Cluster-randomized trial evaluates a standardized algorithm's effect on postoperative complications, suggesting potential improvements in care.
Background Esophageal cancer is the sixth leading cause of cancer-related mortality globally. The standard curative treatment for locally advanced esophageal cancer typically involves esophagectomy with gastric-tube reconstruction. Esophagectomy is a complex surgical procedure, associated with a high complication rate. Anastomotic leakage and pneumonia occur with rates of approximately 15% and 25%, respectively, and are the most important contributors to postoperative mortality and morbidity. Current clinical practice demonstrates substantial variability in the diagnosis and management of complications following esophagectomy. The adoption of a standardized algorithm for postoperative care could facilitate earlier detection and intervention of complications, thereby reducing postoperative mortality and morbidity. Methods This nationwide, stepped-wedge, cluster-randomized superiority trial is designed to evaluate the efficacy of a standardized algorithm for postoperative care. Adult patients scheduled for esophagectomy with curative intent will be enrolled. The intervention comprises a consensus-based algorithm that provides daily advice on diagnosis and management of complications. The control group will receive current postoperative care. The primary outcome measure is the incidence of severe complications (Clavien-Dindo grade ≥ 3b) at 90 days postoperatively. Secondary outcome measures include quality of life, the number of re-interventions and length of hospital and ICU stay. 1050 patients will be enrolled in this study across 14 centers. Conclusion Standardized postoperative care after esophagectomy aids early identification and management of complications which may reduce postoperative mortality and morbidity. In the RESCUE trial, a consensus-based algorithm will be implemented nationwide in the Netherlands, which is expected to reduce the incidence of severe complications and enhance patient outcomes.
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Lemmens et al. (2025) studied this question.