While I don't particularly doubt the conclusion...
"The study analyzed 585 patients in the intensive care unit (ICU) at Northwestern Memorial Hospital with severe pneumonia and respiratory failure, 190 of whom had COVID-19. The scientists developed a new machine learning approach called CarpeDiem, which groups similar ICU patient-days into clinical states based on electronic health record data."
Wait, one hospital? Less than 1000 patients, and less then 200 who had covid-19? What if that hospital was located in an area with older demographics? Or younger? Or different in some other medically significant way than the general population? Also, what if the doctors or the policy for treating covid-19 was different than at many hospitals? There was no generally accepted method at first, and when things like "lay them on their chest instead of their back" were discovered, or "ventilators don't really seem to help much", I'm sure they got adopted at different hospitals at different times. I don't know that I would conclude much of anything from a study of this size.
"The investigators found nearly half of patients 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 resolve were more likely to die," Singer said. "Our data suggested that the mortality related to the virus itself is relatively low, but other things that happen during the ICU stay, like secondary bacterial pneumonia, offset that."
Umm, if cytokine storm wasn't what was putting people at risk, how did dexamethasone have such a powerful affect keeping people alive. As a strong steroid, it reduced inflammation and throttled back the immune response. Yeah, that would have enabled secondary infections a bit more room to grow, but the problem is that dosed people did better than worse.
"The study analyzed 585 patients in the intensive care unit (ICU) at Northwestern Memorial Hospital with severe pneumonia and respiratory failure, 190 of whom had COVID-19. The scientists developed a new machine learning approach called CarpeDiem, which groups similar ICU patient-days into clinical states based on electronic health record data."
Wait, one hospital? Less than 1000 patients, and less then 200 who had covid-19? What if that hospital was located in an area with older demographics? Or younger? Or different in some other medically significant way than the general population? Also, what if the doctors or the policy for treating covid-19 was different than at many hospitals? There was no generally accepted method at first, and when things like "lay them on their chest instead of their back" were discovered, or "ventilators don't really seem to help much", I'm sure they got adopted at different hospitals at different times. I don't know that I would conclude much of anything from a study of this size.