Enhanced recovery after distal radius fracture surgery using combined short- and long-acting nerve blocks: A randomized controlled trial

Background: Distal radius fractures are commonly treated under regional anesthesia; however, conventional approaches face limitations, including prolonged motor block with long-acting agents and pain rebound with short-acting agents. Objective: To investigate whether combining a short-acting axillary block with long-acting truncal blocks at the elbow (median and radial nerves) is equivalent to a long-acting axillary block alone for postoperative pain management after distal radius fracture surgery. Study Design: Multicenter, prospective, randomized, open-label, parallel-group, controlled, equivalence trial. Setting: Seven secondary care centers in France. Patients: 150 adults scheduled for wrist fracture osteosynthesis. Interventions: Patients were randomized to a long-acting axillary block alone (BAX-Alone) or a short-acting axillary block combined with long-acting median and radial nerve truncal blocks at the elbow (BAX-Asso). Main Outcome Measures: Pain intensity at motor block resolution (numerical rating scale, 0–10). Results: 128 patients were analyzed (62 BAX-Alone, 66 BAX-Asso). Pain scores at motor block resolution were similar (2.18 ± 2.35 vs. 2.49 ± 3.22; mean difference 0.31, 95% CI −0.69 to 1.31); equivalence was not formally concluded. Motor block recovery was significantly shorter in BAX-Asso (4 [2−6] vs. 15 [10–19] hours, P < 0.001). Block success rates were comparable (91% vs. 98%, P = 0.08), with no difference in opioid consumption or severe pain incidence. Conclusions: Combining a short-acting axillary block with long-acting truncal blocks at the elbow achieves significantly faster motor recovery, while maintaining the quality of postoperative pain relief, offering a clinically relevant advantage in outpatient wrist fracture surgery. Trial Registration: ClinicalTrials.gov, NCT04046744. © 2026 Société Française d'Anesthésie et de Réanimation (SFAR). Published by Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.