Nat Med: Studying data from nearly 35,000 COVID patients identified four main symptom patterns for COVID growth

In a new study, researchers from research institutions such as Weill Cornell Medical College in the United States found that there are four main subtypes of post-COVID syndrome called long COVID, defined by different symptom groups
.
The findings were recently published in the journal Nature Medicine as "Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.
"

The new study is the largest
of its kind to explore the long coronavirus.
The authors used a machine learning algorithm to find symptom patterns
in the health records of nearly 35,000 U.
S.
patients who tested positive for COVID infection and later developed lingering long COVID symptoms.

The new study, funded by the National Institutes of Health's (NIH) "Researching COVID to Enhance Recovery (RECOVER) program, is part of a year-long $9.
8 million grant focused on the Electronic Health Record Cohort Study, spearheaded by Dr.
Rainu Kaushal, senior associate dean for clinical research and chair of the Department of Population Health Sciences at Weill Cornell Medical School
。

Kaushal said, "The purpose of RECOVER is to quickly clarify what happened
in the long COVID.
Study how cases are classified to influence patient outcomes and care
.
”

Of the four main symptom patterns detected, one pattern was characterized by heart and kidney problems, including patients with a relatively high proportion of infections in the first months of the COVID-19 pandemic in the United States; Another pattern includes respiratory problems, anxiety, sleep disturbances, and other symptoms, including headaches and chest pain; Nearly two-thirds of patients with this pattern are women
.

Corresponding author Fei Wang, Ph.
D.
, associate professor in the Department of Population Health Sciences at Weill Cornell Medical School, said, "These results should inform ongoing research on the potential mechanisms and potential treatments for the long new crown
.
”

Viral infections sometimes leave patients with a variety of lingering, often non-specific symptoms
.
For SARS-CoV-2, post-infection syndrome is commonly referred to as long COVID, and more formally referred to as "Post-Acute Sequelae of SARS-Cov-2 Infection (PASC)"
.
They seem to be very common; It is estimated that Americans with COVID make up to 40%
of the U.
S.
adult population.

"Understanding the epidemiology of COVID enables clinicians to help patients understand their symptoms and prognosis, and to facilitate multidisciplinary treatment
of patients," Kaushal said.
Electronic health records provide a window into this situation, allowing us to better characterize COVID symptoms and inform other types of research
, including basic findings and clinical trials.
”

The health records analyzed in the new study came from two large datasets collected by the National Patient-Centered Clinical Research Network (PCORnet), a consortium
of eight medical institutions from across the United States 。 One dataset comes from Kaushal-led INSIGHT Clinical Research Network, which includes data from patients in New York, while the other comes from the OneFlorida+ network, which includes patients
from Florida, Georgia and Alabama.
Overall, the analysis covers the health records
of 34,605 different patients from March 2020 to November 2021 and does not include the first wave of Omicron.