Dr Trish Gilholm

Data Scientist

Child Health Research Centre
Faculty of Medicine

Overview

Qualifications

  • Masters Degree, Utrecht University
  • Bachelor of Psychological Science (Honours), The University of Queensland
  • Doctor of Philosophy, Queensland University of Technology

Publications

  • Long, Debbie A., Gilholm, Patricia, Le Brocque, Robyne, Kenardy, Justin, Gibbons, Kristen and Dow, Belinda L. (2023). Post-traumatic stress and health-related quality of life after admission to paediatric intensive care: Longitudinal associations in mother–child dyads. Australian Critical Care, 37 (1), 98-105. doi: 10.1016/j.aucc.2023.10.004

  • Gilholm, Patricia, Ergetu, Endrias, Gelbart, Ben, Raman, Sainath, Festa, Marino, Schlapbach, Luregn J., Long, Debbie, Gibbons, Kristen S. and on behalf of the Australian and New Zealand Intensive Care Society Paediatric Study Group (2023). Adaptive clinical trials in pediatric critical care: a systematic review. Pediatric Critical Care Medicine, 24 (9), 738-749. doi: 10.1097/pcc.0000000000003273

  • Gilholm, Patricia, Gibbons, Kristen, Brüningk, Sarah, Klatt, Juliane, Vaithianathan, Rhema, Long, Debbie, Millar, Johnny, Tomaszewski, Wojtek, Schlapbach, Luregn J., Ganeshalingam, Anusha, Sherring, Claire, Erickson, Simon, Barr, Samantha, Raman, Sainath, Long, Debbie, Schlapbach, Luregn, Gibbons, Kristen, George, Shane, Singh, Puneet, Smith, Vicky, Butt, Warwick, Delzoppo, Carmel, Millar, Johnny, Gelbart, Ben, Oberender, Felix, Ganu, Subodh, Letton, Georgia, Festa, Marino, Harper, Gail and the Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcomes & Resource Evaluation (CORE) and ANZICS Paediatric Study Group (ANZICS PSG) (2023). Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study. Intensive Care Medicine, 49 (7), 785-795. doi: 10.1007/s00134-023-07137-1

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Available Projects

  • This project aims to explore the barriers and facilitators to implementation of adaptive trial designs, a more flexible approach to clinical trials, in paediatric critical care. Traditional randomised controlled trials (RCTs) can be time-consuming and require a large number of patients, but adaptive designs offer a more efficient and cost-effective alternative. However, despite these benefits, only a small percentage of paediatric critical care trials have adopted adaptive designs. For this project, a survey and interviews with trialists will be conducted to identify the barriers and facilitators to using adaptive designs in this field, with the goal of understanding how to successfully implement these innovative trial approaches.

  • 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.

  • 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.

View all Available Projects

Publications

Journal Article

Conference Publication

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • This project aims to explore the barriers and facilitators to implementation of adaptive trial designs, a more flexible approach to clinical trials, in paediatric critical care. Traditional randomised controlled trials (RCTs) can be time-consuming and require a large number of patients, but adaptive designs offer a more efficient and cost-effective alternative. However, despite these benefits, only a small percentage of paediatric critical care trials have adopted adaptive designs. For this project, a survey and interviews with trialists will be conducted to identify the barriers and facilitators to using adaptive designs in this field, with the goal of understanding how to successfully implement these innovative trial approaches.

  • 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.

  • 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.