Effects of perioperative “Internet+” rehabilitation nursing combined with early nutritional support on postoperative recovery and nutritional status of patients with esophageal cancer
Abstract
Objective: To evaluate the effects of perioperative “Internet+” rehabilitation nursing combined with early nutritional support on postoperative recovery, nutritional status, and secondary psychological outcomes in patients with esophageal cancer. Methods: A total of 135 patients who underwent radical resection of esophageal cancer from January 2022 to December 2023 were selected and assigned to a control group (CG, n = 67) or an observation group (OG, n = 68). The CG received routine nursing plus total intravenous parenteral nutrition, while the OG received “Internet+” rehabilitation nursing combined with early enteral nutrition. Postoperative intestinal function recovery time, length of hospital stay, psychological status (SAS/SDS), quality of life (QLQ-C30), nutritional indicators, immune function, complication rates, and nursing satisfaction were compared between groups. Results: Compared with the CG, the OG demonstrated shorter time to first anal exhaust, first defecation, and hospital stay (P < 0.01). Post-intervention SAS and SDS scores were lower in the OG (P < 0.05), while physical, role, cognitive, emotional, and social functioning scores were higher (P < 0.05). Nutritional markers (TRF, ALB, TP) and immune indices (IgA, IgG, IgM) were significantly higher in the OG (P < 0.05). The OG also showed a lower complication rate and higher nursing satisfaction (both P < 0.05). Conclusion: Perioperative “Internet+” rehabilitation nursing combined with early nutritional support may accelerate postoperative recovery, enhance nutritional and immune function, improve psychological adaptation, and reduce complication rates in esophageal cancer patients. These findings support the clinical value of integrating digital rehabilitation models and structured nutritional pathways into perioperative care.
Copyright (c) 2026 Qianqian Zhu, Weisu Wang, Yunyun Chen
This work is licensed under a Creative Commons Attribution 4.0 International License.
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