aceA Machine Learning Model to Predict Complications Following Head and Neck Microvascular Surgery
Objectives: Microvascular free tissue transfer is the primary reconstructive method in patients with complex defects of the head and neck. Defect site complications vary; incidence ranges from 15% to 70%. The use of machine learning via mutual information analysis has recently been described in the context of head and neck cancer, but this does not distinguish between causal relationships. The current study explores the first causal machine learning model to predict surgical outcomes in patients undergoing head…
A causal machine learning model on 155 reconstruction patients pointed to lower preoperative hemoglobin and albumin as potential causal predictors of complications, which may help risk assessment.
The study is a retrospective chart review from a single institution with 155 patients, and the causal predictors are described only as potential, so they are not confirmed.
Evidence
- Peer-reviewedLaryngoscope Investigative Otolaryngology2026-10-12
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Truvace Impact Record TRV-2026-1378, v1: “A Machine Learning Model to Predict Complications Following Head and Neck Microvascular Surgery.” Truvace, 2026-10-14. /record/TRV-2026-1378 (accessed at citation time). sha256 d417d813639bb8d9…
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