Temporomandibular disorders (TMD) patients can present clinically significant jaw pain fluctuations which can be debilitating and lead to poor global health. The Graded Chronic Pain Scale evaluates pain-related disability and its dichotomous grading (high/low impact pain) can determine patient care pathways and in general high-impact pain patients have worse treatment outcomes. Individuals with low-impact TMD pain are thought to have better psychosocial functioning, more favorable disease course, and better ability to control pain, while individuals with high-impact pain can present with higher levels of physical and psychological symptoms. Thereby, there is reason to believe that individuals with low- and high-impact TMD pain could experience different pain trajectories over time. Our primary objective was to determine if short-term jaw pain fluctuations serve as a clinical marker for the impact status of TMD pain. To this end, we estimated the association between high/low impact pain status and jaw pain fluctuations over three visits (≤ 21-day-period) in 30 TMD cases. Secondarily, we measured the association between jaw pain intensity and pressure pain thresholds (PPT) over the face and hand, the latter measurements compared to matched pain-free controls (n = 17). Jaw pain fluctuations were more frequent among high-impact pain cases (n = 15) than low-impact pain cases (n = 15) (OR 5.5; 95% CI 1.2, 26.4; p value = 0.033). Jaw pain ratings were not associated with PPT ratings (p value > 0.220), suggesting different mechanisms for clinical versus experimental pain. Results from this proof-of-concept study suggest that targeted treatments to reduce short-term pain fluctuations in high-impact TMD pain is a potential strategy to achieve improved patient perception of clinical pain management outcomes.
Chronic pain patients often experience different pain trajectories over time1,2. While some individuals report stable pain patterns, others describe wax and wane fluctuations3,4. Clinically significant pain fluctuations are disruptive5 and more debilitating than momentary pain intensity2,6,7, as they result in a sense of lack of control in the patient's life7,8. Indeed, pain fluctuations are associated with higher levels of depression and poor mental health3,6,9,10, catastrophizing7,11, and reduced work efficiency2.
It has been reported that patients with painful temporomandibular disorders (TMD), a common chronic orofacial pain condition affecting the temporomandibular joint and/or muscles of mastication12,13, also present pain fluctuations over time14,15. Clinically significant pain fluctuations, often defined as changes in pain intensity of at least 20 in a 0–100 pain scale16,17, have been identified in TMD case samples in both short-14,14 and long-term19,20 periods. These pain fluctuations are influenced by several factors such as menstrual cycle15,21, weather14, stress22 or treatment modality22,23. While the literature related to pain fluctuations and their determinants is comprehensive for several painful conditions such as rheumatoid arthritis24,25, osteoarthritis4,26,27, and low back pain10,28, our current understanding of chronic TMD pain fluctuations is limited. Understanding the factors that render TMD pain patients at greater risk for clinically significant pain fluctuations and treatment strategies to reduce them may lead to improved quality of life for this patient population.
The Graded Chronic Pain Scale (GCPS) is a widely used instrument to assess pain disability level29, and its dichotomous grading (high/low impact pain)30 can be used to determine patient care strategies and resource allocations31,32, while also characterizing individuals with different psychosocial subtypes33. Indeed, individuals with low-impact TMD pain are thought to have better psychosocial functioning, more favorable disease course34, and better ability to control pain, whereas individuals with high-impact pain present with higher levels of physical and psychological symptoms33. Together, these findings suggest that individuals with low- and high-impact TMD pain experience diverse pain trajectories.
Chronic TMD pain involves both peripheral and central mechanisms35,36, the latter being suggested as predominant in high-impact pain patients32,37. The differential contribution of peripheral and central mechanisms to pain fluctuations in TMD patients is unexplored, and it is possible that clinically significant pain fluctuations are associated with altered quantitative sensory testing (QST) measures that are assumed to assess the peripheral component of the somatosensory system38, such as pressure pain thresholds (PPT). Pressure algometry is considered a reliable, clinically accessible technique to assess bodily deep tissue pain sensitivity38,39, including orofacial structures40,41.
Experimental pain assessed with PPT fluctuates along long-term periods (3–6 months) over the clinical course of painful TMD42. By contrast, PPT fluctuations over shorter periods of time (≤ 3 months) were not correlated with clinical pain ratings while TMD patients underwent conservative treatment43. Neither of the studies investigated if pain impact level was associated with TMD pain fluctuations. Therefore, the association between experimental pain as assessed with PPT and clinical TMD pain ratings in patients categorized by pain impact status remains to be determined.
Our primary objective was to determine if jaw pain fluctuations over three visits in a ≤ 21 day-period serve as a clinical marker of low- or high-impact TMD pain. Secondarily, in order to examine the possible contribution of experimental pain sensitivity to jaw pain fluctuations over time, we estimated the association between jaw pain intensity ratings and PPT over the face and hand in the same period. PPT measures were also compared to matched pain-free controls to have a reference for the normal variability of PPT over the three visits.
Data reported here were collected as part of a parent study conducted at the University of Minnesota School of Dentistry (UMN SOD) assessing somatosensory characteristics and neuroimaging outcomes from participants with chronic TMD pain and pain-free controls44,45. Of the 52 female participants enrolled in the parent study, five had partial data missing which prevented them to be considered for the present study. Thus, a total of 30 females with chronic TMD pain and 17 age-matched pain‐free controls are included. As in other studies of painful TMD46,47,48, only female participants were recruited due to the significantly greater prevalence of TMD in females49. Inclusion criteria for chronic TMD pain cases were: (a) adults (≥ 18 years of age); (b) fulfilment of the diagnostic criteria for temporomandibular disorders (DC/TMD) for myalgia (defined as “pain of muscle origin that is affected by jaw movement, function or parafunction, and replication of this pain occurs with provocation testing of the masticatory muscles”) with or without concurrent arthralgia (defined as “pain of joint origin that is affected by jaw movement, function or parafunction, and replication of this pain occurs with provocation testing of the temporomandibular joint (TMJ)”)12. Specifically, pain location for myalgia should be present over the masseter and/or temporalis muscles area. The presence of concurrent pain over the pre‐auricular area (TMJ) was accepted; (c) pain present for a minimum of 6 months and ≥ 15 days of pain in the previous 30 days.
Age‐ matched pain‐free controls were included if they did not report the presence of any persistent pain condition in the previous 6 months and did not meet the DC/TMD criteria for any of the most common pain‐related TMD (myalgia, arthralgia, headache attributed to TMD). Exclusion criteria for all participants were: (a) current acute pain medication use (e.g., opioids, ibuprofen, acetaminophen) that could not be stopped 24 h prior to testing; (b) conditions/diseases associated with altered pain perception: neurological (e.g., multiple sclerosis, trigeminal neuralgia), major psychiatric disorders, diabetes, neoplasm and cardiovascular disorders; (c) substance abuse; and (d) pregnancy.
The study protocol was approved by the UMN Institutional Review Board, and all methods were performed in accordance with the relevant guidelines and regulations. All participants were informed in detail about the experimental protocol and gave oral and written informed consent before entering the study. Full description of the experimental protocol can be found elsewhere44,45. Briefly, data were collected during three experimental visits, each of them separated by a 2–4 day period which is defined here as “short-term”. In the first visit, participants completed questionnaires assessing several sociodemographic and anthropometric characteristics. In the same visit, all participants underwent a clinical examination in accordance with the DC/TMD criteria12 performed by a trained and calibrated examiner. The two additional experimental visits included quantitative sensory testing and neuroimaging data collection, which were not part of the present study and are not reported further.
Repeated measures were collected at each of the three visits. They included PPT of the face (average PPT of bilateral masseter muscles) and dominant hand (thenar eminence), current jaw pain intensity ratings using a 0–100 numerical rating scale (NRS) and potential confounders for sensory testing (e.g., time of the testing, caffeine intake, medication intake, menstrual cycle).
Sociodemographic, anthropometric and pain characteristics
Most of the sociodemographic data were collected using the DC/TMD Patient History Questionnaire12. As described previously44,45, anthropometric characteristics such as age, height and weight were based on self‐report. Pain characteristics encompassed characteristic pain intensity (0–100) from the graded chronic pain scale (GCPS)29, pain duration since it was first noticed by the patient, total number of body sites (0–45) marked as painful in the last 30 days using a body drawing12 and a comorbidity index based on self‐report for the presence of 18 comorbid conditions (migraine headache, tension-type headache, chronic fatigue syndrome, chronic pelvic pain, chronic low‐back pain, vulvodynia, vulvar vestibulitis syndrome, irritable bowel syndrome, interstitial cystitis, premenstrual dysphoric disorder, neuropathic pain, osteoarthritis, rheumatoid arthritis, obstructive sleep apnea, restless leg syndrome, tinnitus, whiplash and post‐traumatic stress disorder)44,45, in a similar way than other studies aiming to describe comorbid conditions in individuals with TMD13,50.
To collect psychosocial variables, the following valid and reliable instruments from the comprehensive DC/TMD Axis II12 were used; Jaw Function Limitation Scale 20‐items (JFLS-20) for jaw limitation; Patient Health Questionnaire‐9 (PHQ‐9) for depression; Generalized Anxiety Disorder‐7 (GAD‐7) for anxiety; Patient Health Questionnaire‐15 (PHQ‐15) for physical symptoms/somatization; Oral Behavior Checklist (OBC) for oral parafunctions. Additional questionnaires included the Perceived Stress Scale (PSS) for perceived levels of stress51 and Pittsburgh Sleep Quality Index (PSQI) for sleep quality52. The order of questionnaire administration was randomised for each participant to reduce priming effects53 and response bias, e.g., due to fatigue or boredom.
Experimental pain measures
Participants were seated in a comfortable armchair, in a quiet room with an ambient temperature of approximately 23 °C. Sensory testing was performed using a digital pressure algometer (SOMEDIC, Sweden) fitted with a probe (1 cm2 surface area) to deliver blunt pressure with a ramp rate of 50 kPa/s over the thenar eminence of the dominant hand (extra-trigeminal location) and the masseter muscle body (centered within its antero-posterior and supero-inferior dimensions, trigeminal location) in each side. PPT was defined as the pressure in kPa delivered by the pressure algometer which the participants first perceived as painful. Three measurements were taken in each body site and the mean was defined as the PPT for that site. To determine PPT in the face, PPT values of both masseter muscles were averaged, as in previous studies38,44. The pressure algometer was calibrated and maintained periodically according to the manufacturer’s instructions.
Confounders that could influence pain sensitivity responses were recorded54, including starting time for each visit, first day of menses’ onset (if occurring) and caffeine and medications intake in the last 24 h prior to each of the three visits. If occurring, the menstrual cycle phase was determined as previously described55 into the following categories: menstrual, follicular, periovulatory, luteal and premenstrual. Caffeine intake in the last 24 h was divided into three categories: low (< 100 mg/day), moderate (101–200 mg/day) or high (> 201 mg/day)56. Participants were asked to not take any acute pain medications 24 h before sensory testing (e.g., opioids, ibuprofen, acetaminophen) and all other pain medications taken in the last 24 h were recorded to derive a score based on the Medication Quantification Scale (MQS)57.
Dichotomization using the GCPS
The GCPS scoring algorithm allows classification on a 5-point ordinal scale from grade 0 (pain free) to grade IV (high disability, severely limiting). A dichotomized GCPS grade categorization (low: 0–IIa; high: IIb–IV) was calculated for each TMD case to assign them to one of two groups: high-impact (n = 15) or low-impact (n = 15) pain. This method of GCPS score dichotomization has been used in several studies30,32,37,58,59, as it assesses pain intensity and disability by averaging three questions for each with scores ranging from 0 to 10. These scores are then combined with the number of days patients report being prevented from their usual activities in the past 6 months, where high-impact chronic pain could then be aligned with other operational definitions such proposed by the National Pain Strategy, where: “High-impact chronic pain is associated with substantial restriction of participation in work, social, and self-care activities for six months or more”60. As a matter of fact, in this study, the 180 days version of the GCPS was used29. While this version may sustain more pronounced recall bias than shorter versions (i.e., 30 days for obvious reasons), it possibly captures the impact of pain in a wider manner, possibly being more representative of the “usual” pain of the individual.
Clinically significant pain fluctuations
Jaw pain intensity changes of magnitude ≥ 20 in a 0–100 NRS occurring between sequential visits (period 1: visit 1 to visit 2; period 2: visit 2 to visit 3) were considered as positive for pain fluctuations17. Given our focus on short periods of time (2–4 days), fluctuations between visit 1 and visit 3 were not considered. The presence of pain fluctuations for each participant in either period was set as a binary outcome (yes/no). Participants who had pain fluctuations in one or both time periods were categorized as having pain fluctuations, whereas participants who did not experience fluctuation in either period were categorized as not having pain fluctuations.
Anthropometric and sociodemographic characteristics collected at visit 1 are presented as means and standard deviations (SD) for continuous variables. Descriptive statistics determined that these data were not normally distributed. Thus, statistical comparison for these characteristics between two groups were conducted using the Mann–Whitney U test, while three group comparisons were conducted using the Kruskal–Wallis test followed by post-hoc pairwise comparisons. Bonferroni correction for multiple comparisons was done for the main between-group comparisons.
Before conducting analyses for the primary objective, we first conducted exploratory analyses examining the potential confounding influence of patient demographics, psychosocial and clinical characteristics. Variables that were significantly associated with main study outcomes (i.e., jaw pain fluctuations) were retained as covariates in subsequent analyses.
For our primary objective, Pearson’s Chi Square test was used to assess differences in number of cases experiencing pain fluctuations by TMD group. Binary logistic regression was used to calculate the likelihood of TMD cases experiencing pain fluctuations between visits. In this analysis, the presence of pain fluctuations (yes/no) was considered as a dependent variable, while the TMD group category (low-/high-impact pain) was considered as the independent variable. The results of the logistic regression model are presented as odds ratios (ORs) plus 95% confidence intervals (CI). The alpha threshold for statistical significance was set at 0.05.
For the secondary objective, we assessed within- and between-group differences in current jaw pain ratings (high- and low-impact TMD groups) and PPT (high- and low-impact TMD and pain-free controls groups) in the face and in the hand over the three visits. Thus, a linear mixed model for each outcome was performed assuming an auto regressive variance/covariance matrix for time (assuming adjacent time points are more correlated than non-adjacent time points). Main effects for “group” and “visit”, and the interaction between “group” and “visit” were included. Correlations between jaw pain intensity and PPT of the face and hand for the three visits was also assessed using Pearson correlation analyses and linear models. Finally, we assessed the association of jaw pain intensity ratings and PPT for face and hand with potential sensory testing confounders collected at each visit: starting time of the visit (“6:00 to 10:00”, “10:01 to 14:00”, or “14:01 and later”), menstrual cycle phase (no menses, menstrual, follicular, periovulatory, luteal, premenstrual), caffeine intake (none, low, moderate, high) or medication intake (MQS score).
All statistical analyses were performed with R software version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria) and SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA).
Clinical and psychosocial characteristics are reported in Table 1. While age and body mass index were similar between groups (p value = 1.000), both groups of TMD cases differed from controls in several clinical and psychosocial characteristics, suggesting higher psychosocial distress for TMD cases regardless of pain impact status. This difference was more evident between the high-impact TMD pain group and pain-free controls, where greater scores were observed across all domains in the high-impact TMD group, including total number painful body sites and number of comorbidities, jaw functional limitation, depressive symptoms and somatization, oral habits and sleep quality (Table 1). However, no significant differences were observed in anxiety or stress. In the low-impact TMD pain group, the total number of painful body sites, jaw functional limitation, oral behaviors, and somatization scores were significantly higher than pain-free controls. Nonetheless, no significant differences were found between high- and low-impact TMD pain groups for any of those measures except characteristic pain intensity (CPI, p value = 0.013), which was partially expected as it is included in the algorithm to determine GCPS grades 0 to IIb (grades III and IV are determined from other information, regardless of the CPI).
Jaw pain fluctuations at the individual level
Jaw pain fluctuations were observed in 14 out of 30 TMD cases, being more frequent among high-impact TMD cases: 10 out of 15 (66.7%), than those with low disability: 4 out of 15 (26.7%); Chi square (df = 1) = 4.53; p = 0.033 (Fig. 1). Results from the logistic regression revealed that high-impact TMD cases had more than five times higher odds of experiencing pain fluctuations than low-impact TMD cases (OR 5.5; 95% CI 1.2, 26.4). Exploratory univariate analyses did not reveal any potential variable significantly associated with pain fluctuations, except for a positive trend in the association between age and pain fluctuations when used alone in the model (p = 0.079). Based on the importance of age in pain fluctuations as previously reported61,62, we decided to include it as a covariate in the logistic regression model which led to higher odds of pain fluctuations in the high-impact compared to low-impact TMD group (OR 7.4; 95% CI 1.2, 43.5; p value = 0.028).
Jaw pain mean ratings over time
Results from the linear mixed model revealed a significant group and visit interaction (F [2, 56] = 5.45, p = 0.007). Between-group comparisons by visit (Bonferroni-corrected p value cut-off = 0.017) showed significantly greater jaw pain ratings for the high-impact TMD group at visit 1 (t  = − 2.80; p = 0.009) and visit 2 (t  = − 2.7; p = 0.012) but no different than the low-impact TMD group at visit 3 (t  = − 0.57, p = 0.573) (Fig. 2).
PPT means over time
Regarding PPT in the face, the linear mixed model revealed a significant main effect for visit (F [2, 92] = 11.05; p value < 0.001), but the main effect for group was not significant (p = 0.131). The “group” and “visit” interaction effect was also not significant (p = 0.221) (Fig. 3A).
Similar findings were observed for PPT of the hand (Table 2). The main effect for visit was significant (F [2, 92] = 4.41; p value = 0.015) but not for the main effect for group across all visits (p = 0.930) nor the interaction group × visit (p value = 0.803) (Fig. 3B).
Associations between mean jaw pain intensity and mean PPT over time
Univariate correlation analyses between jaw pain intensity ratings, PPT face, and PPT hand for each of the three visits for both TMD groups are shown in Fig. 4. While the correlations between PPT and jaw pain were non-significant in both TMD groups, the low-impact TMD group displayed significant positive correlations between jaw pain ratings for all three visits, with correlation for PPT face in visit 1 and visit 3 (Fig. 4A) surviving Bonferroni correction. In contrast, the high-impact TMD group showed no significant correlations between jaw pain ratings at each visit, yet it had significant positive correlations between PPT for the face and hand across visits with several of them below Bonferroni-corrected p value threshold (Fig. 4B). Results from the linear model including jaw pain intensity and PPT did not reveal any significant associations between jaw pain ratings and PPT of the face (p = 0.968) and the hand (p = 0.071).
Potential sensory testing confounders
Most potential sensory testing confounders tested (menstrual phase, caffeine intake, medication intake) did not differ between the three groups over time, nor were associated with pain-impact status or jaw pain intensity ratings for TMD groups (Supplementary Table S1). For starting time of the visit, significant positive associations were observed with jaw pain intensity ratings across all TMD participants (F [2, 21] = 6.04; p value = 0.009), as later starting times were associated with higher pain intensity (“6:00–10:00” vs. “14:00+”, p value = 0.025; “10:01–14:00” vs. “14:01 or later”, p value = 0.004); however when the model included pain-impact status for TMD participants plus its interaction with visits, the starting time of the visit was no longer significant (p value = 0.738).
The main outcomes from the present proof-of-concept study suggest that individuals with high-impact TMD pain have greater likelihood of experiencing clinically significant pain fluctuations within a short-term period than those categorized as having low-impact TMD pain. Indeed, high-impact TMD cases had 5.5 greater odds of experiencing jaw pain fluctuations relative to low-impact TMD cases, indicating that short-term jaw pain fluctuations may be at least partially associated with greater impact for TMD pain. In addition, we found that jaw pain intensity ratings were not associated with PPT when assessed over trigeminal and non-trigeminal body sites, potentially suggesting dissociated mechanisms underlying fluctuations of ongoing clinical jaw pain and evoked PPT measurements over short-term periods (Fig. 5).
Reports of pain fluctuations over time and their possible determinants have increased in numbers over the last decade to address the need to better understand the pain experience of chronic pain cases in a longitudinal fashion. Several factors have been associated with the presence of clinically significant pain fluctuations in diverse pain conditions. For example, mechanical issues such as knee and hip buckling have been associated with more short-term pain exacerbations in patients with osteoarthritis63,64, while psychological problems such as depression and stress have been independently associated with a higher risk of pain flares in low back pain28. Other factors such as poor sleep quality and heightened stress were also implicated with pain flares in qualitative studies among patients with fibromyalgia65. Moreover, pain fluctuations have also been associated with external factors such as weather65,66 and daily temperature variations67, smoking25 among other reported factors68. Altogether, these findings support the view that the pain experience over time is a highly complex and dynamic process, and teasing apart which factors contribute most to pain fluctuations for a particular individual may assist in developing personalized treatment strategies aimed at reducing those fluctuations and their deleterious effects to global health self-perception.
Several studies have recognized disability (i.e., impairment in daily activities) as not only an important consequence69 of but also a contributor to pain fluctuations in different pain conditions24,70. For instance, it was found that in patients with rheumatoid arthritis the functional disability assessed with the Health Assessment Questionnaire–Disability Index (HAQ-DI) at baseline was independently associated with an increased risk of pain flares over a 12 months period24,70. The GCPS is a widely used instrument to assess the global severity of chronic pain based on its related disability29, and it is probably one of the most frequently used among orofacial pain disorders71,72,73,74. To the best of our knowledge, no previous study investigated the influence of pain-related impact status on short-term jaw pain fluctuations in TMD cases. As stated previously, our results suggest that high-impact TMD pain cases were more likely to experience pain fluctuations than those with low-impact pain observed over a < 21 days period. One possible explanation is that high-impact TMD pain patients present a more “active” state of the disease. TMD is a heterogenous group of muscular and TMJ disorders, which can include inflammation especially when the TMJ is affected. Although our TMD case definition is based on myofascial pain, the presence or absence of arthralgia was not an exclusion criterion, therefore one cannot rule out that different pathophysiological mechanisms that could be related to arthralgia35,75, such as for example inflammation (e.g., due to arthritis)76,77,78, could lead to jaw pain exacerbations. Against this possibility is the fact that the presence of arthralgia was equally present among TMD cases (86.7% in each TMD group). In addition, even though patient pain-impact status were determined prior to the assessment of jaw pain fluctuations, we cannot exclude that chronic and frequent pain fluctuations prior to study enrollment is related to TMD cases reporting greater disability related to jaw pain thus leading them to be categorized as high-impact TMD cases. Future studies will need to address the direction of this association more closely, possibly including different diagnostic subgroups or profiles (i.e., only myofascial pain, only arthralgia, combined myofascial pain and arthralgia, etc.), as their underpinnings and outcomes may differ79,80,81.
Experimental pain assessed by PPT over the face and hand did not show significant associations with clinical jaw pain ratings reported by TMD cases, which is consistent with observations of previous studies43. Similarly, PPT changes over time could not predict the incidence of new onset TMD in the Prospective Evaluation and Risk Assessment (OPPERA) study, likely the largest prospective investigation of TMD incidence published to date42. This lack of association between clinical pain ratings and PPT was also demonstrated for other pain conditions such as fibromyalgia, whiplash, and low back pain82,83,84,85, perhaps suggesting that ongoing clinical pain and evoked pain assessed with PPT likely involve different contribution of peripheral and central pain mechanisms82. However, this remains as an educated conjecture and it needs to be interpreted cautiously within the complexity of the chronic pain conundrum, as for example a recent study found that local PPT only explained a 9% variance in resting (i.e., not provoked) pain ratings85. In addition, there is evidence pointing towards other sources of variability such as the difference between static (e.g., pain threshold) and dynamic (e.g., temporal summation) pain sensitivity ratings, and between movement-evoked pain and traditional clinical pain measures85,86,87, possibly suggesting different underlying mechanisms. In that way, the assessment of pain in TMD in a more exhaustive fashion, also including dynamic tests and motor tasks such as talking, yawning, or chewing becomes highly pertinent in the study of pain fluctuations.
Remarkably, we did not observe a statistically significant difference in PPT between cases and controls, despite low-impact TMD cases presenting numerically lower mean PPT in the face in visits 1 and 2. This finding is in contrast to a body of literature reporting decreased PPT over the masseter muscles in TMD cases when compared to controls88,89,90, however this discrepancy has also been reported previously by others91 and it has been recently suggested that somatosensory amplification may act as confounder for decreased PPT92. We observed that jaw pain ratings across visits were correlated between each other in the low-impact TMD group, while in the high-impact TMD group significant positive correlations were found between PPT across visits (both face and hand sites), which could suggest that pain-related impact status differentially contributes to the longitudinal pattern for clinical and experimental pain in each of these TMD groups. Future studies investigating the association between pain fluctuations using methods that can probe central neural pain mechanisms, such as endogenous pain modulation and neuroimaging may help advance our understanding of the role of pain fluctuations in chronic TMD.
The GCPS is thought to characterize patients suffering from diverse pain conditions and categorize them in a way that improves pain management leading to more efficient care32,59. One potential treatment strategy arising from the classification of TMD patients based on pain-related impact is that treatment strategies focused on self-care recommendations in non-specialist settings may be more appropriate for “functional” TMD patients (low-impact pain), whereas “dysfunctional” TMD patients (high-impact pain) may be better served by adding psychological interventions such as cognitive behavioral therapy in specialist care centers32,33, given their increased report of psychosocial issues93,94. Interestingly, we did not observe psychosocial scores differences between high- and low-impact TMD pain groups (Table 1), as one could originally expect. Whereas both TMD groups presented a higher number of comorbidities and painful body sites, somatization, depressive symptoms, oral habits, jaw limitation and poorer sleep quality than healthy controls, psychosocial measures did not differ between TMD groups. A possible explanation might be the existence of other subgroups and pain disability gradients with TMD cases, as past research observed that differences in psychosocial scores were more pronounced between painful TMD patients with no disability (GCPS grades I and II with no disability points) and high disability (GCPS grades III and IV with 3–6 disability points) when they were categorized into three groups (i.e., no disability, low disability, high disability)33,95. Future studies are needed to determine the presence of different subgroups of TMD cases, possibly using the recently proposed revision of the GCPS (GCPS-R)96, where an additional category in between low- and high- impact pain, such as “bothersome” (moderate to severe pain intensity with lower interference with life activities as per the GCPS-R), could prove to be more specific to capture clinical differences.
This study presents some limitations to be considered. First, it is based on secondary analyses of a parent study that was designed to assess outcomes related to somatosensory characteristics and neuroimaging, so the sample size included was not based on a priori power analysis to detect the effect of the statistical tests at the pre-established significance level of 0.05 for the primary outcomes reported herein. Chronic pain is a complex phenomenon with inherent within and between person high variability, influenced by numerous internal and external variables9,10. In adult musculoskeletal conditions, pain fluctuations are recognized as a complex, multi-layered, whole-body experience events that affect quality of life through different angles that are not only limited to pain and are unique for each individual10,97,98,99. Hence, the limited sample size in this study is unlikely to capture the full complexity of pain fluctuations, and larger studies with increased sample size and experimental visits are encouraged. Second, as only females were included given the higher prevalence of TMD in females, these results might not be generalizable to male TMD cases. Third, a denser sampling of jaw pain ratings would improve the assessment of within-person short-term variability for the included outcomes. Micro-longitudinal studies with daily assessments that may include two or more intra-day measurements can provide more insight about both day-to-day and intra-day symptoms fluctuations in TMD patients. One option is the use of electronic diaries as they can provide measurements of short-term pain changes assessed in a natural environment rather than in experimental settings100,101, thus allowing more adequate “real-life” pain fluctuations estimation and identification of their determinants. Moreover, as mentioned earlier, the use of dynamic sensory tests and motor tasks in addition to static sensory measures is also encouraged.
In conclusion, results from this proof-of-concept study suggest that high-impact TMD pain cases are more likely to experience short-term clinically significant pain fluctuations than those with low-impact TMD pain. These pain fluctuations were not well correlated with PPT fluctuations, suggesting that potentially complex and dynamic diverse mechanisms mediate these short-term variations in the pain experience. Due to the nature of the study, caution is warranted when interpreting these results. Future studies are needed to better understand the role of pain-related impact level and other possible determinants for short-term jaw pain fluctuations among TMD cases, with the goal of developing targeted treatment strategies to reduce their occurrence leading to improved patient perception of clinical pain management outcomes.
Harris, R. E. et al. Characterization and consequences of pain variability in individuals with fibromyalgia. Arthritis Rheum. 52, 3670–3674 (2005).
Hutchings, A. et al. The longitudinal examination of arthritis pain (LEAP) study: Relationships between weekly fluctuations in patient-rated joint pain and other health outcomes. J. Rheumatol. 34, 2291–2300 (2007).
Glette, M., Stiles, T. C., Borchgrevink, P. C. & Landmark, T. The natural course of chronic pain in a general population: Stability and change in an eight-wave longitudinal study over four years (the HUNT Pain Study). J. Pain 21, 689–699 (2020).
Radojcic, M. R. et al. Pain trajectory defines knee osteoarthritis subgroups: A prospective observational study. Pain 161, 2841 (2020).
Parry, E., Ogollah, R. & Peat, G. “Acute flare-ups” in patients with, or at high risk of, knee osteoarthritis: A daily diary study with case-crossover analysis. Osteoarthr. Cartil. 27, 1124–1128 (2019).
Kerns, R. D., Finn, P. & Haythornthwaite, J. Self-monitored pain intensity: Psychometric properties and clinical utility. J. Behav. Med. 11, 71–82 (1988).
Schneider, S. et al. Individual differences in the day-to-day variability of pain, fatigue, and well-being in patients with rheumatic disease: Associations with psychological variables. Pain 153, 813–822 (2012).
Kerns, R. D. & Haythornthwaite, J. A. Depression among chronic pain patients: Cognitive-behavioral analysis and effect on rehabilitation outcome. J. Consult. Clin. Psychol. 56, 870–876 (1988).
Costa, N. et al. Low back pain flares: How do they differ from an increase in pain?. Clin. J. Pain 37, 313–320 (2021).
Khanom, S., McDonagh, J. E., Briggs, M., Bakir, E. & McBeth, J. Adolescents’ experiences of fluctuating pain in musculoskeletal disorders: A qualitative systematic review and thematic synthesis. BMC Musculoskelet. Disord. 21, 645 (2020).
Carriere, J. S. et al. The moderating role of pain catastrophizing on the relationship between partner support and pain intensity: A daily diary study in patients with knee osteoarthritis. J. Behav. Med. 43, 807–816 (2020).
Schiffman, E. et al. Diagnostic criteria for temporomandibular disorders (DC/TMD) for clinical and research applications: recommendations of the International RDC/TMD consortium network* and orofacial pain special interest groupdagger. J. Oral Facial Pain Headache. 28, 6–27 (2014).
Slade, G. D. et al. Painful temporomandibular disorder: Decade of discovery from OPPERA studies. J. Dent. Res. 95, 1084–1092 (2016).
Cioffi, I. et al. Effect of weather on temporal pain patterns in patients with temporomandibular disorders and migraine. J. Oral Rehabil. 44, 333–339 (2017).
Sherman, J. J. et al. Cyclic effects on experimental pain response in women with temporomandibular disorders. J. Orofac. Pain 19, 133–143 (2005).
Dworkin, R. H. et al. Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. J. Pain 9, 105–121 (2008).
Smith, S. M. et al. Interpretation of chronic pain clinical trial outcomes: IMMPACT recommended considerations. Pain 161, 2446–2461 (2020).
Glaros, A. G., Williams, K. & Lausten, L. Diurnal variation in pain reports in temporomandibular disorder patients and control subjects. J. Orofac. Pain 22, 115–121 (2008).
Abou-Atme, Y. S., Melis, M., Zawawi, K. H. & Cottogno, L. Five-year follow-up of temporomandibular disorders and other musculoskeletal symptoms in dental students. Minerva Stomatol. 56, 603–609 (2007).
Nilsson, I. M., List, T. & Drangsholt, M. Incidence and temporal patterns of temporomandibular disorder pain among Swedish adolescents. J. Orofac. Pain 21, 127–132 (2007).
Vilanova, L. S., Goncalves, T. M., Meirelles, L. & Garcia, R. C. Hormonal fluctuations intensify temporomandibular disorder pain without impairing masticatory function. Int. J. Prosthodont. 28, 72–74 (2015).
Robinson, R. C., Garofalo, J. P. & Gatchel, R. J. Decreases in cortisol variability between treated and untreated jaw pain patients. J. Appl. Biobehav. Res. 11, 179–188 (2006).
Turner, J. A. et al. Targeting temporomandibular disorder pain treatment to hormonal fluctuations: A randomized clinical trial. Pain 152, 2074–2084 (2011).
Bechman, K. et al. Flares in rheumatoid arthritis patients with low disease activity: Predictability and association with worse clinical outcomes. J. Rheumatol. 45, 1515–1521 (2018).
Oh, Y. J. & Moon, K. W. Predictors of flares in patients with rheumatoid arthritis who exhibit low disease activity: A nationwide cohort study. J. Clin. Med. 9, 3219 (2020).
Trouvin, A. P., Marty, M., Goupille, P. & Perrot, S. Determinants of daily pain trajectories and relationship with pain acceptability in hip and knee osteoarthritis: A national prospective cohort study on 886 patients. Joint Bone Spine 86, 245–250 (2019).
Wieczorek, M. et al. Trajectory analysis combining pain and physical function in individuals with knee and hip osteoarthritis: Results from the French KHOALA cohort. Rheumatology 59, 3488–3498 (2020).
Suri, P. et al. Do physical activities trigger flare-ups during an acute low back pain episode? A longitudinal case-crossover feasibility study. Spine 43, 427–433 (2018).
Von Korff, M., Ormel, J., Keefe, F. J. & Dworkin, S. F. Grading the severity of chronic pain. Pain 50, 133–149 (1992).
Dworkin, S. F. et al. A randomized clinical trial using research diagnostic criteria for temporomandibular disorders-axis II to target clinic cases for a tailored self-care TMD treatment program. J. Orofac. Pain 16, 48–63 (2002).
Breckons, M., Bissett, S. M., Exley, C., Araujo-Soares, V. & Durham, J. Care pathways in persistent orofacial pain: Qualitative evidence from the DEEP study. JDR Clin. Transl. Res. 2, 48–57 (2017).
Durham, J. et al. Healthcare cost and impact of persistent orofacial pain: The DEEP study cohort. J. Dent. Res. 95, 1147–1154 (2016).
Kotiranta, U. et al. Subtyping patients with temporomandibular disorders in a primary health care setting on the basis of the research diagnostic criteria for temporomandibular disorders axis II pain-related disability: A step toward tailored treatment planning?. J. Oral Facial Pain Headache 29, 126–134 (2015).
Manfredini, D., Favero, L., Gregorini, G., Cocilovo, F. & Guarda-Nardini, L. Natural course of temporomandibular disorders with low pain-related impairment: A 2-to-3-year follow-up study. J. Oral Rehabil. 40, 436–442 (2013).
Harper, D. E., Schrepf, A. & Clauw, D. J. Pain mechanisms and centralized pain in temporomandibular disorders. J. Dent. Res. 95, 1102–1108 (2016).
Moana-Filho, E. J., Herrero Babiloni, A. & Theis-Mahon, N. R. Endogenous pain modulation in chronic orofacial pain: A systematic review and meta-analysis. Pain 159, 1441–1455 (2018).
Breckons, M., Shen, J., Bunga, J., Vale, L. & Durham, J. DEEP study: Indirect and out-of-pocket costs of persistent orofacial pain. J. Dent. Res. 97, 1200–1206 (2018).
Rolke, R. et al. Quantitative sensory testing in the German research network on neuropathic pain (DFNS): Standardized protocol and reference values. Pain 123, 231–243 (2006).
Treede, R. D., Rolke, R., Andrews, K. & Magerl, W. Pain elicited by blunt pressure: Neurobiological basis and clinical relevance. Pain 98, 235–240 (2002).
Castien, R. F., van der Wouden, J. C. & De Hertogh, W. Pressure pain thresholds over the cranio-cervical region in headache: A systematic review and meta-analysis. J. Headache Pain 19, 9 (2018).
Svensson, P. et al. Guidelines and recommendations for assessment of somatosensory function in oro-facial pain conditions—A taskforce report. J. Oral Rehabil. 38, 366–394 (2011).
Slade, G. D. et al. Pressure pain thresholds fluctuate with, but do not usefully predict, the clinical course of painful temporomandibular disorder. Pain 155, 2134–2143 (2014).
Sanches, M. L. et al. Correlation between pressure pain threshold and pain intensity in patients with temporomandibular disorders who are compliant or non-compliant with conservative treatment. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 120, 459–468 (2015).
Moana-Filho, E. J. & Herrero, B. A. Endogenous pain modulation in chronic temporomandibular disorders: Derivation of pain modulation profiles and assessment of its relationship with clinical characteristics. J. Oral Rehabil. 46, 219–232 (2019).
Moana-Filho, E. J., Herrero Babiloni, A. & Nisley, A. Endogenous pain modulation assessed with offset analgesia is not impaired in chronic temporomandibular disorder pain patients. J. Oral Rehabil. 46, 1009–1022 (2019).
Donnell, A. & T DN, Lawrence M, Gupta V, Zieba T, Truong DQ, Bikson M, Datta A, Bellile E, DaSilva AF,. High-definition and non-invasive brain modulation of pain and motor dysfunction in chronic TMD. Brain Stimul. 8, 1085–1092 (2015).
Raphael, K. G. et al. Masticatory muscle sleep background electromyographic activity is elevated in myofascial temporomandibular disorder patients. J. Oral Rehabil. 40, 883–891 (2013).
Vidor, L. P., Torres, I. L., Custodio de Souza, I. C., Fregni, F. & Caumo, W. Analgesic and sedative effects of melatonin in temporomandibular disorders: A double-blind, randomized, parallel-group, placebo-controlled study. J. Pain Sympt. Manag. 46, 422–432 (2013).
LeResche, L. Epidemiology of temporomandibular disorders: Implications for the investigation of etiologic factors. Crit. Rev. Oral Biol. Med. 8, 291–305 (1997).
Miller, V. E. et al. Characteristics associated with high-impact pain in people with temporomandibular disorder: A cross-sectional study. J. Pain. 20, 288–300 (2019).
Cohen, S., Kamarck, T. & Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 24, 385–396 (1983).
Buysse, D. J., Reynolds, C. F. 3rd., Monk, T. H., Berman, S. R. & Kupfer, D. J. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res. 28, 193–213 (1989).
Turk, D. C. & Melzack, R. The measurement of pain and the assessment of people experiencing pain. In Handbook of pain assessment (ed. Guilford, The) 3–16 (Guilford Press, New York, 2011).
Lewis, G. N., Rice, D. A. & McNair, P. J. Conditioned pain modulation in populations with chronic pain: A systematic review and meta-analysis. J Pain 13, 936–944 (2012).
Riley, J. L. 3rd., Robinson, M. E., Wise, E. A. & Price, D. D. A meta-analytic review of pain perception across the menstrual cycle. Pain 81, 225–235 (1999).
Sawynok, J. Caffeine and pain. Pain 152, 726–729 (2011).
Harden, R. N. et al. Medication Quantification Scale Version III: update in medication classes and revised detriment weights by survey of American Pain Society Physicians. J. Pain 6, 364–371 (2005).
Penlington, C., Araujo-Soares, V. & Durham, J. Predicting persistent orofacial pain: The role of illness perceptions, anxiety, and depression. JDR Clin. Transl. Res. 5, 40–49 (2020).
Visscher, C. M. et al. Benefits of implementing pain-related disability and psychological assessment in dental practice for patients with temporomandibular pain and other oral health conditions. J. Am. Dent. Assoc. 149, 422–431 (2018).
Pitcher, M. H., Von Korff, M., Bushnell, M. C. & Porter, L. Prevalence and profile of high-impact chronic pain in the United States. J. Pain 20, 146–160 (2019).
de Koning, E. J. et al. Within-person pain variability and mental health in older adults with osteoarthritis: An analysis across 6 European Cohorts. J. Pain 19, 690–698 (2018).
Parry, E., Ogollah, R. & Peat, G. Significant pain variability in persons with, or at high risk of, knee osteoarthritis: Preliminary investigation based on secondary analysis of cohort data. BMC Musculoskelet. Disord. 18, 80 (2017).
Fu, K. et al. Role of hip injury and giving way in pain exacerbation in hip osteoarthritis: An internet-based case-crossover study. Arthritis Care Res. 71, 742–747 (2019).
Zobel, I. et al. Relationship of buckling and knee injury to pain exacerbation in knee osteoarthritis: A web-based case-crossover study. Interact. J. Med. Res. 5, e17 (2016).
Vincent, A., Whipple, M. O. & Rhudy, L. M. Fibromyalgia flares: A qualitative analysis. Pain Med. 17, 463–468 (2016).
Li, J. et al. Does weather trigger urologic chronic pelvic pain syndrome flares? A case-crossover analysis in the multidisciplinary approach to the study of the chronic pelvic pain research network. Neurourol. Urodyn. 39, 1494–1504 (2020).
Fu, K. et al. Association of weather factors with the risk of pain exacerbations in people with hip osteoarthritis. Scandinav. J. Rheumatol. 50, 68–73 (2020).
Costa, N., Hodges, P. W., Ferreira, M. L., Makovey, J. & Setchell, J. What triggers an LBP flare? A content analysis of individuals’ perspectives. Pain Med. 21, 13–20 (2019).
Christopher-Stine, L. et al. Patient-reported dermatomyositis and polymyositis flare symptoms are associated with disability, productivity loss, and health care resource use. J. Manag. Care Spec. Pharm. 26, 1424–1433 (2020).
Saleem, B. et al. Can flare be predicted in DMARD treated RA patients in remission, and is it important? A cohort study. Ann. Rheum. Dis. 71, 1316–1321 (2012).
Brailo, V. & Zakrzewska, J. M. Grading the intensity of nondental orofacial pain: Identification of cutoff points for mild, moderate, and severe pain. J. Pain Res. 8, 95–104 (2015).
Chung, J. W. et al. Chronic orofacial pain among Korean elders: Prevalence, and impact using the graded chronic pain scale. Pain 112, 164–170 (2004).
Cioffi, I. et al. Social impairment of individuals suffering from different types of chronic orofacial pain. Prog. Orthod. 15, 27 (2014).
De La Torre, C. G. et al. Prevalence of psychosocial impairment in temporomandibular disorder patients: A systematic review. J. Oral Rehabil. 45, 881–889 (2018).
Palmer, J. & Durham, J. Temporomandibular disorders. BJA Educ. 21, 44–50 (2021).
Cairns, B. E. Pathophysiology of TMD pain–basic mechanisms and their implications for pharmacotherapy. J. Oral Rehabil. 37, 391–410 (2010).
Kothari, S. F. et al. Pain profiling of patients with temporomandibular joint arthralgia and osteoarthritis diagnosed with different imaging techniques. J. Headache Pain 17, 61 (2016).
Takeuchi, Y., Zeredo, J. L., Fujiyama, R., Amagasa, T. & Toda, K. Effects of experimentally induced inflammation on temporomandibular joint nociceptors in rats. Neurosci. Lett. 354, 172–174 (2004).
Cao, Y., Yap, A. U., Lei, J., Zhang, M. J. & Fu, K. Y. Subtypes of acute and chronic temporomandibular disorders: Their relation to psychological and sleep impairments. Oral Dis. 27, 1498–1506 (2021).
Yap, A. U., Cao, Y., Zhang, M. J., Lei, J. & Fu, K. Y. Comparison of emotional disturbance, sleep, and life quality in adult patients with painful temporomandibular disorders of different origins. Clin. Oral Invest. 25, 4097–4105 (2021).
Yap, A. U., Cao, Y., Zhang, M. J., Lei, J. & Fu, K. Y. Temporomandibular disorder severity and diagnostic groups: Their associations with sleep quality and impairments. Sleep Med. 80, 218–225 (2021).
Kamper, S. J., Maher, C. G., Hush, J. M., Pedler, A. & Sterling, M. Relationship between pressure pain thresholds and pain ratings in patients with whiplash-associated disorders. Clin. J. Pain 27, 495–501 (2011).
Laursen, B. S., Bajaj, P., Olesen, A. S., Delmar, C. & Arendt-Nielsen, L. Health related quality of life and quantitative pain measurement in females with chronic non-malignant pain. Eur. J. Pain 9, 267–275 (2005).
Palsson, T. S., Christensen, S. W. M., De Martino, E. & Graven-Nielsen, T. Pain and disability in low back pain can be reduced despite no significant improvements in mechanistic pain biomarkers. Clin. J. Pain 37, 330–338 (2021).
Simon, C. B. et al. Static and dynamic pain sensitivity in adults with persistent low back pain: comparison to healthy controls and associations with movement-evoked pain versus traditional clinical pain measures. Clin. J. Pain 37, 494–503 (2021).
Coronado, R. A. et al. Suprathreshold heat pain response predicts activity-related pain, but not rest-related pain, in an exercise-induced injury model. PloS One 9, e108699 (2014).
Rakel, B. A. et al. Predictors of postoperative movement and resting pain following total knee replacement. Pain 153, 2192–2203 (2012).
Carlson, C. R. et al. Psychological and physiological parameters of masticatory muscle pain. Pain 76, 297–307 (1998).
Greenspan, J. D. et al. Pain sensitivity risk factors for chronic TMD: Descriptive data and empirically identified domains from the OPPERA case control study. J. Pain 12, T61-74 (2011).
Svensson, P., List, T. & Hector, G. Analysis of stimulus-evoked pain in patients with myofascial temporomandibular pain disorders. Pain 92, 399–409 (2001).
Quartana, P. J., Finan, P. H. & Smith, M. T. Evidence for sustained mechanical pain sensitization in women with chronic temporomandibular disorder versus healthy female participants. J. Pain 16, 1127–1135 (2015).
Spano, V. E., Imbriglio, T. V., Ho, K. C. J., Chow, J. C. F. & Cioffi, I. Increased somatosensory amplification is associated with decreased pressure pain thresholds at both trigeminal and extra-trigeminal locations in healthy individuals. J. Oral Rehabil. 48, 10–17 (2021).
De la Torre, C. G. et al. Correlation between physical and psychosocial findings in a population of temporomandibular disorder patients. Int. J. Prosthodont. 33, 155–159 (2020).
Manfredini, D., Winocur, E., Ahlberg, J., Guarda-Nardini, L. & Lobbezoo, F. Psychosocial impairment in temporomandibular disorders patients. RDC/TMD axis II findings from a multicentre study. J. Dentistry 38, 765–772 (2010).
Suvinen, T. I. et al. Research Diagnostic Criteria Axis II in screening and as a part of biopsychosocial subtyping of Finnish patients with temporomandibular disorder pain. J. Orofac. Pain 27, 314–324 (2013).
Von Korff, M. et al. Graded chronic pain scale revised: Mild, bothersome, and high-impact chronic pain. Pain 161, 651–661 (2020).
Hewlett, S. et al. “I’m hurting, I want to kill myself”: Rheumatoid arthritis flare is more than a high joint count—An international patient perspective on flare where medical help is sought. Rheumatology 51, 69–76 (2012).
Moverley, A. R., Vinall-Collier, K. A. & Helliwell, P. S. It’s not just the joints, it’s the whole thing: Qualitative analysis of patients’ experience of flare in psoriatic arthritis. Rheumatology 54, 1448–1453 (2015).
Setchell, J. et al. What constitutes back pain flare? A cross sectional survey of individuals with low back pain. Scand. J. Pain 17, 294–301 (2017).
Aaron, L. A., Turner, J. A., Mancl, L., Brister, H. & Sawchuk, C. N. Electronic diary assessment of pain-related variables: Is reactivity a problem?. J. Pain. 6, 107–115 (2005).
Piasecki, T. M., Hufford, M. R., Solhan, M. & Trull, T. J. Assessing clients in their natural environments with electronic diaries: Rationale, benefits, limitations, and barriers. Psychol. Assess. 19, 25–43 (2007).
Research reported in this publication was supported by the National Institute of Dental and Craniofacial Research of the National Institutes of Health under Award Number R00DE027414, and the National Center for Advancing Translational Sciences of the National Institutes of Health Award No. UL1-TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional support was provided by the Office of the Vice President for Research, University of Minnesota.
Funding was provided by National Institutes of Health (Grant No. R00DE027414) and National Center for Advancing Translational Sciences (Grant No. UL1-TR002494).
The authors declare no competing interests.
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Herrero Babiloni, A., Exposto, F.G., Peck, C.M. et al. Temporomandibular disorders cases with high-impact pain are more likely to experience short-term pain fluctuations. Sci Rep 12, 1657 (2022). https://doi.org/10.1038/s41598-022-05598-w