Josh Knowles

TL;DR

Big data is being used to diagnose and flag patients with familial hypercholesterolemia, a condition that leads to high risk of early onset heart disease.

Transcript

I'm here with Josh Knowles who is an assistant professor in the cardiology department and he does some really interesting research on familial hypercholesterolemia which sounds like a mouthful but actually is really applicable so tell us a little bit about your research yes so I'm really interested in familial hypercholesterolemia but we just call ... Read More

Key Insights

• 🥰 Familial hypercholesterolemia (FH) is a condition that puts individuals at high risk of early onset heart disease due to the body's inability to recycle bad cholesterol.
• 🛟 Early diagnosis and treatment of FH can significantly improve the lifespan and quality of life for patients.
• 😃 Big data, through a national patient registry and machine learning, is being used to gather insights and identify undiagnosed FH patients.
• 🥺 Patient-led charitable organizations play a crucial role in driving research and empowering individuals to advocate for their own healthcare.
• 😃 The use of big data in FH research has the potential to save thousands of lives by identifying at-risk patients and enabling timely interventions.
• 🥰 FH is often undiagnosed until individuals experience a heart attack or sudden death.
• 😃 The implementation of big data techniques, similar to spam filters, aids in identifying previously undiagnosed FH patients.

Questions & Answers

Q: What is familial hypercholesterolemia (FH) and how does it affect individuals?

FH is a condition that prevents the body from recycling bad cholesterol, resulting in high cholesterol levels and increased risk of early heart disease. It predominantly affects families, with individuals unaware of their condition until they experience a heart attack or sudden death.

Q: How is big data being used in FH research?

Big data is being utilized in two ways. Firstly, a national patient registry allows patients to register their own data, providing insights into diagnosis timelines, medication usage, and challenges faced. Secondly, machine learning techniques are being used to identify undiagnosed FH patients by creating a profile based on known positive cases and finding similar patients.

Q: What is the significance of diagnosing and flagging FH patients?

Early diagnosis of FH is crucial in preventing early onset heart disease. By flagging potential FH patients, healthcare providers can take a closer look and implement appropriate interventions, reducing the risk of heart attacks and saving lives.

Q: How is big data research in FH being driven by patient-led charitable organizations?

The FH Foundation, led and founded by patients, is spearheading big data research in FH. This patient-led approach empowers individuals to take control of their healthcare and ensures that research aligns with the needs and experiences of those affected by FH.

Summary & Key Takeaways

• Familial hypercholesterolemia (FH) is a condition where the body is unable to recycle bad cholesterol, leading to high levels in the blood and increased risk of heart disease.

• Most people with FH are unaware of their condition until they experience a heart attack or sudden death.

• Big data is being utilized through a national patient registry and machine learning techniques to identify undiagnosed FH patients and empower patients to advocate for their own healthcare.