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Published on: February 20, 2021
Predictors of 1-year mortality following discharge from the surgical intensive care unit after sepsis
Anahita Jalilvand1, Tracie Terrana1, Whitney Kellett1
1Division of Trauma, Critical Care, and Burn, Ohio State University, Columbus, OH.
Background:
Postsepsis syndrome is associated with significant long-term mortality. The objective of this study was to determine predictors of mortality within 1 year of discharge from the surgical intensive care unit.
Methods:
We retrospectively reviewed patients admitted to a surgical intensive care unit with sepsis (sequential organ failure assessment score ≥2, 2011-2022). Those who died within 1 year from discharge (n = 171) were compared to survivors (n = 639). Baseline characteristics, sepsis presentation, and hospitalization data were compared. A multiple logistic regression was performed to determine predictors of 1-year mortality after discharge.
Results:
Compared with survivors, those who died were older, less likely to be transferred from another institution (35% vs 46%, P = .003), had more metastatic cancer (9% vs 1%, P < .01), or stage III + chronic kidney disease (16% vs 7%, P < .01). Admission sequential organ failure assessment score, lactate, and vasopressor use were comparable. The 1-year mortality cohort exhibited increased respiratory (15% vs 9%) and abdominal (66% vs 54%) infections (P < .01), median length of stay (29 vs 19, P < .005), renal failure (14% vs 9%, P = .048), and dependent discharge. Adjusted predictors of death included age (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.02-1.05), metastatic cancer (OR 8.0, 95% CI 2.6-25), chronic kidney disease (OR 2.8, 95% CI 1.4-5.6), length of stay (OR 1.02, 95% CI 1.0-1.03), and dependent discharge. A length of stay in the top quartile (>32 days) was associated with a 3-fold increase in postdischarge mortality compared with the lowest quartile (<10 days).
Conclusion:
We identified independent predictors of postdischarge mortality following sepsis, including age, length of stay, dependent discharge, and stage III + chronic kidney disease. These data can identify at-risk patients who can be targeted for closer follow-up.
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