EHR Data Reveals Risk Factors for Poor Outcomes with COVID-19

May 27, 2020 - A team from NYU Langone Health analyzed EHR data and found that low levels of blood oxygen and markers of inflammation were strongly associated with poor outcomes among patients hospitalized with COVID-19.

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In a study published in The BMJ, researchers noted that while reports from China, Italy, and the US have described some characteristics of people with COVID-19, little is known about factors associated with hospitalization and severe disease.

“Studies so far have included few people with severe outcomes or have not compared people with severe disease with those with less virulent disease, making it difficult to assess characteristics associated with poor outcomes. Few large studies have conducted multivariable regression to help identify the strongest risk factors,” the team said.

Researchers analyzed EHR data from 5,279 patients who tested positive for COVID-19. The team then assessed three primary outcomes, including inpatient hospitalization, critical illness, and discharge to hospice or death among hospitalized patients.

The results showed that the factors most strongly associated with hospital admission were age, heart failure, male sex, chronic kidney disease, any increase in BMI, and hypertension. These findings are consistent with a study recently published in JAMA, which revealed that hypertension, diabetes, and obesity are key chronic diseases in the acuity of COVID-19.

The team pointed out that while these factors logically contribute to severe illness among COVID-19 patients, the group was surprised that certain respiratory diseases didn’t have as great an impact.

“The comorbidities we identified as associated with hospital admission in COVID-19 are largely similar to those associated with any type of severe infectious disease requiring hospital admission or ICU level care, though we were surprised that chronic pulmonary disease did not feature more prominently,” researchers stated.

“Others have also noted the absence of asthma and chronic obstructive pulmonary disease as risks for severity of illness in patients with COVID-19. The epidemiologic and/or pathophysiologic reasons for this are unknown.”

In addition to identifying factors that cause severe illness in patients with COVID-19, NYU Langone researchers also discovered risk factors for poor outcomes with the virus. The team found that blood oxygen levels below 88 percent upon admission and markers of inflammation were more strongly associated with critical illness than age and comorbidities.

“We noted a striking association of inflammatory markers with mortality and critical illness among patients admitted to hospital; particularly, early increases in C reactive protein and D-dimer levels. Hyperinflammatory states are well described in severe sepsis; however, the degree to which covid-19 related inflammation is similar to or different from that typically found in sepsis is unknown,” the group said.

The study also revealed that although the risk of hospitalization was constant across the study period, risk of critical illness decreased over time, which suggests that continuous treatment of the disease could lead to improved outcomes even without a vaccine.

“Our institution was stretched but not overwhelmed by the epidemic and did not experience important equipment or treatment shortages,” researchers said.

“The improvement in outcomes over time (in the setting of a functioning health system) raises the possibility that familiarity with the disease, ongoing iteration of protocols and practices in response to observed outcomes, and initiation of new treatments might improve outcomes even in the absence of vaccination or regimens known to be effective.”

In future research, the team plans to create predictive risk models to better identify which patients are most likely to experience poor outcomes as a result of the virus.

“While we continue to study outcomes in patients who tested positive for COVID-19 to create reliable real-time tools, the next phase of investigation will be development of predictive risk models to build into provider workflows, analyzing differences in outcomes across different hospitals to identify best clinical practices, and, finally, looking at non-COVID patients who may have delayed medical care from being fearful to come to the hospital,” said Christopher M. Petrilli, MD, assistant professor, Department of Medicine at NYU Langone Health.