Perioperative predictors of complications in open abdominal aortic surgery: A retrospective analysis under a structured perioperative goal-directed therapy protocol
Year: 2025
Type: article
Study design: Observational Study
Abstract: Perioperative goal-directed therapy (PGDT) optimizes hemodynamics in high-risk vascular surgery. However, data on postoperative risk factors and temporal hemodynamic and arterial blood gas (ABG) data patterns within PGDT-managed patients undergoing open elective abdominal aortic surgery (OEAAS) are limited. We conducted an explorative retrospective cohort study of patients undergoing sub-renal OEAAS managed with a structured PGDT protocol from the induction of anesthesia to six hours postoperatively. We collected clinical, hemodynamic, and ABG data at predefined perioperative time points. Patients were stratified by the occurrence of postoperative complications. Differences between groups were evaluated with appropriate tests. Univariate and bivariate Firth logistic regression analyses identified complication predictors, calculating odds ratio (OR) and 95 % confidence interval (95 % CI). Hemodynamic and ABG trends were assessed using the Aligned Rank Transform (ART) test. A p-value < 0.05 was significant. Among 101 patients, postoperative complications occurred in 9.9 %, and the 30-day mortality rate was 4.0 %. Bivariate analysis identified longer surgery time (OR 1.01, 95 % CI 1.00–1.02, p = 0.034), higher postoperative fluid input (OR 1.67, 95 % CI 1.10–3.52, p = 0.016), and more positive fluid balance (OR 4.10, 95 % CI 1.53–16.76, p = 0.002) as associated with complications. ART indicated that patients with complications showed different trends in ScvO 2 (p = 0.031) and lactate (p < 0.001). In patients managed with PGDT, postoperative complications were associated with surgical complexity, positive fluid balance, and markers of impaired oxygen delivery. Monitoring dynamic trends of ScvO₂ and lactate may help identify high-risk patients and guide individualized hemodynamic management.
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid:
OpenAlex ID: W4416889660