Table 1 Clinical characteristic of the study patients.
From: Machine learning approaches overcome imbalanced clinical data for intraoral free flap monitoring
Characteristics | Patients (N=131) |
|---|---|
Age (mean) | 58.1 |
Sex | |
Male | 81 (61.8%) |
Female | 50 (38.2%) |
Primary site | |
Tongue | 47 (35.9%) |
Mandible\(^*\) | 39 (29.8%) |
Maxilla | 11 (8.4%) |
Floor of mouth | 10 (7.6%) |
Buccal mucosa | 7 (5.3%) |
Soft palate | 2 (1.5%) |
Lower gingiva | 1 (0.7%) |
Retromolar trigone | 1 (0.7%) |
Composite | 13 (9.9%) |
Mandible + Skin | 4 |
Mandible + oropharynx | 2 |
Maxilla + Skin | 2 |
Parotidectomy defect | 2 |
Mandible + Base of the tongue | 1 |
Buccal mucosa + Skin | 1 |
Hypopharynx + Skin | 1 |
Free flap | |
Anterolateral thigh free flap | 64 (48.9%) |
Fibula free flap | 45 (34.3%) |
Radial forearm free flap | 22 (16.8%) |
Compromised patients | 10 (7.6%) |
Success in flap salvage | 8 |
Arterial insufficiency | 4 |
Venous thrombosis\(^\dagger\) | 4 |
Total flap loss | 2 |
Arterial insufficiency | 2 |
