Sepsis is a life-threatening condition that occurs when the body’s response to an infection damages its own tissues and organs. Sepsis can lead to shock, multiple organ failure, and death. It is a leading cause of death in hospitalized patients.
COVID-19 is a novel coronavirus that was first identified in 2019. It is similar to other coronaviruses, such as SARS-CoV and MERS-CoV. COVID-19 has caused a global pandemic of respiratory illness.
Patients with COVID-19 are at risk for developing sepsis. This is especially true for patients who are elderly or have underlying health conditions such as diabetes, lung disease, or heart disease.
A new study has found that a genetic model can predict which COVID-19 patients are most at risk for developing sepsis. The study looked at the genes of 617 COVID-19 patients in China. The researchers found that certain genes were associated with an increased risk of sepsis.
The findings of this study could help doctors to better identify which COVID-19 patients are most at risk for developing sepsis. This is important because sepsis can be fatal. Early diagnosis and treatment of sepsis is essential for the best possible outcome.
Sepsis, a potentially life-threatening condition caused by infection, is a leading cause of death in hospitalised patients. Now, researchers have used a machine-learning approach to create a genetic model that can predict which COVID-19 patients are most at risk of developing sepsis.
The findings, published in the journal Nature Medicine, could help clinicians identify patients who are most in need of close monitoring and early intervention.
Sepsis occurs when an infection triggers a widespread immune response, leading to inflammation and organ damage. It is a major cause of death in hospitalised patients, accounting for around 11% of all in-hospital deaths in the United States.
COVID-19, the disease caused by the new coronavirus, has also been shown to increase the risk of sepsis. A recent study found that around 18% of patients who were hospitalised with COVID-19 developed sepsis, and of those, around one-third died.
To better understand the link between COVID-19 and sepsis, a team of researchers from the University of California, San Francisco (UCSF) used a machine-learning approach to create a model that could predict which patients were most at risk.
The team first analysed data from 5,796 patients with COVID-19 who were admitted to hospital in New York City between March and May 2020. They used this data to train a machine-learning model to identify genetic markers associated with an increased risk of sepsis.
They then validated their model using data from 1,398 patients with COVID-19 who were admitted to hospital in California between March and June 2020.
The findings showed that the model was able to accurately predict which patients were at risk of developing sepsis, with a sensitivity of 80.6% and a specificity of 79.8%.
The genetic markers associated with an increased risk of sepsis were found to be located in genes involved in immune function and inflammation.
The findings suggest that it may be possible to use a genetic test to identify which COVID-19 patients are most at risk of developing sepsis. This could help clinicians to better monitor these patients and offer early intervention when necessary.
The model also allowed the team to identify a subgroup of patients with COVID-19 who had a particularly high risk of developing sepsis. These patients had a three-fold increased risk of sepsis and a four-fold increased risk of death from sepsis, compared to patients without these genetic markers.
The findings could help to improve the management of patients with COVID-19, and may also be applicable to other conditions that increase the risk of sepsis.