one was part of the workshop, was convened to evaluate and validate variables using questionnaires to confirm the relevance of each variable in assessing appropriate prescribing. The initial evidence synthesis of published literature identified 25 variables that could be used to support an assessment of appropriateness of antibiotic use. All the panel members reviewed the variables for the first round of the Delphi; the panel accepted 23 out of 25 variables. Following review by the project team, one of the two rejected variables was rephrased, and the second neutral variable was re-scored. The panel accepted both these variables in round two with a 68% response rate. Accepted variables were used to develop an audit tool to determine the extent of appropriateness of antibiotic prescribing at the individual patient level in acute NHS hospitals through infection expert consensus based on the results of a Delphi process