Research Summaries

This RECOVER study tested a new way to identify Long COVID in children. Researchers created a special computer-based tool, called a computable phenotype (CP), that scans electronic health records (EHRs) for specific codes and symptoms linked to Long COVID. To test the CP, researchers scanned records for nearly 340,000 children who had COVID-19. Doctors then checked a smaller group of 651 children’s records to see how well it worked. The study showed that the CP was able to successfully find that a child had Long COVID. But it sometimes marked symptoms that fit in with health problems someone had before getting COVID-19 (pre-existing conditions), so it wasn’t clear if those symptoms were due to COVID-19. When the researchers updated the CP to pay closer attention to pre-existing conditions, it became more accurate at identifying Long COVID from EHRs. This study is important because it provides a faster and more consistent way for researchers to identify Long COVID in large groups of children. This tool can help doctors give better care to children with Long COVID.

This RECOVER study looked at whether pregnant women who had the Omicron type of COVID-19 were more likely to have Long COVID than women who were not pregnant when they had the Omicron type of COVID-19. Researchers studied the symptom surveys and study visits of more than 2,400 RECOVER pregnancy participants, ages 18–45, to see if being pregnant while having COVID-19 impacted the risk of developing Long COVID. They found that about 10.2% of the participants who had COVID-19 while pregnant later got Long COVID, compared with 10.6% of the those who were not pregnant at the time of infection. This suggests that there was no real difference in the chance of getting Long COVID based on whether someone was pregnant or not when they got COVID-19. This study is important because it helps researchers better understand the risk of developing COVID-19 based on whether or not someone is pregnant.

In this RECOVER study, researchers wanted to find out if natural language processing (NLP) could be used to identify Long COVID symptoms in children. NLP is a tool that can help find details in electronic health records (EHRs) beyond what is usually looked at in EHRs, such as diagnosis or billing codes (known as standard EHR data). Researchers used an NLP tool to look for 25 signs of Long COVID in children: 21 symptoms (like pain or extreme tiredness) and 4 types of daily life challenges (such as trouble with school). They compared children who had been diagnosed with Long COVID to those who had COVID-19 but did not develop Long COVID. The NLP tool analyzed more than 48,000 doctors’ notes within the EHRs of more than 10,000 children across 12 hospitals. Researchers found that the NLP tool identified almost all 25 symptoms much more often in the children who had Long COVID. The NLP tool also often identified patients’ symptoms that were not recognized when researchers only looked at standard EHR data. The study shows that using NLP to read EHR notes can help researchers better understand the symptoms and daily challenges that children with Long COVID experience when compared to looking only at codes and medication lists. This supports the idea that NLP should be used when doing scientific studies that need to identify children with Long COVID.

This RECOVER study looked at how Long COVID symptoms change as people get older and how often those changes happen. Researchers compared younger adults (ages 18–59) and older adults (age 60 and older) who did and did not have COVID-19. They found that Long COVID was most common in people ages 40–59, and less common in those ages 70 and older. Among the participants ages 70 and older, symptoms like fatigue, pain, and hearing problems were less helpful in identifying Long COVID because they were also common in older people who had never had COVID-19. Instead, symptoms of Long COVID in older adults were more likely to include problems with smell and taste as well as stomach issues. This finding is important because it helps doctors know what to look for when diagnosing and treating Long COVID in older patients.

In this RECOVER study, researchers wanted to understand the connection between Long COVID and chronic kidney disease (CKD) in adults who had COVID-19. CKD is long-term, permanent damage to the kidneys. Researchers looked at the electronic health records (EHRs) of more than 2 million adults across 59 health systems in the US to see if people with CKD were more likely to develop Long COVID. The study found that, compared to people without CKD, those who had even mild cases of CKD were more likely to get Long COVID after COVID-19. Researchers also found that, compared to adults who did not get Long COVID, those who developed Long COVID and had healthy kidneys before getting COVID-19 were more likely to develop new CKD or have worsened kidney function within a year. These findings show how Long COVID and kidney disease can affect each other and highlight how important it is for doctors to monitor people’s kidney health after they get COVID-19.

This RECOVER study looked at whether people with Human Immunodeficiency Virus (HIV) are more likely to get Long COVID after having COVID-19. HIV is a virus that attacks the body’s immune system. Researchers used electronic health records (EHRs) from 2 nationwide research networks of people ages 21 and older who had COVID-19. They divided them into 2 groups: people with HIV and people without HIV. Researchers used 2 methods to find people in the groups who might have Long COVID. One used a computer system that looked for Long COVID symptoms in medical records. The other looked for official diagnosis codes that doctors enter when they think someone has Long COVID. They found that people with HIV may have a slightly higher risk of being diagnosed with Long COVID when looking for Long COVID symptoms in medical records. However, they found that there was no clear link between having HIV and receiving the official diagnosis code for Long COVID. This suggests that Long COVID may be missed in people with long-term health problems like HIV.

In this RECOVER study, researchers looked at whether getting COVID-19 a second time increases a child’s or teenager’s risk of developing Long COVID. Researchers compared the electronic health records (EHRs) of more than 400,000 children and teens who had COVID-19 once with the EHRs of about 58,000 children and teens who had COVID-19 twice during the Omicron period. They found that children and teens who had COVID-19 twice were two times more likely to be diagnosed with Long COVID compared to those who only had it once. Children and teens who got COVID-19 twice also experienced other health problems more often, like being very tired, headaches, stomach pain, and heart or kidney problems. This study is important because it shows that children and teens are much more likely to develop Long COVID after getting COVID-19 more than once. These findings show why it is important to continue learning about ways to protect children and teens from getting COVID-19.

This RECOVER study looked at how sense of smell changed over time in people who had COVID-19. Researchers gave a “scratch-and-sniff” test to a large group of people about 2 years after they had COVID-19. This test, called the University of Pennsylvania Identification Test (UPSIT), checks whether people can smell certain odors. The study found that 8 out of 10 people who felt that they had lost or had changes in smell after having COVID-19 were in fact not able to smell the odors normally. Even two-thirds of the people who thought their sense of smell was completely normal had a weaker sense of smell than they realized. These findings show that a weaker sense of smell can be a common and lasting problem after COVID-19. Because changes in smell have been linked to memory and thinking problems in other conditions, this could mean that people with changes in smell from COVID-19 could be at risk for thinking and memory issues. Doctors should use special smell tests to point out smell loss that patients may not notice to help them understand their condition and its risks, like not being able to smell smoke or spoiled food.

In this RECOVER study, researchers created a new computer tool to help doctors identify Long COVID more quickly and accurately. The tool, called a hybrid natural language processing (NLP) pipeline, quickly scans patients’ electronic health records (EHRs) to find descriptions of symptoms and figure out if a patient has them. Researchers tested this tool across 11 US health systems and found it was very accurate at identifying the right Long COVID symptoms. Patient EHRs contain a lot of important information, but it can take a long time to find specific symptoms across thousands of records. Researchers can now look at large amounts of health records from thousands of patients at once using the hybrid NLP pipeline technology. This study is important because it gives researchers a faster, more accurate way to identify Long COVID.