Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

The research focuses on developing and validating a non-invasive point of care test for coronary artery disease or CAD. We're trying to address how to acquire the physiological signals in a manner that's streamlined for both the clinician and the patient, as well as techniques for evaluating the test result and how the overall approach compares to traditional diagnostics in terms of efficacy and cost. The challenges are optimizing the signal acquisition, developing machine learned algorithms to ensure performance across varying clinical scenarios and understanding the test effectiveness in real world settings.

The test offers a non-invasive stress-free diagnostic alternative that is cost effective, requires no capital investment in equipment or specialized personnel, and is accessible in diverse clinical settings, including those with limited resources. Our findings will advance research by providing a validated non-invasive diagnostic tool that can be integrated into standard clinical practice, potentially reducing the burden of CAD globally through earlier detection and treatment. Cardiovascular point of care testing in our current era of access to care is very, very important.

Cause so often patients travel from long distances because of the dirge of cardiovascular providers. They often have to travel a long ways to see a provider and it's often very good if the provider at that time could do some testing in the office that can minimize future or several visits. So I think in the long run, in the short term I should say, point of care testing can increase the time to diagnosis either for testing or not testing, because based on the results of the point of care, can determine if further testing is needed.

I think the Core Vista point of care system can one, help us in those patients that present often with what we consider atypical chest pain, especially in females, because females can present atypically and indeed have disease. And so the Core Vista system can help you increase the probability of disease or increase or decrease the probability of disease that can lead to further testing, whether it's further invasive testing or further non-invasive testing. And what I think this can do in the long run is help with the cost of care.

And the other thing about the point of care Core Vista system, I think, as I said, sometimes patients travel a long distance, and so now we talk about access to care with the current access to care and access to a point of care system that can also speed up testing in patients. Future research will focus on further refine the test, exploring further applications such as pulmonary hypertension, as well as investing in the long-term impact of early CED detection on patient outcomes and healthcare systems globally. To begin position the patient flat on their back in a comfortable resting position.

Connect the leads to electrodes and place the hemodynamic photo plethysmogram sensor on the subject's index finger. After entering patient details, place the device on a flat surface. Check the leads and press start to commence the signal acquisition.

After acquiring a good quality signal, detach the electrodes from the patient and clean the device. Access the portal to view the test results and analyze them. To begin, acquire good quality signals from the patient in the coronary artery disease point of care test using orthogonal voltage gradient and photolithography sensors.

For result interpretation, first, compare the CAD score to zero to determine whether the patient's test is positive or negative. If the score is greater than or equal to zero, the patient's result is test positive. If the score is less than zero, the result is test negative.

Read the CAD score value from the report and compare it to the distributions of negative and positive patients in the validation cohort of the report. Increase the granularity of the test positive and test negative results using the ranges of the CAD score observed in the population to validate the test, specifically division into tertiles. Alternatively, perform a pre-test to post-test probability mapping using the patient's CAD score.

In a 67-year-old male patient, the initial CAD probability of 84%increased to a post-test probability of 94%after testing, justifying invasive cardiac catheterization. In another case, a 39-year-old woman's initial CAD probability of 28%decreased to a post-test probability of 4%after testing ruling out coronary artery disease. A 74-year-old woman's initial CAD probability of 24%increased to a post-test probability of 33%after testing leading to a PET scan recommendation.