November 22, 2024

“Cytokine Storm” Debunked: Machine Learning Exposes the True Killer of COVID-19 Patients

Scientists at Northwestern University Feinberg School of Medicine have discovered that unsettled secondary bacterial pneumonia is a crucial motorist of death in clients with COVID-19, impacting nearly half of the clients who needed mechanical ventilation support. Their findings, published in The Journal of Clinical Investigation, likewise debunk the theory that COVID-19 causes a “cytokine storm” causing death.
Machine knowing finds no evidence of cytokine storm in seriously ill patients with COVID-19

Benjamin Singer, MD, the Lawrence Hicks Professor of Pulmonary Medicine in the Department of Medicine and a Northwestern Medicine lung and important care doctor. Credit: Northwestern Medicine
” Our research study highlights the importance of avoiding, searching for, and aggressively dealing with secondary bacterial pneumonia in seriously ill patients with serious pneumonia, including those with COVID-19,” stated senior author Benjamin Singer, MD, the Lawrence Hicks Professor of Pulmonary Medicine in the Department of Medicine and a Northwestern Medicine pulmonary and critical care doctor.
The investigators found nearly half of clients with COVID-19 develop a secondary ventilator-associated bacterial pneumonia.
” Those who were cured of their secondary pneumonia were likely to live, while those whose pneumonia did not solve were more likely to die,” Singer stated. “Our information recommended that the death associated to the virus itself is reasonably low, however other things that happen during the ICU stay, like secondary bacterial pneumonia, offset that.”
The research study findings likewise negate the cytokine storm theory, said Singer, likewise a professor of Biochemistry and Molecular Genetics.
” The term cytokine storm means a frustrating inflammation that drives organ failure in your lungs, your kidneys, your brain and other organs,” Singer said. “If that held true, if cytokine storm were underlying the long length of stay we see in clients with COVID-19, we would expect to see frequent shifts to states that are identified by multi-organ failure. Thats not what we saw.”
The research study examined 585 clients in the intensive care system (ICU) at Northwestern Memorial Hospital with severe pneumonia and respiratory failure, 190 of whom had COVID-19. The researchers developed a new device finding out technique called CarpeDiem, which groups comparable ICU patient-days into scientific states based on electronic health record information. This novel approach, which is based on the idea of day-to-day rounds by the ICU group, permitted them to ask how problems like bacterial pneumonia affected the course of the illness.
These clients or their surrogates consented to register in the Successful Clinical Response to Pneumonia Therapy (SCRIPT) study, an observational trial to recognize brand-new biomarkers and treatments for clients with severe pneumonia. As part of SCRIPT, a skilled panel of ICU physicians used modern analysis of lung samples collected as part of scientific care to detect and adjudicate the results of secondary pneumonia events.
” The application of artificial intelligence and synthetic intelligence to scientific information can be utilized to establish much better ways to deal with illness like COVID-19 and to assist ICU physicians managing these patients,” said study co-first author Catherine Gao, MD, an instructor in the Department of Medicine, Division of Critical and lung Care and a Northwestern Medicine doctor.
” The importance of bacterial superinfection of the lung as a contributor to death in patients with COVID-19 has been underappreciated, due to the fact that many centers have actually not tried to find it or only take a look at results in terms of existence or absence of bacterial superinfection, not whether treatment is successful or not,” stated research study co-author Richard Wunderink, MD, who leads the Successful Clinical Response in Pneumonia Therapy Systems Biology Center at Northwestern.
The next step in the research will be to utilize molecular data from the study samples and integrate it with machine learning approaches to comprehend why some patients go on to be treated of pneumonia and some dont. Detectives also want to expand the technique to larger datasets and utilize the model to make predictions that can be reminded the bedside to improve the care of seriously ill clients.
Referral: “Machine knowing links unresolving secondary pneumonia to death in clients with serious pneumonia, including COVID-19” by Catherine A. Gao, Nikolay S. Markov, Thomas Stoeger, Anna E. Pawlowski, Mengjia Kang, Prasanth Nannapaneni, Rogan A. Grant, Chiagozie Pickens, James M. Walter, Jacqueline M. Kruser, Luke V. Rasmussen, Daniel Schneider, Justin Starren, Helen K. Donnelly, Alvaro Donayre, Yuan Luo, G.R. Scott Budinger, Richard G. Wunderink, Alexander V. Misharin and Benjamin D. Singer, 27 April 2023, The Journal of Clinical Investigation.DOI: 10.1172/ JCI170682.
Other Northwestern authors on the paper include Nikolay Markov; Thomas Stoeger, PhD; Anna Pawlowski; Mengjia Kang, MS; Prasanth Nannapaneni; Rogan Grant; Chiagozie Pickens 14 MD 17 GME, assistant teacher of Medicine in the Division of Critical and lung Care; James Walter, MD, assistant professor of Medicine in the Division of Pulmonary and Critical Care; Jacqueline Kruser, MD; Luke Rasmussen, MS; Daniel Schneider, MS; Justin Starren, MD, PhD, chief of Health and Biomedical Informatics in the Department of Preventive Medicine; Helen Donnelly; Alvaro Donayre; Yuan Luo, PhD, director of the Center for Collaborative AI in Healthcare and associate teacher of Preventive Medicine; Scott Budinger, MD, chief of Pulmonary and Critical Care in the Department of Medicine; and Alexander Misharin, MD, PhD, associate professor of Medicine in the Division of Pulmonary and Critical Care.
The research study was supported by the Simpson Querrey Lung Institute for Translational Sciences and grant U19AI135964 from the National Institute of Allergy and Infectious Diseases of the National Institutes of Health.

No evidence of cytokine storm in seriously ill clients with COVID-19.
Nearly half of clients with COVID-19 establish a secondary bacterial pneumonia
Crucial to find and aggressively treat secondary bacterial pneumonia in ICU clients

Secondary bacterial infection of the lung (pneumonia) was very common in clients with COVID-19, affecting practically half the clients who required support from mechanical ventilation. By applying maker finding out to medical record information, researchers at Northwestern University Feinberg School of Medicine have actually discovered that secondary bacterial pneumonia that does not deal with was a crucial chauffeur of death in patients with COVID-19, results released in The Journal of Clinical Investigation.
Bacterial infections might even surpass death rates from the viral infection itself, according to the findings. The scientists likewise found evidence that COVID-19 does not cause a “cytokine storm,” so often thought to cause death.

” The term cytokine storm implies a frustrating swelling that drives organ failure in your lungs, your kidneys, your brain and other organs,” Singer stated. “If that were true, if cytokine storm were underlying the long length of stay we see in clients with COVID-19, we would expect to see regular shifts to states that are identified by multi-organ failure. The research study examined 585 patients in the intensive care system (ICU) at Northwestern Memorial Hospital with extreme pneumonia and breathing failure, 190 of whom had COVID-19. The scientists developed a brand-new device discovering technique called CarpeDiem, which groups similar ICU patient-days into medical states based on electronic health record information. This unique technique, which is based on the principle of day-to-day rounds by the ICU group, allowed them to ask how complications like bacterial pneumonia affected the course of the illness.