Bristol team establishes no ‘one size fits all’ treatment for diabetes
Examining glucose levels, researchers from Bristol University have discovered unexpected patterns in insulins needs are just as common as well-established ones.
Yesterday, Wednesday 27th November, a new study was published in JMIRx Med which revealed that automatic insulin delivery systems could be missing vital information when it comes to helping people with Type 1 Diabetes.
Type 1 diabetes is a chronic condition in which the body produces too little insulin, a hormone needed to regulate blood glucose. There is currently no cure for the illness but taking insulin daily and monitoring food and drink intake – particularly carbs – helps manage it. However, experts from the University of Bristol have discovered that other factors beyond carbohydrates, including exercise, hormones and stress can impact glucose levels but current automated insulin delivery systems haven’t been programmed to factor these in.
To conduct the research experts looked at data from patients who use OpenAPS, a state-of-the-art automated insulin delivery system.
Lead author Isabella Degen from Bristol’s Faculty of Science and Engineering explained: ‘The results support our hypothesis that factors beyond carbohydrates play a substantial role in euglycemia – the state when blood glucose levels are within the standard range.
‘However, without measurable information about these factors, AID systems are left to adjust insulin cautiously with the effect of blood glucose levels becoming too low or high.’
In order for elements such as stress and hormone changes to be included in clinical practise, the study claims scientists need to find a way to measure their impact and utilise the information in insulin-dosing. What’s more, researchers also remarked that this technique could also aid more accurate blood glucose forecasting, which the study showed is not consistently possible.
‘Our study highlights that managing Type 1 Diabetes is far more complex than counting carbs,’ Isabella said. ‘The richness of insights that can be gained from studying automated insulin delivery data is worth the effort it takes to work with this type of real-life data.’
Isabella added: ‘What surprised us most was the sheer variety of patterns we observed, even within our relatively small and homogenous group of participants.
‘It’s clear that when it comes to diabetes management, one size doesn’t fit all.’
Following the publication of this study, the team are now working on advancing time series pattern-finding methods that can handle constant changes in medical data, including irregular hormone changes and spikes in stress levels.
To read more about the study, it can be accessed in full here.
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