Diabetes prevention in psychiatric patients

Inspiration

In this study, https://pubmed.ncbi.nlm.nih.gov/18286870/ , it was concluded that improved efforts are needed in the somatic care of patients with bipolar disorder and schizophrenia who are taking antipsychotics, given that they typically have moderate-to-high risk for metabolic diseases. Antipsychotics are associated with metabolic side effects like:

Overweight/obesity
Diabetes
Dyslipidemia Evidence Based Clinical practice recommends timely assessment and management of these conditions.

What it does

Reduce the burden of follow-up doctoral appointments and future diabetic appointments due to medical complications. For this we:

Track the glucose levels of non-diabetic patients
Monitor their risk of developing diabetes
Customize blood testing schedule and reminders
Customize recommendations for improvements in health

How we built it

We used Flutter to build and integrate the app and MATLAB to code the algorithm that assesses the risk of developing diabetes, with the use of journals and reputable sources.

Challenges we ran into

The assessment of the risk of diabetes is very complicated, because there are many factors that play a role in it. There was a lack of time to implement all the features that we would have liked to and to make the design more aesthetic.

Accomplishments that we're proud of

We created an app that can work in a small window of time and created a code that assesses risk of diabetes by taking into account 13 risk factors. We also aim to bring a light on this serious topic that affect a community that is often ignored (psychiatric patients).

What we learned

The risk of developing diabetes is very complex. Many factors need to be taken into account, especially when medication is involved. This requires a heavy monitoring of patients at risk and it supposes a big burden on medical appointments and attention from healthcare professionals.

What's next for Diabetes prevention in psychiatric patients

Ideally, there should be a study to more accurately assess the risk of diabetes and set adequate thresholds. In the future, the features of this app could be increased to monitoring specific patterns of their food intakes, exercise frequency and such, to make it more personalized.