General anesthesia refers to the temporary suppression of the central nervous system caused by anesthetic drugs, clinically manifested as loss of consciousness, loss of general pain sensation, amnesia, reflex suppression, and skeletal muscle relaxation. General anesthesia includes sedation (loss of consciousness), analgesia (suppression and reduction of pain response), and immobilization (muscle relaxation), thus the depth of anesthesia reflects the comprehensive state of sedation, analgesia, and immobilization.
Clinically, the depth of anesthesia is often assessed by monitoring the patient’s basic vital signs (heart rate, blood pressure, etc.). Currently, the bispectral index (BIS) and the train-of-four (TOF) stimulation are used to monitor the depth of sedation and muscle relaxation, but there are no objective specific indicators for monitoring the level of analgesia. During general anesthesia, the patient’s consciousness is lost, making it impossible to express the effectiveness of analgesia subjectively; however, pain responses to noxious stimuli persist. Therefore, monitoring the pathophysiological changes caused by pain responses can be used to evaluate analgesic effectiveness. The following is a review of the research progress in monitoring pain responses during general anesthesia.
The International Association for the Study of Pain defines pain as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, often used to refer to such injuries. From the definition, it can be seen that pain is a harmful sensation, including the individual’s subjective experience, and it is an integral whole composed of nociception and pain response, both closely linked.
Nociception is based on the existence of consciousness and is influenced by factors such as sensation, degree of focus, emotion, state of consciousness, and experience. Therefore, it is difficult to objectively measure pain under anesthesia. When noxious stimuli act on the body, in addition to producing subjective sensations of pain, there are also changes in pain response reflected by different pathophysiological activities, such as autonomic nervous function changes affecting heart rate regulation, increased peripheral vascular tension causing reduced perfusion to the extremities, changes in cerebral electrical activity induced by neural impulses in the cerebral cortex, and sympathetic nervous system excitation causing pupil diameter to increase. By analyzing the changes in pain responses, multiple monitoring indicators have been derived to assess the depth of analgesia.
1. Monitoring indicators based on heart rate analysis
1.1 Heart Rate Variability (HRV)
HRV refers to the small fluctuations in instantaneous heart rate between consecutive heartbeats, resulting from the influence of the autonomic nervous system on the sinoatrial node. Parasympathetic nervous system excitation can lower heart rate, quickly affecting heart rate but having a short duration, influencing only a few heartbeats before returning heart rate to its intrinsic frequency. Sympathetic nervous system excitation raises heart rate, and its regulatory effect is slightly slower, affecting multiple consecutive heartbeats. Thus, HRV, as a non-invasive method to assess autonomic nervous system function, can evaluate the balance between sympathetic and parasympathetic nervous systems.
There are various analytical methods for HRV; the frequency domain analysis method is used for monitoring analgesia during general anesthesia. This method takes continuous recordings of electrocardiograms and applies fast Fourier transformation to obtain a heart rate power spectrum with frequency on the x-axis and power energy on the y-axis. The two typical frequency bands are:
① High-frequency band (HF) is 0.15~0.50 Hz, reflecting changes in cardiac vagal activity.
② Low-frequency band (LF) is 0.04~0.15 Hz, influenced by both sympathetic and parasympathetic nervous systems, with sympathetic influence being dominant. Clinically, the LF/HF ratio can reflect the balance between sympathetic and parasympathetic nervous systems.
Research results indicate that in the application of HRV, HF changes correlate with intraoperative pain response changes. In clinical applications, due to significant individual differences in the population and numerous influencing factors on sympathetic and parasympathetic nerves, HRV change trends are currently used as a reference for analgesia but cannot be quantitatively compared. Therefore, relying solely on HRV is insufficient to meet the practical needs of pain response monitoring.
1.2 Analgesia Nociception Index (ANI)
HRV analysis can effectively evaluate autonomic nervous function and reflect changes in pain responses, but it cannot quantify pain responses. To address this, the ANI monitor developed by Lille University in France detects the R-R wave sequence of the electrocardiogram at 250 Hz, performs wavelet transformation on the R-R waves to obtain the high-frequency signal curve of the R-R wave sequence, and assesses parasympathetic nerve tension by calculating the area under the curve (AUC). The ANI ranges from 0 to 100, primarily reflecting the activity of the parasympathetic nervous system. A higher ANI value indicates better analgesia; when the ANI value is <50, it suggests increased sympathetic nerve activity, typically associated with insufficient analgesia.
Regarding the clinical application of ANI, recent research results show that during the induction of general anesthesia and intubation, the ANI value is linearly negatively correlated with hemodynamics. In adult laparoscopic cholecystectomy, ANI can accurately reflect changes in pain responses caused by noxious stimuli; in pediatric surgeries, the guiding significance of ANI for evaluating analgesia depth is superior to hemodynamic indicators. In surgeries for obese adult patients, using ANI to guide analgesia can reduce the use of opioid medications.
2. Monitoring indicators based on peripheral circulation analysis
2.1 Photoplethysmography (PPG)
PPG uses a photodetector to detect the spectral absorption values of oxyhemoglobin and deoxyhemoglobin in tissues and calculates the corresponding arterial blood volume fluctuations in the tissue. The PPG detected by the pulse oximeter probe can reflect the variability of blood volume in the fingertip arteries, with its shape and amplitude resembling the arterial blood pressure waveform and being related to fingertip vascular tone, regulated by the sympathetic nervous system. When sympathetic nervous activity increases, peripheral blood vessels constrict, reducing blood flow and decreasing PPG amplitude; when sympathetic activity decreases, peripheral blood vessels dilate, increasing blood flow and raising PPG amplitude. Therefore, analyzing the amplitude and waveform of PPG can reflect the state of sympathetic nervous activity and achieve the purpose of monitoring pain responses.
In clinical applications, PPG waveforms are correlated with pain responses, but further calculations and analyses are needed to quantitatively assess pain responses using PPG. Recording PPG waveforms at the site of local anesthesia can reflect the vasodilatory effect after local sympathetic nerve block, thereby judging the effectiveness and duration of local nerve block anesthesia. Recent research results indicate that PPG waveforms monitored through the nasal mucosa during surgery have better correlations with pain responses.
2.2 Perfusion Index (PI)
While the PPG waveform can reflect changes in sympathetic nerve tension, it cannot quantify pain responses. PI is an analytical method for PPG, where the PPG waveform detected by the photodetector consists of two parts:
① The pulsatile tissue (changing small arterial blood) absorbs light, known as the pulsatile signal (AC), which is related to fluctuations in arterial blood volume.
② The non-pulsatile tissue (venous blood, muscle, and other tissues) absorbs light, known as the non-pulsatile signal (DC), which typically remains relatively constant; thus, PI = AC/DC × 100%. Insufficient analgesia leads to increased sympathetic nerve activity and vasoconstriction, causing AC to weaken, resulting in a smaller PI value. Therefore, a larger PI value indicates more adequate analgesia, while a smaller PI value indicates insufficient analgesia.
Recent studies on the clinical application of PI show that the PI value during intubation in general anesthesia is related to changes during stimulation at the time of intubation. In patients undergoing sevoflurane intravenous-inhalation combined general anesthesia, the PI value decreases as surgical stimulation increases; when sufficient analgesic medications are administered, the PI value increases as pain responses diminish. In critically ill patients in the ICU subjected to noxious stimuli, the PI value significantly correlates with changes in their behavioral pain scale scores. Postoperatively, in patients in the post-anesthesia recovery room, the PI value significantly correlates with pain VAS scores, indicating good guidance value for assessing the effectiveness of nerve block in alleviating pain. Currently, in clinical applications, variations in PI values among different individuals are significant, and no unified measurement standards for pain response monitoring have been established.
3. Simultaneous analysis of heart rate and peripheral perfusion monitoring indicators
The simultaneous analysis of heart rate and peripheral perfusion monitoring indicator is the Stroke Volume Index (SPI). Both HRV and PPG can reflect the balance between the sympathetic and parasympathetic nervous systems and have been proven to reflect levels of analgesia. In 2007, Huiku et al. conducted a statistical analysis of the relevant variables of HRV and PPG in 60 patients undergoing total intravenous anesthesia, leading to the calculation method for SPI. SPI is calculated from the cardiac interval and pulse wave amplitude monitored by the oxygen saturation probe of the GE anesthesia machine, with the formula SPI = 100 – (0.3 × standard cardiac interval + 0.7 × volume-recorded pulse wave amplitude), with a value range of 0 to 100. A value that is too high indicates insufficient analgesia. GE recommends that the SPI value during surgery should be <50. Currently, in clinical practice, an SPI value of 20-50 is generally accepted.
In guiding the use of analgesic medications during surgery, a meta-analysis showed that compared to traditional analgesic methods, SPI-guided analgesia can reduce the intraoperative use of opioids. However, in a study of laparoscopic cholecystectomy, SPI-guided analgesia required more analgesic medications. The SPI value at the end of surgery showed no significant correlation with postoperative pain severity and could not predict postoperative pain severity based on the SPI value at the end of surgery. In surgeries for children aged 2 to 16 years, the SPI value showed a significant negative correlation with the age of the children.
4. Monitoring indicators based on EEG analysis
4.1 State Entropy (SE) and Response Entropy (RE)
The entropy index for monitoring anesthesia depth involves collecting EEG and frontalis electromyographic signals, using special computational methods to express the electrical signals numerically. Based on the entropy model, two parameters are calculated: SE and RE. SE collects and calculates electrical signals from 0.8 to 32.0 Hz, primarily from EEG, reflecting the sedative component of anesthesia, similar to BIS. RE collects and calculates electrical signals from 0.8 to 47.0 Hz, with signals from EEG and frontalis electromyography, reflecting both sedation and analgesia. SE values range from 0 to 91, while RE values range from 0 to 100, with RE values typically being ≥ SE values. When the body is subjected to noxious stimuli, pain responses increase, leading to an increase in RE, and the difference between RE and SE increases. Clinically, the difference between RE and SE is often used to assess pain responses; when the difference is >5-10, it indicates an increase in pain response and insufficient analgesia depth.
Recent clinical research results show that in general anesthesia with laryngeal mask insertion, the entropy index can effectively reflect pain responses. A study on cardiac surgery showed that when conventional electrode placements were unavailable due to surgical needs, using electrodes pasted under the eye socket for data collection yielded reliable and effective results.
4.2 Analgesia Index
The Analgesia Index is an indicator developed by Beijing Yifei Huadong Company to assess the depth of analgesia. Its basic principle is to collect EEG data from over 10,000 individuals at different levels and identify components associated with analgesia. The EEG data undergoes wavelet transformation, and the normal value range is defined using the 90th percentile, which is then used to assess the patient’s state. The analgesia index ranges from 0 to 100, extracting data related to pain signal transmission from high-frequency bands (gamma band, 40-100 Hz) and low-frequency bands (alpha and beta bands, 8-30 Hz) that exhibit regular repetitive changes, calculating parameters for the brain’s tolerance to pain stimuli.
Currently, developers recommend maintaining an analgesia index value of 40-60 during surgery for patients undergoing general anesthesia; higher analgesia index values indicate stronger pain responses. Research results have shown that during propofol combined with remifentanil general anesthesia, the analgesia index can monitor changes in pain responses, and its trend aligns with the process of noxious stimuli.
4.3 Pain-Related Evoked Potentials (PREP)
PREP refers to the brain evoked potentials generated by pain induced by noxious stimuli on the body. Commonly used stimulation techniques in clinical research include electrical stimulation, laser stimulation, and chemical stimulation. Due to the longer duration of chemical stimulation, electrical or laser stimulation is predominantly used; electrical stimulation activates non-nociceptive Aβ fibers simultaneously when producing pain, leading to less specificity in pain sensation. Therefore, intradermal electrical stimulation can be employed to obtain more reliable pain signals. Laser stimulation can specifically activate nociceptors, making it an ideal pain stimulation technique.
Due to the need for special devices for both electrical and laser stimulation techniques, the application of PREP in clinical settings is limited. Changes in EEG due to pain can be analyzed and calculated to obtain the evoked potential waveform induced by pain stimuli, monitoring pain through waveform changes. Research results indicate that as a tool for evaluating the nociceptive system, there is a significant correlation between PREP amplitude and pain VAS scores in healthy adults. PREP is still in the research phase for standardized stimulation and cannot accurately monitor pain responses induced by noxious stimuli during surgery.
5. Monitoring indicators based on pupil analysis
The monitoring indicator based on pupil analysis is the Pupil Pain Index (PPI), which assesses pain responses through changes in pupil diameter and instability of the pupillary light reflex. PPI is obtained by monitoring pupil diameter while applying 100 Hz electrical stimulation to the forearm, gradually increasing the current from 10 to 60 mA until the increase in pupil diameter exceeds the baseline value by 13%, and then quantifying the recorded current value to obtain a score from 1 to 9. A higher PPI value indicates a stronger pain response; when the PPI value is >4, it indicates insufficient analgesia.
A study on propofol intravenous anesthesia found that PPI could monitor pain responses induced by noxious stimuli even when blood pressure and heart rate had not changed. PPI can also be used to assess pain responses in critically ill patients under sedation. However, changes in pupil diameter under anesthesia are not only related to pain responses but are also influenced by the use of propofol. The miotic effect of opioids can affect PPI monitoring.
6. Conclusion
Monitoring pain responses in patients undergoing general anesthesia is a relatively new research area. With advancements in medical technology, the demands for clinical anesthesia will inevitably increase, and achieving precise analgesia requires mature and reliable pain response monitoring technologies. Under certain conditions, the correlation between existing pain response monitoring indicators and changes in pain responses suggests that they may better guide analgesia than blood pressure and heart rate, but overall research on various pain response monitoring indicators has not yet reached a conclusion. Due to limitations in collection and analysis methods, the following issues need urgent resolution: whether sensitivity to different types of noxious stimuli is the same, whether pain response measurements are consistent across different surgical sites, the extent of individual differences (age, vascular stiffness, neurological dysfunction, etc.) affecting monitoring, and the impact of vasoactive drugs on measurements. In summary, monitoring pain responses during general anesthesia can be partially achieved under certain conditions, but ideal pain response monitoring indicators require further exploration.
Source: Anesthesia Platform
Authors: Zhou Jianwen, Tang Jun
Typesetting: Liu Jiafu
Proofreading: Yu Lishui
Transferred from: Perioperative Medicine Forum