Real-time cardiorespiratory coherence detects antinociception during general anesthesia

Nociception monitoring tools using autonomic tone changes for intraoperative analgesic guidance in pediatric patients

Nociception monitoring devices using changes in autonomic nervous system activity have been developed in numerous ways. Although there have been few studies conducted on children, compared to the relatively higher number of studies on adults, most of the nociception monitors in children, as in adults, appear to be more useful than the standard clinical practice that uses hemodynamic parameters in the evaluation and treatment of intraoperative nociception (pain) during general anesthesia. Particularly, when monitoring the surgical pleth index (SPI) in anesthetized children, the application of a new target range of SPI values (≤ 40) to the SPI monitoring criteria seems to be necessary for providing a more proper intraoperative analgesia. The analgesia nociception index (ANI) shows promising results in anesthetized adults, and recently, positive results along with cardiorespiratory coherence have been reported in pediatric patients. Newborn infant parasympathetic evaluation (NIPE) could be useful for providing adequate analgesia in newborns, infants, and children under 2 years of age in anesthetized or awake states. In cases of skin conductance and pupillometry, further studies are needed. Understanding the pros, cons, and limitations of these nociception monitoring tools will provide more effective and safe intraoperative analgesia to pediatric patients undergoing general anesthesia, and it may also help to plan and conduct promising research on the use of perioperative nociception monitoring in pediatric patients in the future.

Real-time cardiorespiratory coherence is blind to changes in respiration during general anesthesia

PURPOSE

A novel real-time cardiorespiratory coherence (CRC) algorithm has been developed to monitor nociception during general anesthesia. CRC uses custom designed filters to track and analyze the respiratory sinus arrhythmia (RSA) as it moves in time and frequency. CRC is a form of sensor fusion between heart rate and respiration, estimating the strength of linear coupling between the two signals. The aim of this study was to estimate the effect of changes in respiration rate (RR) and peak airway pressure (PPaw) on CRC. The response of CRC was compared to a prior offline wavelet-based algorithm (WTCRC) as well as traditional univariate heart rate variability (HRV) measures. A nociception index was created for each algorithm, ranging from 0 (no nociception) to 100 (strong nociception).

METHODS

Following ethics approval and informed consent, data were collected from 48 children receiving general anesthesia during dental surgery. The times of change in RR and PPaw events were noted in real-time. A total of 43 RR and 35 PPaw change events were analyzed post hoc in pseudo real-time. The nociception index averages were compared between a baseline period and a response period around each event. A Wilcoxon rank-sum test was used to compare changes.

RESULTS

The change in RR changed the CRC nociception index by an average of -2.2 [95% CI from -10 to 4.7] (P > 0.3), and the change in PPaw changed the CRC nociception index by an average of 5.4 [-1.0 to 11] (P > 0.1). The changes were smaller than those of many traditional HRV measures.

CONCLUSIONS

Real-time CRC was blind to the changes in respiration, and was less sensitive than many of the traditional HRV measures. A nociception index based on CRC can thus function across a wider range of respiratory conditions than can many traditional univariate HRV measures. The real-time CRC algorithm shows promise for monitoring nociception during general anesthesia.