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OBJECTIVE: To assess the efficacy of a novel resorbable hydrogel barrier for preventing postoperative adhesions in animals. METHODS: A hydrogel barrier was formed in situ by photopolymerizing a solution of a macromolecular prepolymer in buffered saline using long-wavelength ultraviolet light. Two models in the rat were evaluated. In a primary adhesion model, devascularization and serosal injury were performed on the uterine horns using bipolar electrocautery. The prepolymer solution was applied to the horns and illuminated to form the barrier. On the seventh postoperative day, the fraction of the length of the horns involved in adhesions was scored, as was the quality of the adhesions. In a readhesion model, adhesions were formed as described and were surgically lysed on the seventh day, then were treated subsequently with the barrier and scored after 7 additional days. Each group in both models consisted of seven animals per treatment condition. Four prepolymer concentrations were examined in the primary adhesion model, and the optimal one was examined in the readhesion model. RESULTS: A conformal hydrogel barrier coating was formed upon in situ photopolymerization and adhered to the treated tissues. No residual hydrogel barrier was observed 7 days after application of the optimal gel concentrations. In the primary adhesion model, the mean fraction of the horns involved in adhesions was reduced significantly, from 76% in controls to 10% (P < .0001), and treatment with a 10% solution of prepolymer was determined to be optimal (P = .025). In the readhesion model, surgical lysis of adhesions alone did not reduce adhesions significantly (from 86% to 79%; P = .3), whereas lysis with barrier treatment did (79% to 28%; P = .002). CONCLUSIONS: In situ photopolymerization allowed the formation of adherent, conformal barriers, which demonstrated high efficacy in the prevention of adhesion formation and reformation in animals. This efficacy and ease of use warrant clinical evaluation. [on SciFinder (R)]
Francesco Stellacci, Matteo Gasbarri, Yong Zhu