Research Summaries

RECOVER researchers wanted to understand whether being vaccinated before having COVID-19 lowered the chance of developing Long COVID. They used electronic health records (EHR) to study the effect of vaccination using EHR for two groups of people who had COVID-19. One group was based on clinic data and represented more than 47,000 people. In this group, 695 were diagnosed with Long COVID in clinics and more than 26,000 were fully vaccinated. The other group represented almost 200,000 individuals who had COVID-19. The researchers used a computer program to estimate who might have Long COVID in this group based on their medical and symptom information. In this group, more than 86,000 people represented were fully vaccinated. The researchers made sure that the people in the vaccinated and unvaccinated groups were as similar to each other as possible in terms of the same sex, age, race, and medical history. 

To test whether vaccination lowered the chance of developing Long COVID, they made comparisons within each group. They used several different definitions of Long COVID and several different statistical tests to figure out whether vaccination status affected Long COVID. For both of the study groups and for all definitions of Long COVID and each statistical test in the analysis, the researchers got the same answer: people who were vaccinated before having COVID-19 were less likely to develop Long COVID.

RECOVER researchers wanted to identify conditions and symptoms associated with Long COVID in children (also known as pediatric Long COVID). The researchers analyzed electronic health record (EHR) data to detect conditions and symptoms associated with pediatric Long COVID. The study identified multiple conditions and body systems associated with pediatric Long COVID related to many different organs, such as heart and lung problems. 

This research is important because these findings use a data-driven approach to detect several new or under-reported conditions and symptoms that should be studied further. Researchers believe that further study may reveal the biological processes that cause these Long COVID symptoms and conditions.

RECOVER researchers wanted to learn more about racial and ethnic differences in Long COVID. Researchers used patients’ electronic health records (EHRs) to compare people who had COVID-19 based on their race or ethnicity, whether they were hospitalized due to COVID-19, and whether they had any health problems related to Long COVID. They looked at data from over 60,000 adults from 5 healthcare systems.

The researchers found that Black and Hispanic adults were more likely to have symptoms of Long COVID compared to White adults – this was true for adults who were and were not hospitalized. The reason for these differences is unclear.

RECOVER researchers wanted to find environmental risk factors of Long COVID by comparing the environment of people who had Long COVID to people who didn’t have Long COVID. Environmental risk factors are things about where a person lives that raise their chance of having a health condition, such as air pollution and poor housing conditions. The researchers looked at data from electronic health records (EHRs) of more than 100,000 people in the New York City area and Florida.  

The researchers found that people who lived in areas with higher levels of air pollution, more poverty, and less access to healthy food had a higher chance of getting Long COVID. People in the New York City area had different environmental risk factors than people in Florida. 

RECOVER researchers analyzed electronic health records (EHR) in order to define Long COVID. Researchers found up to 25 different symptoms that patients who had COVID-19 were more likely to have than those who didn’t have COVID-19. The symptoms were related to many different organs, such as memory loss, hair loss, and feeling tired. They found that certain types of Long COVID symptoms were more likely to happen in patients who were older, had more severe COVID-19, or had more health problems before they had COVID-19. 

This research is important because the findings show that Long COVID affects many organs, and types of Long COVID symptoms differ between certain groups of patients. However, EHR findings are limited in that they can only look at data from the patients' past. In order to confirm these findings, future studies that follow patients' symptoms over time, into the future, are needed.

RECOVER researchers explored Multisystem Inflammatory Syndrome in Children (MIS-C), a Long COVID symptom where there is inflammation (swelling) of multiple organ systems. Researchers looked to see if MIS-C can be identified and managed in the home (outpatient) instead of in the hospital (inpatient). 

An organ system is a collection of organs in your body dedicated to maintaining necessary functions. For example, your heart, arteries, and veins make up the Cardiovascular System--the system responsible for maintaining blood flow and delivering oxygen throughout the body.

Researchers were able to identify that in some patients, their MIS-C symptoms were mild enough to be treated at home and not require hospitalization. These results raise awareness that MIS-C can present in milder forms with the option to treat it at home if directed by a physician.

The relationship between COVID-19 and diabetes has captured the interest of many researchers. Some studies suggest that people may be more likely to develop type 2 diabetes after having COVID-19. The authors of this study tried to find out whether new diagnoses of type 2 diabetes are more common after having COVID-19. They did this by looking at electronic health records (EHRs), which are digital medical charts that have health data like doctor visits, lab results, and other health history. 

The researchers looked at the EHRs of people across the country who had COVID-19 and were also diagnosed with type 2 diabetes within 6 months before or after having COVID-19. They found that the number of new diagnoses increased during the period when people had COVID-19, likely due to increased interaction with the healthcare system during that time. However, the average number of new diabetes diagnoses was about 83% lower in the 6 months after having COVID-19 than in the 6 months before having COVID-19. This analysis could not explain whether having COVID-19 makes people more likely to get diabetes, but it does include the unexpected finding that a diabetes diagnosis was less common months after having COVID-19.

RECOVER researchers looked at the use of a code to diagnose Long COVID in electronic health records (EHRs). They used EHR data from over 8,000 people and compared people who had the ICD-10 code for Long COVID (which is U09.9) in their EHR on or after October 1, 2021. They also looked at other codes in their EHR for health conditions, symptoms, tests, and treatments within 60 days after their Long COVID diagnosis.

Researchers found that many doctors use the Long COVID code along with other codes. People with Long COVID had a mix of symptoms and other health conditions, tests, and treatments. This suggests there may be different types of Long COVID. The researchers concluded that for now, doctors should look at a person’s mix of symptoms and other health conditions to diagnose Long COVID.

In this study, RECOVER researchers used a computer program to identify possible types of Long COVID based on electronic health records (EHRs). They used the computer program to review EHRs of people diagnosed with Long COVID and group them based on patterns in their symptoms and health conditions.

The computer program found 6 different types of Long COVID, which were related to 1) many symptoms and health conditions with unusual lab test results, 2) the lungs, 3) the brain, 4) the heart, 5) pain and feeling weak and tired (fatigue), and 6) many symptoms and conditions with pain. Each type of Long COVID also differed based on health conditions people had before COVID-19 and how severe their COVID-19 was. This research could help identify people with different types of Long COVID to better diagnose and treat them and invite them to join research studies.