Machine Learning for acute kidney injury in COVID 19
Covid-19 is a new, highly contagious disease, and there are no established protocols for treatment.
Around one third of patients hospitalised with COVID-19 have significant injury to their kidneys. Many will go on to require temporary dialysis and some will require lifelong kidney therapy. We currently have very limited understanding of how, why, and when the kidneys are injured during infection with COVID-19, and no proven strategies to prevent the condition. In many resource poor countries, the availability of kidney treatments like dialysis is limited and therefore rationing is required.
The ISARIC Acute Kidney Injury Analysis is an observational study collecting hospital data from 64 countries around the world. In collaboration with Oxford University, the UQ data team led by Dr Sally Shrapnel aims to
- Characterise acute kidney injury in COVID
- Develop a predictive algorithm to identify patients at high risk of kidney injury
- Validate and deploy this algorithm in a resource poor setting (Latin America)
