Acute care Post 1

Prof Gavin Murphy, Professor of Cardiac Surgery Mr Mustafa Zakkar, Associate Professor of Cardiac Surgery

Project Lead: Professor Gavin Murphy gjm19@le.ac.uk

Project 1) The effect of ethnicity on outcomes in cardiac surgery

Research Question/Aim: To compare the impact of ethnicity on treatment strategies (surgical/interventional/optimal medical therapy) and clinical outcomes in patients treated for coronary artery disease (CAD).

Background: The selection of the most appropriate treatment modalitiy for patient with CAD is based on internationally developed guidelines which takes into account the clinical and anatomical features of the coronary disease. However; guidelines and available risk scoring systems dont consider ethinic background as a factor when selecting the best management option. Literature suggests that there are disparities in access to appropriate diagnostic and interventional procedures based on race. Moreover; ethnic background seems to impact on long term survival after CABG. When looking closely at these studies, it is clear that they mostly relied on medical-claims data and the majority did not contain important clinical information needed or adjust for differences in the severity of disease. Most importantly, they reflect mainly the diverse population in USA which is widely different to the UK population. Furthermore; these studies could not determine the effect of differences in treatment on outcomes in patients.

The reasons behind the disparities in care is not clear and can be related to racial differences in clinical indications for procedures, access to care, patient preferences, and provider bias. Access to care and insurance can be a major factor in America but there remain the issue of presence of such disparity in the UK and the reasons and potential impact of such variations.

Objectives and Expected outputs: 1) Systematic review and meta-analysis of currently available data and analysis of Hospital Episodes Statistics (HES) data to investigate disparities in access to care based on ethnicity in patients admitted to NHS hospitals in England with cardiovascular diseases.

2) To work with all stakeholders, including patients/ relatives and care provider to understand reasons related to such differences.

3) To develop an early career researcher with MRC key skills in health data science biostatistics

Methods: The work will be carried out with collaboration with the BME center and Methods in meta-analysis and advanced statistics will be applied to NHS HES data. National surveys involving patients, relatives and health care providers will be developed to understand the impact of ethnic back ground on decision making with regards to referral for revascularization or agreeing to undergo revascularization.

Innovation: The project will provide detailed insight to disparities in access to revascularization focusing on the UK population with the collaboration with the BME center and the results will be highly informative to enable tackling misconceptions about treating ethnic minorities as well as providing better information to these groups that is tailored to their needs.

 

Project 2) In-silico trials in cardiac surgery

Research Question/Aim: In Silico analysis of Hospital Episodes Statistics (HES) data will be used to estimate key clinical trial parameters of patients admitted to NHS hospitals in England with cardiovascular diseases as defined by ICD10 I00-I99 from 2008/9 to 2017/18. The analysis conducted will be used to design, propose, optimise and evaluate the feasibility of new pragmatic trials to address key research priorities in cardiac surgery identified in a recent James Lind Alliance priority setting exercise; http://www.jla.nihr.ac.uk/priority-setting-partnerships/heart-surgery/.

Background: Successful delivery of clinical trials is limited by assumptions that are required for design and planning, such as recruitment, event rates and treatment effect sizes. In-silico modelling of trials as part of the design process may overcome some of these limitations.

Objectives and Expected outputs: 1) To develop a platform for in-silico trials using routinely collected health data. This project will contribute to a master protocol that will describe the methods, strengths and limitations of the in-silico approach.  2) To work with all stakeholders, including patients to integrate this work into a national trials programme in cardiac surgery. 3) To develop an early career researcher with MRC key skills in health data science, biostatistics and trial design, with the capacity to model novel trials of surgical interventions in-silico which will subsequently inform the design of key trials in adult cardiac surgery.

Methods: Methods in advanced statistics will be applied to NHS HES data. These analyses will inform the assumptions required for trial design and provide additional information on feasibility and generalisability. Statistical methods will be used to estimate the treatment effects of the trial intervention in the target population as well as in high-risk patient subgroups. Sensitivity analysis will be conducted to determine the optimal clinical trial design and the expected effects of bias in the analyses. These analyses will guide the efficient design of smart cost-effective novel pragmatic trials that address key research priorities in cardiac surgery identified in the Adult Cardiac Surgery Priority Setting Partnership.

Innovation: The use of routinely collected health care data in clinical trials is the subject of intense research, focusing on its ability to screen eligible patients, estimate patient recruitment, evaluate outcomes, and perform long term follow-up and surveillance. This project will be the first to combine these methods and use machine learning methods to estimate key trial parameters and optimise the design of clinical trials.

 

Project 3) Molecular phenotyping in cardiac surgery

Research Question/Aim: We will use UK Biobank data to identify the molecular phenotypes of frailty as part of a personalized medicine approach to the optimization of people referred for major surgery with specific emphasis on the improvement of longer-term post-surgery outcomes. This reflects the top two national research priorities identified in a recent James Lind Alliance priority setting exercise; http://www.jla.nihr.ac.uk/priority-setting-partnerships/heart-surgery/.

Background: Frailty is a condition of global impartment due to depletion of physiological reserves and overall disruption of homeostasis. Frail individuals are more vulnerable to stressors and even a minor health issue can have serious effects on the subject’s wellbeing, and even survival. This becomes especially problematic patients with frailty require surgical interventions. Frailty has been reported to affect anywhere between 10 – 54% of people referred for cardiac surgery. These patients are at a high risk of developing serious complications during or after the procedure and their survival rates are highly compromised. We suggest that characterization of the molecular phenotypes of frailty will facilitate to personalized interventions.

Using AI analyses of GEO datasets and multi-omics analyses of cardiac tissue biopsies obtained from previous clinical studies we have identified a number of pathways that we believe link chronic conditions, sarcopaenia, mitochondrial function, and adverse long-term outcomes. We now propose to assess how these factors interact with the frailty phenotype and frailty index measured in the UK Biobank population.

Objectives and Expected outputs:

1) To use multilevel models and AI to identify novel molecular phenotypes of frailty in UK Biobank

2) To validate these findings in an established local Bioresource.

3) To develop an early career researcher with MRC key skills in health data science, biostatistics and bioinformatics, who has an interest in precision medicine.

Methods: Methods in advanced statistics, AI, and bioinformatics will be applied to multilevel data; genotype telomere length, chronic disease, activity, demographics, activity, from UK Biobank. The aim will be to identify novel molecular phenotypes of frailty that in turn will be validated in an existing local bioresource.

Innovation: These analyses will provide new and unique insights into the molecular basis of frailty, support the development of a novel precision medicine approachs to perioperative care in people with frailty, and have findings generalisable across multiple areas of health research. This project will be the first to combine large scale genomic, genetic (telomere length) and clinical datasets, to understand the molecular basis of frailty.

 

Project 4) Iron metabolism in cardiac surgery

Research Question/Aim: We will use an experimental medicine approach to explore dysregulated iron metabolism as a molecular mechanism underlying accelerated sarcopaenia observed following cardiac surgery in frail patients, or following prolonged critical care stays. This research addresses the top two national research priorities identified in a recent James Lind Alliance priority setting exercise; http://www.jla.nihr.ac.uk/priority-setting-partnerships/heart-surgery/; improving long-term outcomes, and improving the management of people with frailty referred for surgery.

Background: Frailty is a condition of global impartment due to depletion of physiological reserves and overall disruption of homeostasis. Frail individuals are more vulnerable to stressors and even a minor health issue can have serious effects on the subject’s wellbeing, and even survival. This becomes especially problematic patients with frailty require surgical interventions. Frailty has been reported to affect anywhere between 10 – 54% of people referred for cardiac surgery. These patients are at a high risk of developing serious complications during or after the procedure and their survival rates are highly compromised. We suggest that characterization of the molecular phenotypes of frailty will facilitate to personalized interventions.

This project aims to measure global, cellular (cardiomyocyte, skeletal muscle) and mitochondrial iron metabolism in people referred for cardiac surgery with and without sarcopaenia at baseline. The findings will inform targeted analyses of existing bioresources, and if positive will lead to design of early phase trials of interventions targeting iron metabolism.

Objectives and Expected outputs:

1) To explore the role of dysregulated iron metabolism on the frailty phenotype.

2) To validate these findings in an established local and national Bioresources.

3) To develop an early career researcher with MRC key skills in health data science, clinical study design, biostatistics, and bioinformatics.

Methods: Global, cellular and mitochondrial iron metabolism will be measured in plasma, leucocytes, cardiomyocytes, and skeletal muscle biopsies obtained from the cohort of a prospective clinico-experimental study where sarcopaenia and frailty are quanified pre- and post-surgery. Iron metabolism will use targeted –omics techniques. Associations between measures of iron metabolism and sarcopaenia or frailty will be validated using existing local and national bioresources (UK Biobank).

Innovation: These analyses will provide new and unique insights into the molecular basis of frailty, support the development of a novel precision medicine approachs to perioperative care in people with frailty, and have findings generalisable across multiple areas of health research.

 

Project 5) Clinical trials in cardiac surgery

Research Question/Aim: We will use randomised clinical trials to evaluate the effects of pre-surgery interventions on longer-term outcomes following cardiovascular surgery. The target of the interventions will be chronic conditions including diabetes, chronic kidney disease and heart failure.  This research addresses three of the top 6 national research priorities identified in a recent James Lind Alliance priority setting exercise; http://www.jla.nihr.ac.uk/priority-setting-partnerships/heart-surgery/; improving long-term outcomes, and improving the management of people with frailty or with long-term chronic conditions referred for surgery.

Background: Baseline clinical status is the critical determinant of outcomes following surgery, accounting for 98% of variation in outcomes. The basis of these observations are complex due to the diverse pathology of chronic diseases. Importantly, they are not reflected in preclinical models commonly used to develop novel organ protection interventions. As a consequence, widely used interventions intended to optimise pre-surgery status lack efficacy. Multiple novel interventions have been shown to impact on the natural history of chronic diseases. It follows that these may also be effective at improving clinical outcomes following surgery in patients with chronic diseases. This project aims to evaluate several repurposed interventions using a platform precision medicine RCT design with linked ex-vivo tissue analyses.

Objectives and Expected outputs:

1) To evaluate repurposed medications for chronic diseases as organ protection strategies in people referred for cardiac surgery.

2) To link these findings to multi-omic phenotyping analyses of tissues and samples collected from trial patients.

3) To develop an early career researcher with MRC key skills in clinical trial design,  clinical study design and biostatistics.

Methods: A cohort multiple RCT design will be adopted. Repurposed medications will be evaluated based on precision medicine biomarkers identified by our exiting research. Trial results will be interpreted by linked multi-omics analyses of cardiomyocytes, plasma, and urine analyses obtained before, during and after surgery.

Innovation: These analyses will provide new and unique insights into the mechanisms linking chronic diseases with post-surgery organ injury and long-term outcomes and provide a platform for further clinico-experimental trials of organ protection strategies as well as evidence to support evaluation of promising therapeutics in later phase trials.

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