JOURNAL ARTICLE

A novel hydrogel-coated chest drain based on ropivacaine-glycerol-alginate hydrogel with construction and application to postoperative thoracic rehabilitation.

  • Published In: Journal of Biomaterials Applications, 2026, v. 40, n. 6. P. 699 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Liao, Sida; Sun, Zijie; Lin, Furong; Liang, Jingyu; Guo, Longmei; Deng, Zixin; Zhang, Xinyao; Zhong, Minghui; Zeng, Jiamin; Long, Bu; Huang, Jiawei; Ji, Wenjin; Lan, Lan 3 of 3

Abstract

This article focuses on the development and evaluation of a ropivacaine-loaded hydrogel-encapsulated chest drain designed to improve postoperative comfort and recovery in thoracic surgery patients. The hydrogel, composed of 2% sodium alginate and 10% glycerol with ropivacaine concentrations between 0.25% and 0.75%, demonstrated favorable morphological characteristics, controlled degradation, sustained drug release, and bacteriostatic effects in vitro. In a rat model using the seldinger method for chest drain implantation, the low-concentration (0.25%) ropivacaine hydrogel showed superior analgesic, anti-inflammatory, and oxidative stress-inhibitory effects compared to higher concentrations, as evidenced by imaging, lung function tests, histological analysis, and superoxide dismutase activity assays. These findings suggest that the modified ropivacaine-alginate hydrogel chest drain may offer a promising local slow-release strategy to enhance postoperative recovery and reduce complications after thoracic surgery.

Additional Information

  • Source:Journal of Biomaterials Applications. 2026/01, Vol. 40, Issue 6, p699
  • Document Type:Article
  • Subject Area:Anatomy and Physiology
  • Publication Date:2026
  • ISSN:0885-3282
  • DOI:10.1177/08853282251369244
  • Accession Number:189507230
  • Copyright Statement:Copyright of Journal of Biomaterials Applications is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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