Children’s Intensive Care Research Program student projects

Sepsis is a dangerous condition in children caused by the body's response to infection, which can lead to organ problems and even death if not treated quickly. Children who survive sepsis may face ongoing educational difficulties, such as trouble learning, cognitive issues, and struggles in school. To better understand the long-term effects, this project will use data from a 20-year period, linking information about sepsis survivors in paediatric intensive care units (PICU) with standardised educational assessments in Queensland. The results will help inform support programs for this vulnerable group, ensuring they receive the necessary help to succeed in their education.

Project type: Masters

Contact: Dr Trish Gilholm

Our team has developed a machine learning model to predict poor school outcomes in children who survived the intensive care unit (ICU). We used data from over 13,000 childhood ICU survivors in Queensland, Australia, over a 22-year period. The model showed promising results with an ability to predict school performance based on data available at the time of ICU discharge, which could help prioritise patients for follow-up care and target rehabilitation efforts. However, most children who are admitted to ICU are admitted prior to school-age, which limited our ability to assess more immediate effects of ICU admission on children’s educational performance. This project will focus on the school performance of school aged PICU survivors, and will assess the change in educational performance before and after a PICU admission.

Project type: Masters

Contact: Dr Trish Gilholm

Extracorporeal Life Support (ECLS) is an advanced form of life support utilised in the care of patients with severe cardiac and pulmonary dysfunction Unfortunately, patients on ECLS are at a higher risk of nosocomial infections than the general intensive care patient. These can significantly morbidity and mortality. Early diagnosis of nosocomial infection in ECMO patients is difficult. Although surveillance cultures are routinely utilized to identify infections, there is a dearth of evidence supporting this practice and are unlikely to be cost-effective. Additionally, the use of biomarkers for detection have demonstrated conflicting results. This project involves the development of a more robust screening criteria in order to detect infections in a timely manner.

Project type: Honours / Masters

Contact: Dr Sai Raman

The diagnostic value of biomarkers in sepsis can only be realised if the results are available to clinicians in a timely way. Currently, many regional and remote facilities in Queensland do not have the on-site laboratory capabilities to accommodate this need. C-reactive protein (CRP) can be measured at the point of care (POC) using the TGA-approved Abbott Afinion CRP assay. We implemented a POC CRP device in Ayr, Charters Towers, Ingham (Townsville HHS), Cooktown and Weipa (Torres and Cape HHS) Emergency Departments (ED). This pilot demonstrated that the POC CRP device is acceptable to clinicians and the use is sustainable. The follow-up project involves the implementation of the POC CRP device across >56 sites with the aim of delivering safe and responsive care to priority populations living in regional, rural and remote areas. The student will undertake the evaluation of the implementation.

Project type: Masters / PhD

Contact: Dr Sai Raman

Health in-equity is unfortunately still prevalent in Australia. One of the key seps to address this problem is describe the burden of the problem. With this current project, we aim to investigate impact of SE status on health outcomes. The project will source data from Australia New Zealand Paediatric Intensive Care Registry, the Office of National Statistics and the Statistical Services Branch. The student will be mentored to source data, analyse the data, and write a manuscript.

Project type: Honours

Contact: Dr Sai Raman

Currently, critically ill children on the paediatric intensive care receive blood transfusion when their blood haemoglobin level drops below 70 gms/L. Children with certain cardiac conditions are administered blood at a level of 100 gms/L. While there is some evidence in the general paediatric intensive care cohort that these thresholds are safe, no clear evidence exists in patients supported on Extracorporeal Life Support. In this project, the student will perform a retrospective cohort study to investigate outcomes based on haemoglobin cut-offs in children placed on ECMO.

Project type: Honours

Contact: Dr Sai Raman

Critically ill children on the paediatric intensive care unit routine receive blood test and Chest X-rays every morning. While majority of these are clinically indicated, it is unclear what proportion of these change management. Using ML techniques, in this project, we aim to develop a clinical decision-making tool that will guide junior doctors to order clinical investigations appropriately. Additionally, we will explore the HE cost efficiency of such an approach. Furthermore, we will cross validate a similar project that is underway in the PICUs in the US.

Project type: Masters

Contact: Dr Sai Raman

Recent evidence suggests early mobility on intensive could augment recovery from severe critical illness. To apply an intervention directed at this facet of intensive care, we need to first observe and document the range of movements that children have on intensive care. In the novel observational study, we will be placing accelerometers (like smart watches) on children’s arms during their stay on PICU. We will then describe the interactions of severity of illness, intensive care procedures and mobility. The follow-up study would incorporate ‘liberation’ principles with an intervention directed at early mobility.

Project type: Masters / PhD

Contact: Dr Sai Raman

Unfortunately, children suffer cardiac arrest due to various reasons before being admitted to intensive care or whilst on PICU. There are some consensus guidelines on how to manage and support these children after return of spontaneous circulation. An international collaborative (Pedi-ResQ) has generated tools and dashboards to assist PICUs to benchmark their practice and improve care delivered to this sick cohort of children. The Queensland Children’s Hospital joined this collaborative earlier this year. We will implement a bundle of care that will include intra-arrest and post arrest goal directed care. This proposed study will have two components 1) a description and evaluation of the implementation of the bundle of care and 2) Objective quantitative analysis of outcomes of children post-cardiac arrest. The second project will be a pre-post cohort study design.

Project type: Masters

Contact: Dr Sai Raman

Our group described the epidemiology sepsis in children admitted to PICUs across ANZ about 10 years ago. Since then, there have been implementation of quality improvement programs in several states directed at early sepsis recognition and management. Now, we aim to explore if there has been any change in the patterns of sepsis presentation and outcomes. Others studies that the student could be part of are around delivery intravenous antibiotic therapy. In this program of research, we are investigating therapeutic drug monitoring, Bayesian forecasting, duration of antibiotic infusion and dosing on extracorporeal life support.

Project type: Masters / PhD

Contact: Dr Sai Raman

In a life-threatening situation when urgent life-saving care in an intensive care unit (ICU) is required, any delay to receiving treatment may increase the likelihood of a poor clinical outcome. In such instances, obtaining prospective informed consent for research from substitute decision makers for adult patients, and the families/carers of a paediatric patient, is challenging. This can lead to suboptimal research participation with acutely ill patients being deprived of the opportunity to benefit from new treatments.

It is largely unknown if a) delayed consent is acceptable to patients, families, and carers, b) clinicians and researchers feel adequately trained to undertake this approach, and c) HRECs have a thorough understanding of how to review projects with this consent approach. This project aims to:

1. Understand the perceptions of a broad range of stakeholders involved in consenting practices in an ICU.
2. Explore how demographic, social and/or clinical factors of patients, carers, families, clinicians researchers and HREC members, influenced satisfaction with the consent approach.

Develop responsive, sensitive, consenting materials that optimise research practices in health research after engaging in meaningful co-design with consumers, clinicians and HREC members.

Project type: Masters

Contact: Associate Professor Kristen Gibbons

The importance of ensuring the consumer voice is sought, respected, and included in the research lifecycle has been globally recognised. Involving patients and families in research design enhances the quality, appropriateness, acceptability and relevance to patients and their families. Despite wide acceptance of these benefits, there is limited published accounts of patient and family engagement within the PICU context. Recently, the key ANZ PICU research priorities were defined, incorporating only doctors and nurses’ views. Similarly, an international exercise to propose a global PICU clinical research agenda did not engage consumers. The most important and meaningful research questions for PICU families need to be identified and prioritised.

This project will:

1. Identify and prioritise outcomes, clinical cohorts, and treatments, important to PICU children and families.
2. Identify barriers and enablers to innovative trial and precision medicine study designs in PICU research.
3. Develop a prioritised PICU research agenda co-designed by consumers, clinicians, and researchers.

Project type: Masters

Contact: Associate Professor Kristen Gibbons

Precision medicine tailors therapies for an individual by taking into account the underlying heterogeneity in a population. Many models have been developed, but translation has only been successful in few disciplines. To date, the scarce precision medicine models in paediatric critical care have been limited by small sample sizes, lack of external validation and have not been trialled in clinical practice. However, PICU is optimised for precision medicine due to the large quantity of biomarkers measured, widespread implementation of electronic health records (EHRs), and extensive digitised physiological monitoring. Machine learning models derived from these granular, high-quality PICU datasets, coupled with omics data, will explain the biological heterogeneity. The models will identify children who are more likely to benefit from certain interventions and establish personalised care pathways for consumer-prioritised outcomes. Using the extensive, highly curated databank from the NITRIC clinical trial (largest international trial of infants undergoing heart surgery) and the follow-up study, and the RAPIDS observational cohort investigating better identification of children with sepsis, as sandpits to develop models to establish personalised trajectories, this project will:

1. Derive and validate phenotypes to quantify the heterogeneity of the patient cohort (including infants undergoing heart surgery, and septic patients).
2. Develop prediction models for prioritised short- and long-term outcomes incorporating clinical and omics data.

Project type: Multiple Masters / PhD

Contact: Associate Professor Kristen Gibbons

Tailoring medical treatments to account for a patient’s individual variability is the future of healthcare. Clinical trials have demonstrated that such “precision medicine” approaches can improve clinical outcomes for patients. Recently, breakthroughs in the application of computational science in healthcare have shown the promise of using computer algorithms on health data to assist in clinical decision-making. For the most critically unwell children admitted to hospital, there is a lack of high-quality research for the treatments they receive—the sickest children are often excluded from high quality trials, and thus may not receive treatments that are optimal for them. A large amount of health-related data is generated within paediatric intensive care units (PICUs) but, to date, this data has not been fully utilised. Using extensive, high-resolution data from >32,500 patient admissions across three large PICUs (Brisbane, Melbourne, and Zurich), this project will use advanced machine learning techniques to develop a model to assist clinicians to detect deterioration of a child’s condition early so that they can intervene early. This will result in the right treatments being delivered at the right time — reducing mortality, decreasing neurodevelopmental complications, and ultimately increasing quality of life for children admitted to intensive care.

Project type: Masters/ PhD

Contact: Associate Professor Kristen Gibbons

There is a paucity of high-quality trials to inform the life-saving care of children admitted to PICU. >75% of all PICU trials have ≤100 participants, >80% only recruit from a single centre and only 3% have used an innovative trial design, severely hampering the delivery of robust and generalisable results. The COVID-19 pandemic highlighted the need for agile trial infrastructure and international networks to rapidly generate gold-standard, personalised evidence to inform practice. Adult intensive care researchers demonstrated the feasibility of such an approach in a critical care setting, enrolling thousands of patients into global interventional trials using innovative designs. These learnings need to be translated to the paediatric setting to trial precision medicine approaches in a robust, efficient manner, delivering best care for children. This project will lay the foundations for translating a machine-learning model into clinical practice. Components of the project will include undertaking a systematic review, developing and deploying silent models into clinical care, and collecting and evaluating stakeholder feedback in relation to implementation of such models, and, using implementation science, designing best practice tools to promote the highest level of successful model translation.

Project type: Masters / PhD

Contact: Associate Professor Kristen Gibbons

Sepsis, defined as life-threatening organ dysfunction caused by dysregulated host response to infection, affects an estimated 48.9 million cases every year. Sepsis is not only a leading cause of global mortality, but can result in long-term morbidity related to physical, cognitive, and psychosocial sequelae. This translates into a major health and economic burden to societies. In 2017, the World Health Organisation (WHO) declared sepsis a global health priority. The WHO resolution stated an urgent need to implement measures for the prevention, diagnosis, management, and follow-up support of sepsis. This project will use existing MRFF and NHMRC funded cohorts to identify and explore patterns of responses to long-term follow-up assessments and questionnaires from children and families after an intensive care admission, co-design with stakeholders enhanced methods for conducting long-term follow-up, and implement such strategies through a prospective project.

Project type: Masters / PhD

Contact: Associate Professor Kristen Gibbons

Sepsis develops when the body starts to attack its own tissues and organs in response to the infection resulting in organ dysfunction, multi-organ failure and death if not identified and treated promptly. Our group utilises several genomic approaches to identify biomarkers to improve sepsis diagnosis. This project will utilise latest genomic technologies such as long-read direct RNA sequencing and single-cell RNA sequencing to discover novel biomarkers for sepsis and to understand the biological mechanisms involved in sepsis, to diagnose and treat patients promptly. This project will provide experience in bioinformatics tools for genomic analysis and provide opportunities to work in clinical research setting with clinicians and researchers involved in paediatric care. 

Project type: Honours / Masters / PhD

Contact: Dr Devika Ganesamoorthy