Perioperative Management Considerations for Patients with Suspected MT-ND4 m.11232T>C-Associated Mitochondrial Vulnerability: A Physiology-Guided Narrative Review and Conceptual Framework

Background: Recent clinical reports have described perioperative neurologic complications including delayed emergence, encephalopathy, seizures, basal ganglia injury, and death following general anesthesia in otherwise healthy pediatric and adult patients with maternal Venezuelan ancestry. Emerging genetic data suggest a possible association with the mitochondrial DNA variant MT-ND4 m.11232T>C affecting Complex I of the electron transport chain. Most reported cases have involved exposure to volatile anesthetics, particularly sevoflurane. However, the underlying mechanisms remain uncertain, and no structured perioperative framework currently exists to guide anesthetic management when mitochondrial vulnerability is suspected. Methods: This narrative review synthesizes published case reports, professional society safety communications, mitochondrial disease literature, anesthetic pharmacology, and perioperative physiology to develop a physiology-guided conceptual framework for suspected MT-ND4 m.11232T>C-associated mitochondrial vulnerability. Because the available evidence consists primarily of case reports, institutional observations, and professional society communications rather than prospective clinical studies, the proposed framework is intended to generate hypotheses and inform future investigation rather than establish evidence-based clinical guidelines. Results: The available literature suggests that MT-ND4–associated mitochondrial vulnerability may represent a state of reduced bioenergetic reserve in which cumulative perioperative physiologic stress exceeds ATP production capacity in susceptible individuals. We introduce the Mitochondrial Stress Gradient Model (MSGM), a conceptual framework describing the interaction among anesthetic exposure, physiologic perturbations, inflammatory signaling, and metabolic demand. Building on this model, we propose illustrative anesthetic frameworks emphasizing physiologic optimization, multimodal anesthesia, EEG-guided anesthetic titration, metabolic optimization, regional anesthesia considerations, and structured postoperative neurologic assessment as priorities for future investigation. Conclusions: This framework is intended to support individualized perioperative decision-making and should be interpreted as a physiology-guided conceptual model requiring prospective clinical validation rather than an evidence-based clinical guideline. Although current evidence remains preliminary, the proposed framework emphasizes proportionate physiologic optimization, identifies priorities for future clinical and genetic investigation, and provides a structured foundation for prospective research in this emerging area of perioperative medicine.