Analgesia Nociception Index Monitoring in Trigeminal Cardiac Reflex During Nasal Septoplasty

ENT Disease

Analgesia Nociception Index, Trigeminal Cardiac Reflex, Septoplasty

This study aims to evaluate the utility of Analgesia Nociception Index (ANI) monitoring as a predictive and preventive tool for TCR during septoplasty. By comparing standard anesthetic monitoring with ANI-guided analgesia, this research seeks to determine whether maintaining optimal autonomic balance can reduce the incidence of trigeminal cardiac reflex (TCR) and improve intraoperative cardiovascular stability.

Nasal septoplasty is among the most frequently performed otorhinolaryngological procedures and is generally regarded as safe. However, it may occasionally be complicated by autonomic reflexes, most notably the trigeminal cardiac reflex (TCR) . The TCR is a brainstem reflex triggered by stimulation of the trigeminal nerve or its branches, resulting in sudden parasympathetic activation manifested as bradycardia, hypotension, arrhythmias, or even cardiac arrest. Clinically, TCR is typically defined as a decrease in heart rate exceeding 20% from baseline following trigeminal stimulation . The nasal septum is richly innervated by branches of the trigeminal nerve, particularly in the posterior septal region and near the sphenopalatine area. Surgical manipulation during septoplasty, including mucoperichondrial flap elevation, septal correction, and spur removal, can therefore precipitate TCR. Reported incidence rates of TCR during nasal surgery vary widely in the literature, ranging from approximately 15% to 25%, depending on surgical technique, anesthetic depth, and patient-related factors. Although most episodes are transient and reversible, unanticipated bradycardia can lead to hemodynamic instability and interruption of surgery, underscoring the importance of early detection and prevention . Traditionally, anesthesiologists rely on conventional hemodynamic parameters such as heart rate and blood pressure to assess autonomic responses and anesthetic adequacy . However, these parameters represent relatively late manifestations of vagal activation. By the time a significant decrease in heart rate is observed, the trigeminal cardiac reflex has already occurred. Therefore, a monitoring modality capable of detecting early changes in autonomic balance before overt bradycardia develops would be of considerable clinical value . The Analgesia Nociception Index (ANI) is a non-invasive monitoring tool derived from heart rate variability analysis, reflecting the balance between sympathetic and parasympathetic activity. ANI primarily reflects parasympathetic tone, with values ranging from 0 to 100. Higher values indicate parasympathetic predominance, whereas lower values suggest sympathetic activation or inadequate analgesia. Maintaining ANI values within a target range (commonly 50-70) has been proposed as a strategy to optimize intraoperative analgesia and autonomic stability. Given that TCR is mediated by sudden parasympathetic overactivity, continuous ANI monitoring may provide an early warning signal of impending reflex activation . A sudden drop in ANI could theoretically precede the hemodynamic manifestations of TCR, allowing timely anesthetic or surgical interventions to prevent or attenuate the reflex. Despite its growing use in anesthesia practice, the role of ANI monitoring in predicting and preventing TCR during nasal septoplasty has not been adequately studied. Data analysis will be carried out using SPSS (IBM SPSS Statistics) and/or R. Continuous variables will be expressed as mean ± standard deviation (SD) when normally distributed, or as median with interquartile range for nonnormally distributed data. Categorical variables will be summarized as frequencies and percentages. A p-value of less than 0.05 (two-tailed) will be considered statistically significant. Group comparisons will be conducted using: Independent samples t-test for normally distributed continuous data, Mann-Whitney U test for skewed continuous data, Chi-square test or Fisher's exact test for categorical data

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