COVID-19 patients were more likely to die than flu patients this past flu season: study

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Toronto, Ontario (CTV Network) — According to new research published in the Journal of the American Medical Association, people hospitalized with COVID-19 this past flu season were more likely to die than people hospitalized with influenza, especially if they were unvaccinated against the coronavirus.

The study was conducted by researchers Yan Xie, Taeyoung Choi and Ziyad Al-Aly, who all work for the VA St. Louis Health Care System’s Clinical Epidemiology Center, and funded by the U.S. Department of Veterans Affairs. The findings, published on Thursday, were based on data from 11,399 predominantly older male veterans who were hospitalized with COVID-19 or influenza between Oct. 1, 2022, and Jan. 31, 2023.

Xie, Choi and Al-Aly found there were 538 deaths among 8,996 patients hospitalized for COVID-19, and 76 deaths among 2,403 patients hospitalized for influenza. In other words, 5.98 per cent of patients hospitalized for COVID-19 died within 30 days, versus 3.16 per cent of influenza patients. During the study period, the number of patients hospitalized with COVID-19 was between two and three times higher than the number of patients hospitalized for influenza.

“This study found that in a (Veterans Affairs) population in fall (and) winter 2022-2023, being hospitalized for COVID-19 versus seasonal influenza was associated with an increased risk of death,” the authors wrote. Fortunately, they also found mortality rates among people hospitalized with COVID-19 had decreased compared to early in the pandemic, when they were between 17 and 21 per cent in 2020.

“The decline in death rates among people hospitalized for COVID-19 may be due to changes in SARS-CoV-2 variants, increased immunity levels from vaccination and prior infection, and improved clinical care,” they wrote.

“The increased risk of death was greater among unvaccinated individuals compared with those vaccinated or boosted—findings that highlight the importance of vaccination in reducing risk of COVID-19 death.”

METHOD Xie, Choi and Al-Aly used the electronic health databases of the U.S. Department of Veterans Affairs to enroll every person in the database with at least one hospital admission record between two days before and 10 days after a positive test result for SARS-CoV-2 or influenza, and an admission diagnosis for COVID-19 or seasonal influenza. They excluded anyone who had been diagnosed with both.

In analyzing their data, they controlled for variables like age; self-reported race; body mass index; smoking status; prior history of COVID-19 infection; use of long-term care; blood pressure; use of steroids; cancer; cardiovascular, lung and coronary artery disease; dementia; diabetes; HIV and immune dysfunction; liver and peripheral artery diseases; outpatient visits and hospital admissions, number of medications; Medicare usage; date of admission and hospital bed capacity and occupancy.

They assessed the risk of death in people hospitalized with COVID-19 – versus influenza – through inverse probability-weighted Cox survival models. They used a statistical model called logistical regression to generate a propensity score, which they then applied in inverse probability weighting to balance the two groups. They also estimated the absolute risk as the percentage of excess deaths – specifically, the difference in death rates between COVID-19 and influenza groups at 30 days. They also looked at risk in pre-specified subgroups based on age, vaccination status, SARS-CoV-2 infection status and use of outpatient COVID-19 antiviral treatment before admission.

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