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Published on: September 8, 2023
Algorithm for the Treatment of Oronasal Communications: Introducing a Novel Classification
Francesco Arcuri1, Francesco Laganà1, Ferri Andrea2
1Unit of Maxillo-Facial Surgery, IRCCS "Policlinico San Martino", Genoa, Italy.
Introduction:
Breach of the palate leading to a pathological communication between the oral cavity and the nose is known as oronasal communication/fistula (ONC). Various methods for the closure of communications have been reported in the literature, such as obturators, local flaps, and microvascular surgery. Due to the lack of a classification system for ONC, the purpose of this study was to trace an operative algorithm in a group of patients affected by ONC who underwent surgical reconstruction of the oronasal communication.
Methods:
A retrospective study was conducted for all patients affected by ONC who had undergone reconstruction between January 2016 and December 2021 at the University Hospital of Genoa and Parma. Our classification for ONC is based on the extent of the defect; clinical variations range from a defect <2 cm (type I) to a defect that includes both the hard and soft palate (type IV).
Results:
The final study population consisted of 19 patients (11 men and 8 women) with an average age at the time of surgery of 49.2 years (range: 18-78 y). Local flaps were the following: temporalis muscle flap (3 patients), palatal flap (3 patients), Bozola flap (3 patients), facial artery myomucosal flap (2 patients), temporalis fascia flap (1 patient), temporalis fascia flap plus Bichat flap (1 patient), temporalis fascia flap plus pharyngeal flap (1 patient), and Bichat flap (1 patient). Microvascular reconstructive procedures were adopted in 8 cases: forearm free flaps (6 patients), scapular tip plus serratus anterior free flap (1 patient), and serratus anterior free flap (1 patient). At the 1-year follow-up, all patients had no evidence of oronasal communications.
Conclusion:
Reconstructive options for ONC are still opinion-based rather than evidence-based. Our algorithm attempts to bridge this gap together with the latest opinions and trends in the treatment choice.
