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AFRICAN RESEARCH NEXUS

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Predictive Factors of Intraoperative and Early Postoperative Outcome Measures After Anterior Lumbar Interbody Fusions Based on American Society of Anesthesiologists Score

World Neurosurgery, Volume 177, Year 2023

Objective: Anterior lumbar interbody fusion (ALIF) is a surgical treatment that requires a close operative plane to the great vessels, which increases the risk of perioperative complications. To our knowledge, no previous study has investigated the American Society of Anesthesiologists (ASA) Physical Status Classification System as a predictive factor for unfavorable perioperative outcomes in ALIF procedures. We aimed to analyze the ASA score as a predictive factor of intraoperative and postoperative outcomes in patients undergoing ALIFs. Methods: A retrospective chart review was completed at each center to identify a consecutive set of patients who underwent an ALIF. Univariate and multivariate analyses between patients with preoperative ASA scores of ≤2 and >2 were performed to identify predictive factors that may contribute to adverse intraoperative and early postoperative outcomes. Results: Among 210 patients identified, 59 (28.1%) had an ASA score >2 and 151 (71.9%) had an ASA score ≤2. On multivariate analysis, an ASA score >2 was predictive of increased 90-day reoperations (P = 0.02), estimated blood loss (EBL) (P = 0.02), and operative time (P = 0.02). Previous lumbar surgery was predictive of increased length of stay (P = 0.005), EBL (P < 0.001), 90-day readmission (P = 0.02), and operative time (P < 0.001). Posterior supplemental fixation was predictive of increased length of stay (P = 0.04). Increased number of operative levels was predictive of increased EBL (P < 0.001) and operative time (P < 0.001). Perioperative anticoagulation use was predictive of increased EBL (P < 0.001) Conclusions: Increased ASA scores were associated with unfavorable outcomes after ALIF and also can be used as a predictive tool for the risk of reoperations.
Statistics
Citations: 13
Authors: 13
Affiliations: 5
Identifiers
Research Areas
Health System And Policy
Study Design
Cohort Study