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Developing models to predict patient outcomes in children with severe illness

28 December 2020 | Story André Damons | Photo Supplied

A lecturer from the University of the Free State’s (UFS) department of Paediatrics and Child Health is investigating the use of artificial neural networks to develop models for the prediction of patient outcomes in children with severe illness.

Dr Michael Pienaar, senior lecturer and specialist, is conducting this research as part of his doctoral research and the study deals primarily with the development of models that are designed and calibrated for use in South Africa. These artificial neural networks are computer programs designed to mimic some of the learning characteristics of biological neurons.

The potential applications of models

According to Dr Pienaar these models have traditionally been developed in high-income nations using conventional statistical methods.

“The potential applications of such models in the clinical setting include triage, medical research, guidance of resource allocation and quality control. Having initially begun this research investigating the prediction of mortality outcomes in the paediatric intensive care unit (PICU) I have broadened my scope to patients outside of PICU, seeking to identify children early during their illnesses who are at risk of serious illness requiring PICU,” says Dr Pienaar.

The research up until now has been directed towards the identification of characteristics that are both unique to children with serious illness in South Africa, but also accessible to clinicians in settings where expertise and technical resources are limited.

Research still in the early changes

The research is still in its early stages but next year a series of expert review panels will be held to investigate the selection of variables for the model, after which the collection of clinical data will begin. Once the data has been collected and prepared, a number of candidate models will be developed and evaluated. This should be concluded by the end of 2022.

Says Dr Pienaar: “The need to engage with the rapid proliferation of technology, particularly in the realms of machine learning, mobile technology, automation and the Internet of Things is as great in medical research now as it is in any academic discipline.

“It is critical that research, particularly in South Africa, engage with this in order to take advantage of the opportunities offered and avoid the dangers that go paired with them. Together with the technology as such, it has been essential to pursue this project as an interdisciplinary undertaking involving clinicians, biostatisticians and computer engineers.”

Hope for the research

Dr Pienaar says he was very fortunate and grateful to be the recipient of a generous interdisciplinary grant from the UFS which has allowed him to procure software and equipment that is critical to this project.

“The hope for this research is that the best performing of these models can be integrated with a mobile application that assists practitioners in a wide range of settings in the identification, treatment and early referral of children at high risk of severe illness. I would like to expand this research project to include other countries in Africa and South America and to use it as a bridge to collaboration with other clinical researchers in the Global South,” says Dr Pienaar.

As an early career researcher, Dr Pienaar hopes that this research can serve as a platform to build a body of research that uses the rapid technological advances of these times together with a wide range of collaborations with other disciplines in the pursuit of better child health.

He concludes by saying that he has had excellent support thus far from his supervisors, Prof Stephen Brown (Faculty of Health Sciences, UFS), Dr Nicolaas Luwes (Faculty of Computer Science and Engineering, Central University of Technology) and Dr Elizabeth George (Medical Research Council Clinical Trials Unit, University College London). I have also been supported by the Robert Frater Institute in the Faculty of Health Sciences.

News Archive

Census 2011 overshadowed by vuvuzela announcements

2012-11-20

Mike Schüssler, economist
Photo: Hannes Pieterse
15 November 2012

Complete Lecture (MP3)

Census 2011 contains good statistics but these are overshadowed by vuvuzela announcements and a selective approach, economist Mike Schüssler said at a presentation at the UFS.

“Why highlight one inequality and not another success factor? Is Government that negative about itself?” Mr Schüssler, owner of Economist.co.za, asked.

“Why is all the good news such as home ownership, water, lights, cars, cellphones, etc. put on the back burner? For example, we have more rooms than people in our primary residence. Data shows that a third of Africans have a second home. Why are some statistics that are racially based not made available, e.g. orphans? So are “bad” statistics not always presented?”

He highlighted statistics that did not get the necessary attention in the media. One such statistic is that black South Africans earn 46% of all income compared to 39% of whites. The census also showed that black South Africans fully own nearly ten times the amount of houses that whites do. Another statistic is that black South Africans are the only population group to have a younger median age. “This is against worldwide trends and in all likelihood has to do with AIDS. It is killing black South Africans more than other race groups.”

Mr Schüssler also gave insight into education. He said education does count when earnings are taken into account. “I could easily say that the average degree earns nearly five times more than a matric and the average matric earns twice the pay of a grade 11.”

He also mentioned that people lie in surveys. On the expenditure side he said, “People apparently do not admit that they gamble or drink or smoke when asked. They also do not eat out but when looking at industry and sector sales, this is exposed and the CPI is, for example, reweighted. They forget their food expenditure and brag about their cars. They seemingly spend massively on houses but little on maintenance. They spend more than they earn.”

“On income, the lie is that people forget or do not know the difference between gross and net salaries. People forget garnishee orders, loan repayments and certainly do not have an idea what companies pay on their behalf to pensions and medical aid. People want to keep getting social grants so they are more motivated to forget income. People are scared of taxes too so they lower income when asked. They spend more than they earn in many categories.”

On household assets Mr Schüssler said South Africans are asset rich but income poor. Over 8,3 million black African families stay in brick or concrete houses out of a total of 11,2 million total. About 4,9 million black families own their own home fully while only 502 000 whites do (fully paid off or nearly ten times more black families own their own homes fully). Just over 880 000 black South Africans are paying off their homes while 518 000 white families are.

Other interesting statistics are that 13,2 million people work, 22,5 million have bank accounts, 19,6 million have credit records. Thirty percent of households have cars, 90% of households have cellphones and 80% of households have TVs.

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