Student research project
Supervisor(s): Dr Julian Sacre and Professor Jonathan Shaw
This research project is part of a larger epidemiological study led by the Baker Institute — the Progression of Diabetic Complications (PREDICT) study. PREDICT is aiming to develop ways of identifying those people with type 2 diabetes who are at risk of developing diabetic complications (e.g. heart or eye problems).
One of the complications of diabetes that can eventually lead to major illness and/or death is kidney disease. Obviously it is desirable to detect kidney disease in its early stages so that preventative strategies can be put in place to try to slow its progression. Markers of early-stage kidney disease can indeed be obtained from blood and urine samples, and this is part of current practice for the PREDICT study. However, these markers have been known to exhibit day-to-day variability, and while some of this can be attributed to technical reasons (differences in sample processing etc), there may also be biological factors that play a role. Whatever the reasons, it presents a problem for detecting kidney disease because measurement of a single sample may return a result in the normal range, when in reality the individual has early-stage kidney disease (or vice versa).
The main purpose of this project is therefore two-fold:
- To examine the day-to-day reproducibility of markers of kidney damage in people with type 2 diabetes.
- To determine the impact of reproducibility (or lack thereof) on diagnostic outcomes (i.e. how many samples are required to make an accurate diagnosis?).
Applicants should have an interest in data analysis and epidemiology (experience in or prior knowledge of the types of sample analyses described above is not required). In addition to data analysis, you would have the opportunity to be involved in data collection and other aspects of clinical research.
This project is suitable for an Honours student and will involve applying various skills and techniques, including conducting systematic reviews, statistics and epidemiology.
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