Abstract
PURPOSE: This study aimed to assess the impact of different anesthesia methods on postoperative outcomes of lower limb surgeries in elderly patients over 90 years old. PATIENTS AND METHODS: We retrospectively reviewed the medical records of elderly patients over 90 years old who underwent lower limb surgeries at Chongqing University Center Hospital, the Affiliated Hospital of Southwest Medical University, and Chongqing General Hospital from January 2012 to December 2022. The patients were categorized into two groups based on the anesthesia method employed: the general anesthesia (GA) group and the regional anesthesia (RA) group. To minimize potential confounding, propensity score matching (PSM) was conducted in a 1:1 ratio with the caliper value set as 0.1; additionally, further univariable logistic regression was employed to compare the risk of postoperative complications and mortality between the GA and RA groups. RESULTS: A total of 560 patients were included in our analysis, with 363 cases receiving general anesthesia (GA) and 197 cases receiving regional anesthesia (RA). After conducting propensity score matching (PSM), 139 pairs of data were successfully matched. Compared with the RA group, the GA group had a higher risk of postoperative complications (32.4% vs. 19.4%;OR,1.99; 95% CI, 1.15-3.44; p = 0.015), a higher risk of postoperative ICU admission (44.6% vs. 20.9%;OR,3.05; 95% CI,1.80-5.18;p < 0.001), but a lower risk of intraoperative blood transfusion (46% vs. 59%;OR,0.59; 95% CI,0.37-0.95;P = 0.031).No statistically significant differences were observed in other perioperative indices between the two groups. CONCLUSION: In elderly patients over 90 years old undergoing lower limb fracture surgeries, GA is associated with a higher risk of postoperative complications and ICU admission compared to RA. Furthermore, compared with RA, GA is associated with a decreased need for intraoperative blood transfusion. TRIAL REGISTRATION: The study was registered in the Chinese Clinical Trial Registry (ChiCTR2400083103, principal investigator: Hong Fu, 14/04/2024).