A recent study by an international consortium revealed the positive influence of an Omega-3 rich diet in in the prevention of cardiovascular diseases. More than 26,000 women participated in the international project, run in collaboration between the Pere Virgili Health Research Institute (IISPV), the Rovira i Virgili University (URV) and the Harvard Medical School. The study’s conclusions are relevant because cardiovascular diseases are the most prevalent cause of death, with 1 in 3 people dying from these events.
Up to now it had been shown that the consumption of Omega-3 fatty acids was associated with lower levels of triglycerides, a type of fat, in the blood. However, its high consumption is also associated with a rise in low-density cholesterol, also known as bad cholesterol. This type of cholesterol is one of the main risk factors for cardiovascular diseases by accelerating the formation of atherosclerosis, the process by which the arteries stiffen and lose their elasticity.
The research has been led by Dr. Núria Amigó, CEO of the spin off Biosfer Teslab and member of the Metabolomics Interdisciplinary Laboratory – Metabolomics Platform. The Metabolomics Platform is a joint research unit of the URV and the IISPV. Prof. Xavier Correig, from the Department of Electronic, Electrical and Automatic Engineering and Director of the Metabolomics Platform, has participated in this study along with the researchers from the Center for Lipid Metabolomics, Division of Preventive Medicine at the Brigham and Women’s Hospital (Harvard Medical School).
Dr. Núria Amigó highlights that this study goes beyond the previous results, owing to the use of a specialized technique – Nuclear Magnetic Resonance, provided by the Metabolomics Platform. She noted that “The Nuclear Magnetic Resonance technique goes further than simply analysing triglyceride and cholesterol content and can quantify the number and size of the different subtypes of lipoprotein“.
RETINOPROGRAM is a 10-year collaboration between Dr Pere Romero-Avoca (Director of Ophtamology clinic at University Hospital San Joan de Reus) and Prof Domenech Puig (Head of ITAKA, URV) research groups, resulting in several publications and 4 registered softwares. Our access to clinical expertise and patients meant that our tools were awarded a fast track to innovation program (Innobics) to be adopted in the Catalonia ICS hospitals (accessible to all doctors through EHR database).
Under the IISPV umbrella, both groups have joined efforts work in the diagnosis and prevention of Diabetic Retinopathy (DR). Despite being the fifth cause of blindness and visual impairment (and most common one in working age adults), there is no stratification method based on their risk to develop DR. Furthermore, existing treatments can only stop progression and DR is asymptomatic in its early stages. Prevention plays also a key role in DR development as it can be prevented by controlling some risk factors as glycemia or arterial hypertension.
Researchers from both groups are working on a tool that 1) stratify patients based on their risk of developing DR, 2) calculates their next screening appointment based on the calculated risk, and 3) offers prevention interventions for patients to self-manage their risk. This tool would be the merging of ourexisting and validated sof twares (through EyePACS and general population data):
DR Deep Learning Algorithm (DLA) that stratifies patients in 4 levels of severity and sets up their next appointment
based on the resulting risk level.
What distinguishes their work from existing companies in the market (IDx and EyeArt) is our access to patients and clinical expertise. Thus, existing companies work with DLA but they don’t take into account the associated clinical risk factors for DR and consequently, cannot provide personalised prevention and treatment plans. In addition, our product has been validated by EyePACS, MESSIDOR-2 and retinographies from the general population (107.977 patients for COSS and 18.792 patients for DLA), whilst our competitors have reached the market by only validating their models with EyePACS and/or MESSIDOR.
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