ArticleFrontiers in public health2022
Tree-based, two-stage risk factor analysis for postoperative sepsis based on Sepsis-3 criteria in elderly patients: A retrospective cohort study.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 7 citations in OpenAlex.
- Explainable machine learning algorithms for preoperative risk stratification of urosepsis after retrograde intrarenal surgery.Urolithiasis · 2026Article
- The difference in hematocrit and albumin levels and the risk of sepsis for patients with acute pancreatitis: a retrospective cohort study based on the MIMIC-IV database.Sao Paulo medical journal = Revista paulista de medicina · 2025Article
- The attributable mortality of sepsis for acute kidney injury: a propensity-matched analysis based on multicenter prospective cohort study.Renal failure · 2023Article
- Preoperative hs-CRP/HDL ratio is associated with increased risk for postoperative SIRS in elderly patients: a retrospective cohort study.Aging clinical and experimental research · 2023Article
- Observational
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9 authors at 4 institutions in 1 country.
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Abstract
Background: Sepsis remains the leading cause of postoperative death in elderly patients and is defined as organ dysfunction with proven or suspected infection according to Sepsis-3 criteria. To better avoid potential non-linear associations between the risk factors, we firstly used a tree-based analytic methods to explore the putative risk factors of geriatric sepsis based on the criteria in the study. Methods: Data of 7,302 surgical patients aged ≥ 65 years at the Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were collected. An analytic method that combined tree-based analysis with the method of Mantel-Haenszel and logistic regression was adopted to assess the association between 17 putative risk factors and postoperative sepsis defined by the Sepsis-3 guideline by controlling 16 potential confounding factors. Results: Among the 16 potential covariates, six major confounders were statistically identified by the tree-based model, including cerebrovascular diseases, preoperative infusion of red blood cells, pneumonia, age ≥ 75, malignant tumor and diabetes. Our analysis indicated that emergency surgery increases the risk of postoperative sepsis in elderly patients by more than six times. The type of surgery is also a crucial risk factor for sepsis, particularly transplantation and neurosurgery. Other risk factors were duration of surgery > 120 min, administration of steroids, hypoalbuminemia, elevated creatinine, blood urea nitrogen, hematocrit, platelets, glucose, white blood cell count, abnormal neutrophil-to-lymphocyte ratio and elevated hsCRP-to-albumin ratio. Conclusions: Our study uses an effective method to explore some risk factors for postoperative sepsis in elderly by adjusting many potential confounders and it can provide information for intervention design.
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