Mayo Clinic and nference Study Links Pre-Existing Conditions to Short- and Long-Term COVID-19 Complications

nference, the AI-driven health technology company, today announced publication of a study in npj Digital Medicine which establishes relationships between specific pre-existing conditions and complications from COVID-19 infection, in an effort to better identify which patients will develop severe disease. npj Digital Medicine is an online open-access journal from Springer Nature dedicated to publishing high quality peer-reviewed research to provide the necessary data and longitudinal monitoring to best inform the broadest medical community. 

Authors of the study, "Mapping each pre-existing condition's association to short-term and long-term COVID-19 complications," analyzed the clinical notes of 1803 hospitalized Mayo Clinic COVID-19 patients, using advanced nference artificial intelligence (AI) software to characterize associations between 21 risk factors for COVID-19 severe illness reported by the CDC and the development of 20 complications (including respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection. 

The researchers found hypertension was the most significant risk factor associated with 10 different complications including pleural effusion, acute respiratory distress syndrome (ARDS), cardiac arrhythmia, and anemia.

"The significance of hypertension as a factor in ARDS, which was not previously known, is quite striking," says Venky Soundararajan, PhD, co-founder and chief scientific officer of nference. "This study validates initial findings from the CDC that these comorbidities are significant risk factors. Specifically in the case of hypertension patients, healthcare workers should expect more serious short term complications."

In another notable result, while the risk of new-onset of pleural effusion is reduced after a month, the study revealed persistent risk of pleural effusion beyond 30 days post-infection, particularly among patients with pre-existing conditions such as cardiomyopathy, chronic kidney disease, and coronary artery disease. This indicates an increased need to monitor patients with pre-existing conditions for pleural effusion well beyond the initial period of illness. 

"This study provides important evidence that physicians consider pre-existing conditions when monitoring and determining treatment for COVID patients," said Andrew Badley, MD, co-author of the study and enterprise chair of the department of molecular medicine and enterprise chair of COVID-19 task force at the Mayo Clinic. "In particular, as medical professionals around the world work to understand more about long COVID, this study may shed light on underlying factors that may lead to complications months after patients recover from coronavirus."

In the process of conducting these studies, nference employed its leading-edge augmented intelligence software, nferX®, which uses proprietary natural language learning processes to rapidly synthesize and process lab tests, clinical notes and structured Electronic Health Records (EHRs) to produce actionable results.

This powerful AI technology, frequently implemented by nference during the COVID-19 pandemic, has enabled discoveries with a wide range of implications that contribute to a greater understanding of the virus and the disease, which are ultimately advancing patient care.

About nference

Through its powerful augmented intelligence software nferX®, nference is transforming health care by making biomedical knowledge computable. Its partnership with Mayo Clinic has given nference an opportunity to synthesize more than 100 years of institutional knowledge, producing real-world evidence in real time by converting large amounts of data into deep insights to advance discovery and development of diagnostics and therapeutics. nference is headquartered in Cambridge, Massachusetts and has operations in Rochester, Minnesota; Toronto, Canada; and Bangalore, India.