summary: A recent study found that secondary bacterial pneumonia, rather than the much-discussed ‘cytokine storm’, was a significant factor in COVID-19-related deaths. Almost half of the patients who required ventilator support were affected by this secondary bacterial infection.
By applying machine learning to analyze medical records, researchers found that people who recovered from secondary pneumonia were more likely to survive, whereas unresolved cases had an increased risk of death. Did.
Challenging the cytokine storm theory, this study highlights the importance of preventing and aggressively treating secondary bacterial pneumonia in critically ill patients.
Important facts:
- Nearly half of COVID-19 patients requiring ventilator support developed secondary bacterial pneumonia, significantly increasing mortality.
- Patients who recovered from secondary bacterial pneumonia were more likely to survive, and those who were unresolved were more likely to die.
- This study challenges the widely held belief that a ‘cytokine storm’ causes death in COVID-19 patients and highlights the importance of prevention and aggressive treatment of secondary bacterial pneumonia in critically ill patients. I’m here.
sauce: Northwestern University
Secondary bacterial infections of the lungs (pneumonia) are very common in patients with COVID-19, affecting nearly half of those requiring ventilator support.
By applying machine learning to medical record data, scientists at Northwestern University Feinberg School of Medicine found that unresolved secondary bacterial pneumonia is the leading cause of death in COVID-19 patients. It even exceeds the death rate from the virus infection itself.
Scientists also found evidence that COVID-19 does not trigger a “cytokine storm.”
This research recently Clinical Investigative Journal.
“Our study highlights the importance of preventing, detecting, and aggressively treating secondary bacterial pneumonia in critically ill patients with severe pneumonia, including COVID-19.” and Pulmonary and Critical Care Physician at Northwestern Medicine.
Researchers found that nearly half of COVID-19 patients develop ventilator-associated secondary bacterial pneumonia.
“People who were cured of secondary pneumonia were more likely to survive, whereas those who were not cured of pneumonia were more likely to die,” Singer said.
“Our data suggest that the mortality associated with the virus itself is relatively low, but other things that occur during ICU stays, such as secondary bacterial pneumonia, offset that. ”
The findings also refute the cytokine storm hypothesis, Singer said.
“The term ‘cytokine storm’ refers to overwhelming inflammation that causes organ failure in the lungs, kidneys, brain and other organs,” Singer said.
“If that is true, and if cytokine storms underlie the prolonged stays seen in COVID-19 patients, we would expect to see frequent transitions to a condition characterized by multiple organ failure. is not what I saw.”
This study analyzed 585 patients with severe pneumonia and respiratory failure in the intensive care unit (ICU) of Northwestern Memorial Hospital, of whom 190 had COVID-19.
Scientists have developed a new machine learning approach called CarpeDiem. It groups similar patient days in his ICU into clinical status based on electronic health record data.
This new approach, based on the concept of daily rounds by the ICU team, allowed us to ask how complications like bacterial pneumonia affected the course of the disease.
These patients or their surrogates consented to enroll in the Successful Clinical Responses to Pneumonia Treatment (SCRIPT) study, an observational trial to identify new biomarkers and treatments in patients with severe pneumonia.
As part of SCRIPT, an expert panel of ICU physicians used state-of-the-art analysis of lung samples collected as part of clinical care to diagnose and determine the outcome of secondary pneumonia events.
“By applying machine learning and artificial intelligence to clinical data, we can develop better ways to treat diseases such as COVID-19 and assist ICU physicians managing these patients.” Feinberg Lung and Physician in Critical Care Medicine and Northwestern Medicine.
“The importance of bacterial co-infection in the lungs as a contributing factor to death in COVID-19 patients has been underestimated. This is because we have only looked at the results in terms of the presence or absence of bacterial superinfection, said study co-author Richard Wandering, PhD, who leads successful clinical responses at Northwestern University’s Center for Pneumonia Therapeutic Systems Biology. increase.
The next step in research is to use molecular data from research samples and integrate it with machine learning approaches to understand why some patients are cured of pneumonia and others are not.
The researchers also hope to extend the technique to larger datasets, use the model to make predictions, and bring it back to the bedside to improve care for critically ill patients.
Other Northwestern authors of this paper include 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, Scott Budinger, Alexander Misharin.
Funding: This work was supported by grant U19AI135964 from the Simpson Quarry Lung Translational Science Institute and the National Institute of Allergy and Infectious Diseases at the National Institutes of Health.
About this Artificial Intelligence Research News
author: Mara Paul
sauce: Northwestern University
contact: Marla Paul – Northwestern University
image: Image credited to Neuroscience News
Original research: open access.
“Machine learning associates unresolved secondary pneumonia with mortality in patients with severe pneumonia, including COVID-19,” by Benjamin Singer et al. Journal of Clinical Investigation
overview
Machine learning associates unresolved secondary pneumonia with mortality in patients with severe pneumonia, including COVID-19
Background. Despite guidelines promoting the prevention and aggressive treatment of ventilator-associated pneumonia (VAP), the importance of VAP as a driver of outcomes in ventilator-using patients, including those with severe COVID-19 Gender remains unknown. We aimed to determine the contribution of treatment failure for her VAP to mortality in a patient with severe pneumonia.
Method. A single-center, prospective cohort study was conducted in 585 mechanically ventilated patients with severe pneumonia and respiratory failure. Of those, 190 had her COVID-19, and he underwent at least one bronchoalveolar lavage. A panel of ICU doctors determined pneumonia episodes and endpoints based on clinical and microbiological data. Considering her relatively long ICU stay for COVID-19 patient, we developed the following machine learning approach. carpe diemgroup similar ICU patient days into clinical status based on electronic health record data.
result.carpe diem Longer ICU stays in COVID-19 patients were found to be primarily due to prolonged stays in clinical conditions characterized by respiratory failure. Although VAP was not associated with overall mortality, mortality was higher in patients who had one episode of VAP who had failed treatment compared to patients who had successfully treated VAP. (76.4% vs 17.6%, P. < 0.001). In all patients, including those with COVID-19, carpe diem We showed that unresolved VAP is associated with transition to a clinical state associated with higher mortality.
Conclusion. Failure to treat VAP results in high mortality. The relatively long hospital stay of COVID-19 patients is mainly due to prolonged respiratory failure, which increases the risk of VAP.
Financing. U19AI135964
