Authors
Ahjin Kim, Youjin Kim, Yeonjeong You, Jiyoung Won, Jin-Yong Cho
Published in
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery. Volume 54. Issue 11. Pages 109855. Aug 15, 2026. Epub Aug 15, 2026.
Abstract
Sublingual hematoma is a rare but life-threatening condition with heterogeneous etiologies that complicate emergency decision-making. This study compared clinical characteristics and management outcomes between implant-induced sublingual hematoma (ISH) and spontaneous sublingual hematoma (SSH), and developed an etiology-guided treatment algorithm through integrated statistical and machine-learning analyses. A systematic literature search through January 2025 identified 77 studies comprising 85 cases (ISH, n = 33; SSH, n = 52). Clinical variables were compared statistically, and random forest and decision tree models were applied to identify determinants of treatment and prognosis. SSH was strongly associated with cardiovascular comorbidities and anticoagulant therapy (84.6% vs 12.1%; p < 0.001), whereas ISH required surgical intervention more often (54.5% vs 13.5%; p < 0.001), with shorter hospital stays (5.3 ± 3.9 vs 10.5 ± 9.8 days). Machine learning identified symptom-to-treatment time and surgical parameters as major predictors for ISH management, while warfarin use and respiratory distress determined SSH severity. These findings indicate that sublingual hematoma requires prompt, etiology-specific management: immediate surgical hemostasis for implant-induced cases and correction of coagulopathy with airway vigilance for spontaneous cases. The proposed framework provides preliminary data-informed guidance for managing this rare but critical condition.
PMID:
42603531
Bibliographic data and abstract were imported from PubMed on 16 Aug 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 5
- Comments 0