Systematic reviews on the prognostic role of biomarkers in heart failure
People with heart failure often have to be admitted to hospital many times, to stabilise after severe episodes. Several different approaches to treatment may be tried, but finding the best treatment for each individual can be a process of trial-and-error. Biomarkers are proteins in the blood that can give us an indication of a person’s current condition. They might - in combination with other information - help us predict how the condition might react to different treatments. A number of ‘prognostic models’ for heart failure exist. These are mathematical models that combine different patient measurements to estimate what is likely to happen to their condition. Some of these models include levels of biomarkers in their calculations. This team will evaluate how good these models are at predicting the future health of heart failure patients, and if they are as accurate for all groups of patients. Their results will help doctors to decide which is the best prognostic model to use for each of their patients. This will help to get the right treatments to each person more quickly. The findings may well point to ways that prognostic models can be improved, and help doctors to understand what signs to watch out for in their patients.
Project details
| Grant amount | £144,806 |
|---|---|
| Grant type | Project Grants |
| Application type | Project Grant |
| Start Date | 01 January 2018 |
| Duration | 2 years |
| Reference | PG/17/49/33099 |
| Status | In Progress |
