ANI |
Updated: December 13, 2020 4:59 PM IST
Washington (USA), December 13 (ANI): During a recent study conducted at the University of Vermont and Cedars-Sinai, collaborating researchers using routine blood tests were able to obtain high precision in predicting the probability of Covid-19 infection.
The study published in the Journal of Medical Internet Research is also available online. Describes the performance of Biocogniv’s new AI-COVID software, which can help hospitals reduce the number of patients referred for rare PCR tests.
Lead author and assistant professor at the University of Vermont, Timothy Plante, MD, MHS, said: “Nine months after this pandemic, we now have a better understanding of how to care for Covid-19 patients.”
He further said, “but there is still a big bottleneck in diagnosing Covid-19 with PCR testing.”
The PCR test is the current standard diagnosis for Covid-19 and requires specific sampling, such as a nasal swab and specialized laboratory equipment to run.
Biocogniv COO Tanya Kanigan, PhD, said: “Based on data from more than 100 US hospitals, the national average response time for Covid-19 tests requested in emergency rooms is superior. to 24 hours, far from the expected response time of one hour. “
Complete blood count and complete metabolic panels are common laboratory tests requested by emergency departments and have a quick turnaround time. These tests provide information about the immune system, electrolytes, kidneys, and liver.
The researchers were able to train a model that analyzes the changes in these routine tests and assigns a probability that the patient is negative for Covid-19 with high precision.
“AI-Covid takes a few seconds to generate its informative result once these blood tests return, which can then be incorporated by the laboratory into its own interpretation of the test,” said Jennifer Joe, MD, an emergency physician in Boston, Massachusetts and Chief Medical Officer of Biocogniv. Official.
“In an efficient emergency department that prioritizes these routine blood tests, the door-to-result time could be less than an hour,” added Joe.
Cedars-Sinai pulmonary and internal medicine specialist Victor Tapson, MD, says these assistive tools that help doctors rule out possible diagnoses are familiar in emergency medicine.
Tapson said: “For example, a low-D-dimer blood test can help us rule out clots in certain patients, allowing providers to skip expensive and often time-consuming diagnoses such as chest CT scans.” .
The Biocogniv team believes that a secondary benefit of labs incorporating AI-Covid could be the reduced time for traditional PCR results.
“With the help of AI-Covid, labs could alleviate some of the testing bottlenecks by helping providers better allocate rapid PCR tests to patients who really need them,” Joe said.
The AI-Covid model was validated with real-world data from Cedars-Sinai, as well as data from geographically and demographically diverse patient encounters from 22 U.S. hospitals, achieving an area under the curve (or AUC) of 0 , 91 over 1.00.
“This allows the model to achieve a high sensitivity of 95 percent while maintaining a moderate specificity of 49 percent, which is very similar to the performance of other commonly used discard tests,” said Biocogniv Scientific Director George Hauser, MD, a pathologist.
“I am honored to have such an impressive team of University of Vermont and Cedars-Sinai medical scientists as collaborators that invalidate this timely model,” said Biocogniv CEO Artur Adib, PhD.
Adib added: “AI has made considerable progress; now is the time to harness this powerful tool for further advancements in healthcare, and we are pleased to direct it to help laboratories and hospital providers combat the current Covid-19 crisis.” . (AND ME)