The impact of connected devices on postoperative readmission rates after sleeve gastrectomy: a randomized controlled trial
Year: 2026
Type: article
Study designs: Randomized Controlled Trial, Clinical Trial
Abstract: BACKGROUND: Bariatric surgery remains the most effective long-term treatment for obesity, with laparoscopic sleeve gastrectomy (LSG) being one of the most common procedures. Despite advancements in surgical techniques and enhanced recovery protocols, postoperative readmission remains a challenge. This study evaluates whether the use of connected devices (CDs) can reduce early readmission rates after LSG. METHODS: This was a prospective, randomized, monocentric pilot study including 179 patients who underwent LSG between March 2020 and March 2022. Patients were randomized into two groups: (1) CD group (n = 87), discharged 24 hours postoperatively with remote monitoring via connected devices, and (2) non-CD (NCD) group (n = 92), discharged per standard protocol (24-72 hours postoperatively). The primary outcome was the rate of early readmission (within 15 days). Secondary outcomes included patient satisfaction and safety of the monitoring protocol. RESULTS: The early readmission rate was significantly lower in the CD group (2.3%) compared to the NCD group (7.6%; P = 0.04). Remote monitoring allowed for real-time clinical assessment, leading to fewer unnecessary hospitalizations (P = 0.02). Patient satisfaction was high, with 93.1% completing the satisfaction questionnaire, and nearly all patients in the CD group recommending the use of connected devices for postoperative care. CONCLUSION: Remote monitoring using connected devices is a safe and effective strategy to reduce early readmission rates after LSG. Further multicenter studies are needed to validate these findings and explore cost-effectiveness.
Source: International Journal of Surgery
Authors: Sergio Carandina, Viola Zulian, Silvia Ferro, Salvatore Avallone, Antonio Iannelli
Institution: Université Côte d'Azur
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,450
OpenAlex ID: W7130393039