Bayesian networks for Risk Assessment and postoperative deficit prediction in intraoperative neurophysiology for brain surgery.

PURPOSE: To this day there is no consensus regarding evidence of usefulness of Intraoperative Neurophysiological Monitoring (IONM). Randomized controlled trials have not been performed in the past mainly because of difficulties in recruitment control subjects. In this study, we propose the use of Bayesian Networks to assess evidence in IONM. METHODS: Single center retrospective study from January 2020 to January 2022. Patients admitted for cranial neurosurgery with intraoperative neuromonitoring were enrolled. We built a Bayesian Network with utility calculation using expert domain knowledge based on logistic regression as potential causal inference between events in surgery that could lead to central nervous system injury and postoperative neurological function. RESULTS: A total of 267 patients were included in the study: 198 (73.9%) underwent neuro-oncology surgery and 69 (26.1%) neurovascular surgery. 50.7% of patients were female while 49.3% were male. Using the Bayesian Network´s original state probabilities, we found that among patients who presented with a reversible signal change that was acted upon, 59% of patients would wake up with no new neurological deficits, 33% with a transitory deficit and 8% with a permanent deficit. If the signal change was permanent, in 16% of the patients the deficit would be transitory and in 51% it would be permanent. 33% of patients would wake up with no new postoperative deficit. Our network also shows that utility increases when corrective actions are taken to revert a signal change. CONCLUSIONS: Bayesian Networks are an effective way to audit clinical practice within IONM. We have found that IONM warnings can serve to prevent neurological deficits in patients, especially when corrective surgical action is taken to attempt to revert signals changes back to baseline properties. We show that Bayesian Networks could be used as a mathematical tool to calculate the utility of conducting IONM, which could save costs in healthcare when performed.

Intraoperative Sneezing Secondary to Indirect Olfactory Nerve Stimulation.

Sneezing is a poorly understood, protective reflex response. It's characterized by the following sequence: eye closure, inspiration, glottic closure, forced expiration with sudden glottic opening, and release of an elevated intrathoracic pressure creating a flow of explosive air through the nose.1 Studies have indicated an anatomic sneezing area of the brainstem corresponding to the central recipient zone of the nasal sensory neurons in the lateral medulla.2 The traditional pathophysiology of the sneeze is thought to begin by stimulation of the distal branches of the trigeminal nerve within the nasal mucosa. Afferent neural stimuli are transmitted to the trigeminal ganglion and then the lateral medulla. The efferent phase then begins, giving rise to the sneezing sequence described earlier.1 In addition to direct nasal irritation, sneezing has been shown to be triggered by several other causes (Table 1). This suggests that alternative mechanisms of sneeze induction other than direct nasal stimulation exist. We report a case of a 34-year-old man undergoing an awake craniotomy for a recurrent World Health Organization grade 2 oligodendroglioma (IDH-mutant, 1p19q-codeleted, ATRX preserved). During the operation we elicited a sneeze response on 3 occasions on stimulation of the olfactory nerve (Video 1). Although we cannot completely exclude costimulation of the sensory trigeminal terminations in the anterior fossa floor, the actual sneezing occurred during tumor peeling away from the arachnoid surface overlaying the olfactory nerve. This suggests a potential accessory route of sneeze stimulation involving the olfactory nerve distinct from the previously described trigemino-related, autonomic (sympathetic and parasympathetic systems) and psychogenic etiologies.