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Saturday, October 24, 2020
Home Professions Hospital Admin Can AI Predict Outcomes in COVID-19 Patients?

Can AI Predict Outcomes in COVID-19 Patients?

Since the start of the COVID-19 pandemic, clinical researchers have been rushing to discover new drugs and therapies, novel uses for old drugs, as well as other strategies for combating COVID-19. At the same, a silent partner has been quietly churning away in the background: artificial intelligence (AI). No longer relegated to the sidelines, AI technology is driving new applications to improve COVID-19 planning, treatment, and outcomes, especially on pandemic frontlines.

Early detection helps preserve frontline resources

Early detection and diagnosis of COVID-19 infections ranks as one of the most important (and timely) uses for AI technology, according to a recent review in Diabetes & Metabolic Syndrome Journal, with currently available AI platform options ranging from enhanced chest tomography imaging to AI-guided cardiac ultrasound

Until now, COVID-19 diagnosis has largely relied upon commercially available diagnostic platforms that use molecular detection as a framework. Still, gaps remain with respect to identifying patients with high mortality risk or with low risk for complications, both which can impact resource utilization. To address these gaps, New York University researchers created an app that uses AI to help assess patient risk factors (e.g. age, sex) and key serum biomarkers (e.g. C-reactive protein, myoglobin, procalcitonin [PCT], and cardiac troponin), all important drivers of COVID-19 complications and mortality. These data are then fed into a statistical learning algorithm — the COVID-19 Severity Score — to predict mortality; scores range from 0 (mild to moderate) to 100 (critical).

Writing in a study published in ‘Lab on a Chip’ journal, the researchers explain that they first developed the COVID-19 Disease Severity model based on data from 160 hospitalized Wuhan Chinese patients. Findings showed that males accounted for 70% of deaths, and had significantly higher biomarker levels (were significantly older) than patients who were discharged. These data were then validated in 12 hospitalized Shenzhen, Chinese patients, with results showing significantly higher median COVID-19 Severity Scores in patients who died vs those who were discharged. 

What’s next?

Preliminary data from a general New York City patient population demonstrates that there are other biomarkers that might help discern patients at greatest risk for severe COVID-19 illness  (e.g. D-dimer for thrombotic events or PCT for bacterial co-infections). Additional research efforts are needed to evaluate others that also drive serious manifestations, such as cytokine storms. Meanwhile, the study’s lead investigator John McDevitt, PhD, says that plans to develop and scale the app for point-of-care serum testing are underway. Future work may also involve a test for population-based COVID-19 surveillance in clinical or public settings, with the goal of supporting healthcare workers on the frontlines tasked with rapidly diagnosing and triaging patients needing the most care. 

References

Artificial Intelligence (AI) Applications for COVID-19 Pandemic. Diabetes & Metabolic Syndrome.

AI COVID-19. An algorithm developed in a collaborative approach. Siemens Healthineers.

How does the CT Pneumonia Analysis2 work? Siemens Healthineers.

FDA Expedites Clearance for AI Ultrasound Solution to Fight COVID-19. HIT Consultants.Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19. Lab on a Chip.


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