AAGBI/Anaesthesia Research Grants

The successful applicants for the AAGBI/Anaesthesia Research Grant were:

Principal Applicant
Dr Sheila Black
Leeds Teaching Hospital NHS Trust

Prospective, open label, single site pilot study to assess the effects of Spinal Cord Stimulation on autonomic function in patients with failed back surgery syndrome


Scientific Abstract

Failed Back Surgery Syndrome (FBSS) is a chronic painful condition resulting in persistent back and/or leg pain following spinal surgery. The National Institute of Clinical Excellence recommends spinal cord stimulation (SCS) as a treatment for FBSS. In our institution, we achieve around 85% successful trial of implantation of SCS for this condition. In order to predict those patients who would be most likely to benefit, we are investigating the autonomic function of these patients before and after SCS implantation.

This is a prospective single-centre pilot study. Ten participants will be recruited. We will measure autonomic activity before and 6 months after SCS implantation, including Heart Rate Variability, Baroreceptor sensitivity, and Muscle Sympathetic Nerve Activity using microneurography.

Microneurography has not yet been studied in patients with FBSS, so this study aims to establish the extent of sympathetic activation in these patients prior to SCS implantation. We will compare autonomic activity before and after SCS implant.

The implication of this study is the potential ability to predict which patients are responders or non-responders of SCS therapy. This will improve clinical outcome by targeting those most likely to benefit from SCS therapy, and increase patient safety by avoiding unnecessary procedures.

Principal Applicant
Dr Emma Fitzgerald
Portsmouth Hospital

Cefoxitin resistance as a marker of AmpC beta-lactamase production: Clinical significance in the Intensive Care Unit


Scientific Abstract

Antimicrobial resistance is a serious and growing global health threat, with resistance patterns in gram-negative organisms being particularly important in ICU. A predominant mechanism for resistance to β-lactam antibiotics in gram-negative bacteria is mediated by AmpC beta lactamase. This has been associated with clinical antimicrobial treatment failure, but is not identified by conventional sensitivity testing. Testing for in vitro Cefoxitin resistance is reported as being a reliable way to detect AmpC gene presence.

To establish whether presence of cefoxitin resistance leads to greater treatment failure in critically ill patients who have a coliform isolated from their non-bronchoscopic lavage (NBL) sample.

Blinded retrospective review of microbiological and clinical data collected from all ICU patients in 2013 who had a coliform isolated in their NBL sample and who were on appropriate antibiotics according to sensitivities.

Statistical analysis to identify any relationship between cefoxitin resistance and treatment success or failure (primary end-point), ICU / hospital length of stay, ICU / hospital mortality (secondary end-points).

Potential Impact
If cefoxitin resistance is clinically significant, then microbiological testing for it is important and should be conducted routinely on every NBL sample to minimise antibiotic resistance and improve treatment success and patient outcome.

Principal Applicant
Dr Ramani Moonesinghe
University College London

EPICS: EPIdemiology of Critical care after Surgery: version 2


Scientific Abstract
EPICS will describe the epidemiology of critical care referral and admission after inpatient surgery in the UK, and will estimate the clinical effectiveness of planned postoperative critical care admission as an intervention to reduce postoperative mortality.

EPICS will be a prospective observational cohort study. Prospective data will be collected by perioperative anaesthetists on all patients undergoing inpatient surgery in participating UK hospitals for one week. The dataset will include patient risk factors, and questions about clinical decision making and resource availability related to critical care referral and admission. Additionally, an organizational questionnaire for each hospital will be completed to describe structure and process in those institutions, and critical care unit occupancy at regular time-intervals throughout the one-week data collection period.

The descriptive epidemiology of critical care referral and admission patterns will be reported. The accuracy (discrimination) of previously validated risk prediction tools for postoperative mortality will be compared with clinical judgment using receiver-operator-characteristic curves. Regression analyses will determine independent predictive factors for postoperative critical care admission. Propensity score matching and Instrumental variable (IV) analysis will be used to determine the clinical effectiveness of planned critical care admission on length of hospital stay, 90 day and one-year mortality.