Introduction

The global taste for spicy foods is increasing, as demonstrated by an international survey that reported that nearly 70% of respondents listed “spicy” as one of their top three food choices, which fuels a worldwide trend towards greater consumption of spicy foods.1 As such, there is a corresponding increasing scientific interest in spicy foods.2 Our previous study found that a long-term spicy diet can reduce the human basal pain threshold.3 Furthermore, some studies have found that the capsaicin receptor, transient receptor potential vanilloid type1 (TRPV1), is the primary sensory neuron of the “pain” pathway,4,5 as well as the integration of diverse painful stimuli.6 Another study showed that capsaicin is the pungent ingredient in chili pepper and TRPV1 is expressed in taste buds and epithelial keratinocytes throughout the oral cavity.7 However, evidence related to the relationship between a long-term spicy diet and increased pain sensitivity is insufficient, especially in post-surgical populations.

Chronic postsurgical pain (CPSP) is a heightened pain sensitivity that is far more common than other postoperative complications.8 The annual number of surgeries performed worldwide is approximately 320 million.9 The National Bureau of Statistics of China has reported that the number of inpatient surgeries in 2019 exceeded 69.3 million.10 This phenomenon indicates that a considerable number of patients suffer from CPSP, which can continue for months or years after surgery. Although pain is a psychological sensory experience, it is an integrated manifestation of physiological, genetic, and psychosocial backgrounds.11 In terms of postoperative pain, the surgery itself is only a small part of the cause. Therefore, identification of high-risk patients is critical for early intervention in CPSP.8 Many studies have analyzed the risk factors for CPSP11 and established a predictive model of CPSP.12 However, few studies have focused on the relationship between a long-term spicy diet and CPSP.

Women who underwent elective cesarean section (eCS) have relatively consistent characteristics for the investigation of CPSP. The incidence of CPSP after CS is as high as 15%-18.3%.13,14 Therefore, optimizing the perioperative program for the unique CS population to reduce the occurrence of CPSP is a major issue worthy of attention. The purpose of this study was to evaluate the association between long-term spicy dietary habits and the incidence of CPSP after eCS to provide a reference for the identification of high-risk populations and the optimization of perioperative schemes.

Materials and Methods Study Design

This investigation was a prospective cohort study of Chinese patients who underwent eCS at a tertiary referral hospital (the Second Affiliated Hospital of the Army Medical University) in Chongqing, China, from August 20, 2018, to March 5, 2020 (Figure 1). The protocol, including data and statistical analyses, was approved by the Medical Ethics Committee of the Second Affiliated Hospital, Army Military Medical University (approval ID:2018–030-01) before data were accessed. Written informed consent was obtained from all participants before the study. This manuscript adheres to STROBE guidelines.

Figure 1 Trial flow chart.

Participants

The inclusion criteria were patients aged 20–40 years, American Society of Anesthesiologists class II, and singleton full-term pregnant women who underwent eCS. The exclusion criteria included a history of smoking, alcohol and opioid abuse, or chronic dysmenorrhea, use of analgesics in the past three months, history of chronic pain, and lack of cooperation with the research.

Setting

This investigation was an observational study that did not interfere with any clinical decisions. An experienced anesthesiologist and obstetrician implemented a standardized CS under standard spinal anesthesia for each participant. When the patient was hospitalized before CS, sleep quality in the last week and the frequency of spicy food consumption were recorded. Sleep quality was self-reported by the patients and rated on five levels (very bad, bad, general, good, and very good). A numerical rating scale (NRS; 0, never eat, 1:1 day/month, 2:2 days/month, 3:3 days/month, 4:1 day/week, 5:2 days/week, 6:3 days/week, 7:4 days/week, 8:5 days/week, 9:6 days/week, 10:7 days/week) was used to quantify the self-reported frequency of spicy food consumption. At hospital admission, the preoperative Edinburgh Postpartum Depression Scale (EPDS) and Generalized Anxiety Disorder 7-item (GAD-7) questionnaires were administered by a professionally trained researcher in face-to-face interviews. The GAD-7 is a common tool for screening for GAD in general hospitals in China (a GAD-7 score > 9 indicates the presence of GAD).15,16 Patient self-report EPDS is a commonly used instrument for screening perinatal depression.17,18 The recommended cut-off score for screening depressive illness in the Chinese general postnatal population is equal to or greater than 10;18 thus, an EPDS < 10 represents no state of antenatal depression (AD), and an EPDS ≥ 10 indicates a state of AD (no/yes). Other relevant data were collected from the electronic medical record system of the hospital, including age, body mass index (BMI), number of previous CSs, number of previous non-CS surgeries, complications (yes/no), and history of dysmenorrhea (yes/no). The operation duration was obtained from the electronic anesthesia recording system of the hospital. Pain intensity was quantified using an 11-point NRS (0 represents “no pain” and 10 represents “unbearable pain”). The main follow-up item during hospitalization was the incidence of inadequate analgesia (NRS score > 4) within 48 hours after surgery. At three months (± 3 days) and one year (± 7 days) after surgery, follow-up telephone calls were made to every participant to assess the presence of chronic pain. Patients who were not contacted within the time window were considered to be lost to follow-up. Moreover, patients who were lost to follow-up at three months still need to be followed up for one year. The items in the questionnaires mainly contained the following: (1) Do you still have any pain that you could link to your surgery or surgical procedures? (2) Location of the painful area, (3) immediate pain intensity and maximum pain intensity in the past week, (4) pain onset time, (5) duration of pain, (6) feeling of pain, (7) Was your mood affected? (8) Are your sleep quality affected? (9) Was your daily life affected? (10) Did you use analgesics? And (11) Did you seek medical attention? Participants who were lost to the three months follow-up were contacted for a one-year telephone follow-up.

Outcomes

The 11th revision of the International Classification of Diseases defines CPSP as pain developing or increasing in intensity after a surgical procedure, in the area of the surgery, persisting beyond the healing process (ie, at least three months), and that is not better explained by other causes such as infections, malignancies, or pre-existing pain conditions.19 Therefore, the incidence of CPSP three months after eCS was the primary outcome. Participants who answered “yes” to the question, “Do you still have any pain that you could link to a surgery or surgical procedure?” were defined as pain cases. All adverse responses were classified as those without pain.

Considering that CPSP may last longer, we regarded the incidence of CPSP one year after CS as a secondary outcome to observe long-term effects. In addition, other secondary outcomes included the characteristics of pain at three months and one year after CS. Pain features included the pain site (wound, near the wound, intra-abdominal, wound and intra-abdominal, and unlocated), immediate pain intensity and maximum pain intensity in the past week (assessed using the numerical rating scale [NRS]), pain onset time (occasionally, during activities, at nighttime, in the daytime, during rainy weather, and during hot weather), duration of pain (occasionally, last week, last month, and from the operation to the present), feeling of pain (aching, stabbing, cramping, inexplicable, and others), whether it affected the patient’s mood, quality of sleep, or daily life, and use of analgesic drugs or seeking of medical attention.

Statistical Analysis

Stata version 15.0 (StataCorp) and R software (version 3.0.1; http://www.Rproject.org) were used to perform statistical analyses. The “OptimalCutpoints” package in R was used for the receiver operator characteristic (ROC) analysis to determine the cut-off of the NRS scores of the frequency for spicy food consumption. To better understand the relationship between the frequency of spicy food consumption and outcomes, participants were divided into a low-frequency group (NRS < cut-off value, LF group) and a high-frequency group (NRS ≥ cut-off value, HF group). A two-tailed P-value less than 0.05 was considered statistically significant. Data are summarized as the mean (standard deviation), number (frequency), or median (interquartile range). Considering the influence of bias and confounding variables in the observational study, the “MatchIt” package in R was used to perform propensity score matching (PSM) between the LF and HF groups in 1:1 nearest neighbor matching without replacement under a logit model (caliper = 0.2). The propensity score was calculated for the significantly different baseline variables between the LF and HF groups. Before and after PSM, the incidence of CPSP at three months and one year was compared between the two frequency groups. The data of participants who underwent CPSP after PSM were extracted to further investigate the pain features. Chi-square tests, nonparametric tests, Fisher’s exact test, and analysis of variance statistical tests were performed to compare the two groups in terms of categorical and continuous variables. For sensitivity analyses, a stepwise logistic regression analysis was used to screen the optimal model at 10 levels of pe (0.2, 0.1, 0.01, 0.001, 0.0001), pr (0.02, 0.2, 0.1, 0.3), and pe (0.05) pr (0.2) to ensure that the factors included in the model are significant without serious multicollinearity. According to the principle of model selection, the model with the minimum Akaike information criterion (AIC) value and variable number was selected. As we excluded patients with missing essential data from our analysis, we did not impute missing data.

Power Analysis At Three Months After CS

In this study, the incidence of CPSP three months after CS was considered the primary outcome. PASS software version 11.0 (NCSS, Kayesville, UT, USA) was used to calculate power. Group sample sizes of 359 in the HF group and 359 in the LF group after PSM achieved 90% power to detect an odds ratio in the group proportions of 1.75. The proportion in the HF group was assumed to be 0.198 under the null hypothesis and 0.30 under the alternative hypothesis. The proportion of patients in the LF group was 0.1980. The proportion of patients in the LF group was 0.08. The test statistic used is the two-sided Likelihood Ratio test. The significance level of the test was set at P < 0.05.

A logistic regression of a binary primary outcome on a binary independent variable (frequency for spicy consumption) with a sample size of 982 observations (of which 42% are in the group frequency for spicy consumption = 0 and 58% are in the group frequency for spicy consumption = 1) achieves 91% power at a 0.05 significance level to detect a change in Prob(Y=1) from the baseline value of 0.230 to 0.325. This change corresponded to an odds ratio (OR) of 1.610.

At One Year After CS

Group sample sizes of 369 in the HF group and 369 in the LF group after PSM achieved 84% power to detect an odds ratio in the group proportions of 2.02. The proportion in the HF group was assumed to be 0.08 under the null hypothesis and 0.15 under the alternative hypothesis. The proportion of patients in the LF group was 0.08. The two-sided Likelihood Ratio test was used with significance set at P < 0.05.

A logistic regression of a binary response variable on a binary independent variable (frequency for spicy consumption) with a sample size of 1010 observations (of which 42% are in the group frequency for spicy consumption = 0 and 58% are in the group frequency for spicy consumption = 1) achieves 92% power at a 0.05 significance level to detect a change in Prob (Y = 1) from the baseline value of 0.120 to 0.198. This change corresponded to an odds ratio (OR) of 1.810.

Results

Of the 1029 patients enrolled, 47 patients (4.6% [47/1029]) lacked data for the primary outcome, and data from 982 eligible patients were eventually collected at the three months after CS (Figure 1). 19 patients (1.9% [19/1029]) lacked data, and a total of 1010 eligible patients were collected at the one-year mark. Based on the ROC analysis, the cut-off value of the frequency for spicy food consumption was determined to be “NRS = 5”, thus, an NRS score ≥ 5 indicates a high frequency (HF) group for spicy food consumption, and an NRS score < 5 indicates a low frequency (LF) group. The demographic and clinical data for all subjects at three months after eCS are shown in Table 1, and those at one year after CS are shown in Table 2.

Table 1 Demographic and Clinical Characteristics at Baseline for the Data of 3 Months After CS

Table 2 Demographic and Clinical Characteristics at Baseline for the Data of 1 Year After CS

Short-Term Outcomes

The incidence of CPSP at three months after CS was 23.1% (227/982). In the unmatched cohort, we identified 411 patients in the low frequency group and compared them with 571 patients in the high group. As shown in Table 1, the significantly different factors between the LF and HF groups were the occupation (P < 0.001), monthly household income (P < 0.001), sleep quality in the last week before CS (P = 0.003), state of AD (P = 0.001), operation duration (P = 0.023). The propensity score was calculated for all baseline variables. After PSM, in the matched cohort, the analysis compared 359 subjects in the LF group and 359 subjects in the HF group (Table 1). There were no significant differences in the demographic and clinical data between the two groups. The incidence of CPSP at the three months after CS in the HF group (30.1% [108/359]) was significantly higher than that in the LF group (19.8% [71/359], P=0.001, Table 3). To further investigate the pain features, the data of subjects with CPSP (71 in the LF group and 108 in the HF group) after PSM were extracted, with no statistical difference in the baseline data between the two groups. The results are shown in Figure S1. The immediate NRS scores (2 [1, 5]) at three months after CS in the HF group were significantly higher than that (2 [1, 3]) in the LF group (P = 0.018), as were the maximum NRS scores (2 [1, 5]; 2 [1, 4]; P=0.014). There were no significant differences in the other pain characteristics.

Table 3 The Incidence of CPSP Between the Low and High Group

Sensitivity analyses were performed through the stepwise logistic regression. The optimal model filtered is shown in Figure 2. Compared to the low frequency group (NRS < 5), the risk of CPSP in the group of high frequency increased 1.61 times by three months after CS (NRS ≥ 5, OR 1.61, 95% CI 1.18–2.20, P = 0.003). Moreover, the occurrence of insufficient analgesia within 48 h after CS (OR 1.94, 95% CI 1.25–3.01, P = 0.003), fewer CS times in the past (OR 0.75, 95% CI 0.56–0.99, P = 0.04), and younger age (OR 0.96, 95% CI 0.93–1.00, P = 0.03) were also high-risk factors for CPSP at three months after surgery.

Figure 2 Risk factors for the incidence of CPSP at three months after CS (all demographic and clinical data were entered in a step-by-step logistic regression model, and finally the AIC value of the optimal model was 1043.659; R2 = 0.027).

Long-Term Outcomes

The incidence of CPSP at one year after CS was 12.1% (112/1010). In the unmatched cohort, we identified 424 patients in the low frequency group and compared them with 586 patients in the high group. As shown in Table 2, monthly household income (P < 0.001), occupation (P < 0.001), sleep quality in the last week before CS (P = 0.001), state of AD (P = 0.001), and operation duration (P = 0.006) were significantly different between the LF and HF groups. The propensity score was calculated for all baseline variables. After PSM, the analysis compared 369 subjects in the LF group and 369 subjects in the HF group (Table 2). All covariates were not statistically different between the two groups. The incidence of CPSP at one year after CS in the HF group (15.2% [56/369]) was significantly higher than that in the LF group (8.1% [30/369], P=0.003). To further investigate the pain features, the data of subjects with CPSP (30 in the low group and 56 in the high group) after PSM were extracted, with no statistical difference found in the baseline data between the two groups. The results are shown in Figure S2. The onset time of CPSP was significantly different between the two groups (P = 0.02). There were no significant differences in the other pain features. It is worth noting that in the overall population, a total of 15 people (12.3% [15/122]) sought medical advice for CPSP at one year after the operation; however, 0 subjects sought medical advice after three months.

A stepwise logistic regression analysis was also performed, and the optimal model is shown in Figure 3. As the result of 3 months after the operation, the spicy frequency was also a high-risk factor for CPSP at one year. The risk of CPSP in the group with high frequency was 1.81 times higher than that of the low frequency group at one year after CS (OR 1.81, 95% CI 1.20–2.72, P = 0.005). Furthermore, with an increase in BMI (OR 1.06, 95% CI 1.00–1.12, P = 0.04), the risk of CPSP also increased at one year after CS.

Figure 3 Risk factors for the incidence of CPSP at one year after CS (all demographic and clinical data were entered in a step-by-step logistic regression model, and finally the AIC value of the optimal model was 763.7911; R2 = 0.03).

Discussion

With NRS ≥ 5 as a boundary, women who consumed spicy food ≥ 2 days/week were more likely to have CPSP than those who consumed spicy food < 2 days/week, and the maximum degree of pain of CPSP was also significantly higher at three months after eCS. Furthermore, younger age, fewer CSs, and poor postoperative analgesia within 48 hours were risk factors for CPSP at 3 months.

Central sensitization8 and ongoing inflammation11 are two important mechanisms of CPSP. Capsaicin is a classic agonist of the transient receptor potential vanilloid subtype 1 (TRPV1),20 which is the nociceptor and downstream integrator of many inflammatory pathways.21 TRPV1 promotes nociception and neurogenic inflammation by regulating CD4+ T cells22 and enhancing interleukin-4.23 TRPV1 is widely distributed throughout the human gastrointestinal tract.24 Moreover, a study reported that capsaicin injection produced a wide dose-dependent area of hyperalgesia to mechanical stimuli via a central sensitization mechanism.25 This central sensitization induced by TRPV1 has been verified in many animal and human experiments.21,24,26 Therefore, we speculated that ongoing stimulation of TRPV1 via persistent intake of capsaicin through the gastrointestinal tract can result in ongoing inflammation that can sensitize nociceptive neurons, which can promote central sensitization and long-term potentiation to produce hyperalgesia and pain hypersensitivity. Several studies have reported the use of capsaicin-induced analgesia for chronic pain.27 Our previous study also found that a long-term spicy diet can reduce the body’s basic pain threshold.3 This finding may be the reason for the increased incidence of CPSP after CS in people who frequently consumed spicy food in this study, as well as the reason for the higher immediate and maximum pain of their CPSP.

The risks and predictors of CPSP in previous research11,12,14 include age, sex, type of surgery, extent of preoperative pain, acute postoperative pain on movement, preoperative depression, and level of anxiety. Few studies have examined the association between long-term spicy eating habits and CPSP. There have been many studies on the application and exploration of capsaicin in chronic pain management,28 and the capsaicin receptor TRPV1 plays an important role in the mechanism of pain.29 Combined with the results of this study, spicy eating habits are one of the factors that cannot be ignored in the management of CPSP, especially in the context of a global pandemic. Although CPSP occurs far outside the perioperative period, perioperative physicians should continue to optimize perioperative pain management to reduce its occurrence. The comprehensive and accurate recognition of high-risk groups is an advance guard for developing individualized multi-mode pain management programs. The finding that women who frequently consume spicy foods are more likely to experience CPSP and higher pain intensity provides insight for identifying high-risk mothers. In summary, CPSP that occurs after planning surgical events has the potential to be prevented and controlled better in a plan.

This study has some limitations. First, we included a number of risk factors in the analysis for CPSP; other risk factors may exist (eg, gene mutation, degree of nerve injury caused by surgical technique, and preceding pain). Second, the complication is only classified as either “yes” or “no”; thus, a more detailed classification should be performed. Third, our findings were only evaluated in women who underwent eCS and were not generalizable to all patients who undergo other types of surgery or are men. Fourth, whether our findings apply to other ethnic backgrounds and provinces/geographical locations requires further validation.

Conclusion

The incidence of CPSP in women who frequently (≥ 2 days/week) consume spicy food is significantly higher than in women who seldom (< 2 days/week) consume spicy food at three months and one year after CS. The frequency of a personal spicy diet is an important factor in the identification stage, when clinicians optimize management schemes for the complex, multifaceted pain syndrome of CPSP.

Data Sharing Statement

The datasets generated during or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Informed Consent

The study is an observational research adhering to the applicable STROBE guidelines. The protocol including data analysis and statistical plan was approved by the Medical Ethics Committee of the Second Affiliated Hospital, Army Military Medical University (approved ID: 2018-030-01) before data were accessed. All subjects provided written informed consent and the study complied with the Declaration of Helsinki.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This research was supported by the key projects of Chongqing Natural Science Foundation (No. CSTC2019jcyj-zdxmX0001).

Disclosure

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. All named authors take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published. And all authors declare that they have no conflict of interest.

References

1. Spicy foods prefered by over half of people globally. FOODmanufacture.co.uk; 2014. Available from: www.foodmanufacture.co.uk/World-News/Spicy-foods-prefered-by-over-half-of-people-globally. Accessed September7, 2022.

2. Forouhi NG. Consumption of hot spicy foods and mortality–is chilli good for your health? BMJ. 2015;351:h4141. doi:10.1136/bmj.h4141

3. Duan G, Wu Z, Duan Z, et al. Effects of Spicy Stimulation and Spicy-Food Consumption on Human Pain Sensitivity: a Healthy Volunteer Study. J Pain. 2020;21(7–8):848–857. doi:10.1016/j.jpain.2019.11.011

4. Derry S, Rice AS, Cole P, et al. Topical capsaicin (high concentration) for chronic neuropathic pain in adults. Cochrane Database Syst Rev. 2017;1:CD007393. doi:10.1002/14651858.CD007393.pub4

5. Caterina MJ, Leffler A, Malmberg AB, et al. Impaired nociception and pain sensation in mice lacking the capsaicin receptor. Science. 2000;288(5464):306–313. doi:10.1126/science.288.5464.306

6. Frias B, Merighi A. Capsaicin, Nociception and Pain. Molecules. 2016;21(6):797. doi:10.3390/molecules21060797

7. Roper SD. TRPs in taste and chemesthesis. Handb Exp Pharmacol. 2014;223:827–871. doi:10.1007/978-3-319-05161-1_5

8. Glare P, Aubrey KR, Myles PS. Transition from acute to chronic pain after surgery. Lancet. 2019;393(10180):1537–1546. doi:10.1016/S0140-6736(19)30352-6

9. Baker DW. History of The Joint Commission’s Pain Standards: lessons for Today’s Prescription Opioid Epidemic. JAMA. 2017;317(11):1117–1118. doi:10.1001/jama.2017.0935

10. The number of inpatient surgeries in 2019 (National Bureau of Statistics of China). Available from: https://data.stats.gov.cn/easyquery.htm?cn=C01&zb=A0O0A&sj=2020. Accessed September7, 2022.

11. Kehlet H, Jensen TS, Woolf CJ. Persistent postsurgical pain: risk factors and prevention. Lancet. 2006;367(9522):1618–1625. doi:10.1016/S0140-6736(06)68700-X

12. Kalkman JC, Visser K, Moen J, et al. Preoperative prediction of severe postoperative pain. Pain. 2003;105(3):415–423. doi:10.1016/S0304-3959(03)00252-5

13. Weibel S, Neubert K, Jelting Y, et al. Incidence and severity of chronic pain after caesarean section: a systematic review with meta-analysis. Eur J Anaesthesiol. 2016;33(11):853–865. doi:10.1097/EJA.0000000000000535

14. Jin J, Peng L, Chen Q, et al. Prevalence and risk factors for chronic pain following cesarean section: a prospective study. BMC Anesthesiol. 2016;16(1):99. doi:10.1186/s12871-016-0270-6

15. Tong X, An D, McGonigal A, et al. Validation of the Generalized Anxiety Disorder-7 (GAD-7) among Chinese people with epilepsy. Epilepsy Res. 2016;120:31–36. doi:10.1016/j.eplepsyres.2015.11.019

16. He XY, Li CB, Qian J. Reliability and validity of a generalized anxiety disorder scale in general hospital outpatients. Shanghai Arch Psychiatry. 2010;1(4):200–203.

17. Patton GC, Romaniuk H, Spry E, et al. Prediction of perinatal depression from adolescence and before conception (VIHCS): 20-year prospective cohort study. Lancet. 2015;386(9996):875–883. doi:10.1016/S0140-6736(14)62248-0

18. Lee DT, Yip SK, Chiu HF, et al. Detecting postnatal depression in Chinese women. Validation of the Chinese version of the Edinburgh Postnatal Depression Scale. Br J Psychiatry. 1998;172:433–437. doi:10.1192/bjp.172.5.433

19. Treede RD, Rief W, Barke A, et al. A classification of chronic pain for ICD-11. Pain. 2015;156(6):1003–1007. doi:10.1097/j.pain.0000000000000160

20. Conway SJ. TRPing the switch on pain: an introduction to the chemistry and biology of capsaicin and TRPV1. Chem Soc Rev. 2008;37(8):1530–1545. doi:10.1039/b610226n

21. Hanack C, Moroni M, Lima WC, et al. GABA blocks pathological but not acute TRPV1 pain signals. Cell. 2015;160(4):759–770. doi:10.1016/j.cell.2015.01.022

22. Bertin S, Aoki-Nonaka Y, de Jong PR, et al. The ion channel TRPV1 regulates the activation and proinflammatory properties of CD4(+) T cells. Nat Immunol. 2014;15(11):1055–1063. doi:10.1038/ni.3009

23. Stander S, Moormann C, Schumacher M, et al. Expression of vanilloid receptor subtype 1 in cutaneous sensory nerve fibers, mast cells, and epithelial cells of appendage structures. Exp Dermatol. 2004;13(3):129–139. doi:10.1111/j.0906-6705.2004.0178.x

24. O’Neill J, Brock C, Olesen AE, et al. Unravelling the mystery of capsaicin: a tool to understand and treat pain. Pharmacol Rev. 2012;64(4):939–971. doi:10.1124/pr.112.006163

25. LaMotte RH, Lundberg LE, Torebjork HE. Pain, hyperalgesia and activity in nociceptive C units in humans after intradermal injection of capsaicin. J Physiol. 1992;448:749–764. doi:10.1113/jphysiol.1992.sp019068

26. Kim YS, Chu Y, Han L, et al. Central terminal sensitization of TRPV1 by descending serotonergic facilitation modulates chronic pain. Neuron. 2014;81(4):873–887. doi:10.1016/j.neuron.2013.12.011

27. Arora V, Campbell JN, Chung MK. Fight fire with fire: neurobiology of capsaicin-induced analgesia for chronic pain. Pharmacol Ther. 2021;220:107743. doi:10.1016/j.pharmthera.2020.107743

28. Mason L, Moore RA, Derry S, et al. Systematic review of topical capsaicin for the treatment of chronic pain. BMJ. 2004;328(7446):991. doi:10.1136/bmj.38042.506748.EE

29. Szolcsanyi J, Sandor Z. Multisteric TRPV1 nocisensor: a target for analgesics. Trends Pharmacol Sci. 2012;33(12):646–655. doi:10.1016/j.tips.2012.09.002