Section 1
The nociceptive and pain-modulatory pathways enable the brain to regulate pain
sensations through both inhibitory and excitatory processes [ 1 ]. One of the
outputs of the central nervous system (CNS) to modulate pain is the endogenous
pain modulation (EPM). Abnormal EPM, either increased pain facilitation and/or
impaired pain inhibition, might be associated with the genesis of several chronic
pain mechanisms [ 2 , 3 ]. EPM can be assessed by using psychophysical methods, such
as temporal summation of pain (TSP) and conditioned pain modulation (CPM) [ 4 ].
TSP evaluates facilitatory modulation through the changes in pain perception
caused by a series of repeated noxious stimuli [ 4 , 5 ]. CPM is a paradigm used to
assess the pain inhibition pathway based on the “pain inhibits pain” theory
[ 6 ].
Temporomandibular disorders (TMD) are a collective term for a heterogeneous
condition of musculoskeletal disorders involving pain and/or functional
limitations in the masticatory muscles, temporomandibular joints (TMJ), and
associated structures in the orofacial region [ 7 , 8 ]. Multiple studies have
assessed pain facilitation and modulation in TMD patients in both trigeminal and
non-trigeminal areas. Some studies reported higher sensitivity to noxious stimuli
in TMD patients compared with healthy controls [ 9 , 10 ]. In addition, certain
studies reported lower pain thresholds [ 11 , 12 ] and increased TSP in TMD patients
when tested outside the trigeminal nerve region [ 13 ]. In contrast, another study
found no significant difference in pain thresholds outside the painful area [ 14 ].
Regarding CPM responses, TMD cases produced impaired CPM at extra-segmental sites
compared with controls [ 15 , 16 ]. In other studies, however, no significant change
in the CPM effect was found at pain-free sites between those with and without TMD
[ 17 , 18 ].
Migraine is a head pain frequently characterised by unilateral throbbing pain
and a variety of neurological and autonomic symptoms, including hypersensitivity
to light, sound, smell, nausea, cognitive, emotional, and motor disturbances
[ 19 ]. Studies regarding the investigation of CPM efficiency in migraine patients
have reported mixed results. A preliminary study showed disrupted descending pain
modulation in both episodic and chronic migraine [ 20 ], while other CPM studies
indicated that migraine patients typically show only mild or absent inhibitory
responses, comparable to those in controls [ 21 ].
Fibromyalgia is characterised by widespread musculoskeletal pain, tenderness,
and heightened pain sensitivity, often accompanied by other symptoms, such as
fatigue, sleep disturbances, and cognitive issues [ 22 ]. CPM responses in
individuals with fibromyalgia have been somewhat inconsistent. Some studies, on
one hand, have suggested that individuals with fibromyalgia exhibit impaired CPM
responses [ 23 ]. On the other hand, other research has reported normal [ 24 ] or
even enhanced CPM responses in fibromyalgia patients [ 25 ].
TMD is associated with several comorbidities, particularly migraine and
fibromyalgia. The three pain conditions have been associated with impaired
EPM and they occasionally coexist in some patients. To date, no studies have
measured the EPM system in TMD patients with comorbid migraine and fibromyalgia.
Considering previous findings, we hypothesised that TMD patients with
comorbidities may exhibit greater EPM impairment in the non-trigeminal innervated
area compared with TMD patients without comorbidities. Therefore, this study
aimed to investigate EPM in TMD patients with comorbid migraine and fibromyalgia
(FM) in a non-trigeminally innervated area.
Section 2
A previous meta-analysis, which encompassed 9 studies exploring pain modulation
in chronic orofacial pain, these studies comprised 14 to 58 samples within their
respective groups, with an average sample size of 20 to 30 participants. The
findings from these studies demonstrated compromised pain modulation in patients
compared with control groups [ 13 ]. A power analysis was conducted using G*Power
version 3.1.9.4 (Heinrich-Heine-Universität Düsseldorf, Düsseldorf,
NRW, Germany) to ascertain the minimum sample size essential for testing the
study hypothesis. The results indicated that to achieve 80% power for detecting
a medium effect, at a significance level of α = 0.05, a total sample
size of N = 269 was necessary, equating to 54 individuals per group. Hence,
considering insights from previous studies and the power analysis calculation, it
was recommended to conduct the study with a sample size ranging from 15 to 54
participants per group. Ultimately, the study succeeded in enrolling a total of
135 participants, which were 30 participants in four groups and 15 participants
in one group.
Participants were recruited between May 2021 and December 2023 from Orofacial
Pain Clinic, King’s College Dental Institute and Headache Clinic at St Thomas’
Hospital. Ethical approval for the study was obtained from the Health Research
Authority (Approval No: 21/WS/0050). Informed consent was mandatory prior to
participation.
Participants were recruited into five groups based on history and clinical
examination:
● TMD: chronic myogenous painful TMD patients. TMD diagnosis was based
on the 1st edition of International Classification of Orofacial Pain, 1st edition
(ICOP) for primary myofascial orofacial pain [ 26 ] and TMD pain presented for more
than 3 months.
● Migraine (MG): chronic migraine patients. Chronic migraine diagnosis
followed the 3rd edition of the International Classification of Headache
Disorders (ICHD-3) [ 19 ].
● (TMD + MG): chronic myogenous painful TMD patients with chronic
migraine.
● (TMD + MG + FM): chronic myogenous painful TMD pain patients with
comorbid migraine and fibromyalgia. Fibromyalgia diagnosis aligned with the
American College of Rheumatology (ACR) criteria [ 22 ].
● Healthy participants.
The study was inclusive of individuals aged between 18 and 50 years complying
with specific inclusion and exclusion criteria. This selection aimed to mitigate
the influence of confounding factors related to the experimental protocol [ 3 ] and
the participant characteristics [ 27 , 28 , 29 ] in the context of the CPM paradigm.
● Presence of systemic comorbidities and psychological disorders, for
example, fibromyalgia, systemic myofascial pain and chronic fatigue syndrome,
chronic headaches, migraines, heart arrhythmias, endometriosis, interstitial
cystitis, irritable bowel syndrome, lower back pain, autoimmune diseases, and
sleep disorders or diabetes mellitus.
● Diagnosis of medication overuse for headache, and use nonsteroidal
anti-inflammatory drugs (NSAIDs) or paracetamol within 12 hours before the
experiment.
● Smoking more than five cigarettes daily.
● Consuming over 6 cups of caffeinated drinks daily.
● Indications of substance abuse.
● Alcohol consumption within 24 hours before the experiment.
● Irregular menstrual cycles in the case of female participants.
The study was divided into three parts, as follows:
Part 1: Mechanical detection threshold (MDT) and pressure pain threshold (PPT).
Part 2: Mechanical Temporal Summation (MTS) and decay of after-sensations.
Part 3: Conditioned Pain Modulation Protocol (CPM).
To measure mechanical detection threshold (MDT), von Frey Filaments
(Semmes-Weinstein) were administered on both the painful site and the hands. The
procedure began with the application of a filament with an initial force of 0.008
grammes (0.08 mN). With eyes closed, participants were asked to indicate when
they first sensed the touch. The MDT with von Frey Filaments is a standard tool
for assessing tactile and mechanical pain thresholds. High test-retest
reliability has been reported (intraclass correlation coefficients (ICC)
0.76–0.98), though some studies note only moderate reproducibility (Kappa
<0.6), influenced by examiner training, site, and protocol [ 30 , 31 ].
Subsequently, the pressure pain threshold (PPT) was assessed by a pressure
algometer (Pressure algometer, Wagner Pain Test™, Wagner
Instruments, Greenwich, CT, USA) at the same locations. The PPT by algometry
showed high intra- and inter-rater reliability, with excellent concurrent
validity between digital and analogue devices (ICC 0.82–0.99) [ 32 ]. Pressure was
manually increased at a rate of 30 kPa per second until participants reported
feeling the first sensation of pain. Each stimulation was repeated three times
and then the average force was calculated.
The MTS was performed to evaluate pain facilitation (Fig. 1 ). The test was
conducted according to the Deutscher Forschungsverbund Neuropathischer Schmerz
(DFNS) standardised protocol [ 33 ] by using weighted pinprick stimulators
(Pinprick Stimulator, MRC Systems GmbH, Heidelberg, BW, Germany). Employing the
recommended force of 256 mN for the hand [ 34 ], a pinprick stimulus was applied
over the volar part of the forearm of the dominant hand. The stimulator was
positioned vertically, perpendicular to the testing surface, and a single
pinprick stimulus was administered. This stimulus was repeated three times, each
with a 10-second interval. After each pinprick test, patients were asked to rate
the painful sensation on a numerical pain scale (NPS) of 0 to 100, where 0
represents no pain and 100 signifies the maximum imaginable pain. After a single
pinprick test, this was followed by a train of 10 successive stimuli, 3 cycles of
the same force and repeated at a 1/s rate (1 Hertz). The repetition of stimuli
was concentrated within a confined area of 1 cm 2 . After every 10 stimuli,
patients were asked to rate the degree of painful sensation on a numerical pain
scale. Subsequently, the wind-up ratio (WUR) was computed by dividing the mean
rating of the three series of 10 stimuli by the mean rating of the three
individual stimuli. The MTS has demonstrated good to excellent
test-retest reliability in both healthy and clinical populations. For example,
ICC values range from 0.80–0.91 in healthy subjects (hand/back sites) using 2–3
repeated measurements [ 35 ], 0.73–0.89 in low back pain patients [ 36 ], and
0.63–0.86 in shoulder pain cohorts [ 37 ].
Overview of mechanical temporal summation and conditioned pain
modulation protocol.
Each participant underwent the CPM paradigm (Fig. 1 ); the pinprick stimulator
used in the MTS test served as a test stimulus in the CPM test, while cold water
served as the conditioning stimulus (CS). This specific cold water conditioning
stimulus aligned with the recommendations from the CPM guidelines [ 38 ]. The
selection of a 10 °C intensity followed a precedent set by a previous
protocol and has been validated as effectively inducing a CPM effect through
corroborating studies [ 39 , 40 ]. Cold water was prepared within an insulated ice
bucket, and its temperature was measured with a digital thermometer. Participants
were requested to immerse their nondominant hand in cold water at wrist level.
Blood pressure and pulse rate were measured at the 20-second mark. At the
30-second point during the immersion, the MTS procedure was applied using the
same protocol as previously described, but targeting a different area on the same
hand. CPM magnitude was calculated as the difference of pain intensity report
during the hand immersion in cold water and pain intensity report without hand
immersion from the MTS test (CPM = MTS with conditioning pain score − MTS without
conditioning pain score). A negative CPM value indicated a decrease in pain
response to the TS when a simultaneous CS is applied. The % CPM effect was
calculated by determining the percentage reduction in pain perception caused by
the conditioning stimulus compared to the baseline stimulus. The formula used
was: % CPM effect = ((baseline pain − conditioning stimulus pain)/baseline pain) × 100. A higher % CPM effect
indicated a stronger pain modulation response, meaning the body is better at
inhibiting pain perception in response to the conditioning stimulus. For the
validity and reliability of CPM, a meta-analysis reported good intra-session
reliability (ICC 0.64–0.77 in healthy subjects; ICC 0.77 in patients), but only
fair inter-session reliability (ICC 0.44–0.59), depending on test and
conditioning stimuli [ 41 ].
To determine an efficient CPM, two approaches were used to determine the % CPM
threshold. Firstly, a review conducted by Pud et al . [ 42 ] revealed that
the expected reduction in pain sensitivity corresponding to the Diffuse Noxious
Inhibitory Control (DNIC) effect, averaged approximately 29%. This finding
implied that when participants experienced one pain-inducing stimulus, they
subsequently experienced another pain-inducing stimulus to a lesser degree. As a
result, efficient conditioned pain modulation was characterised as the ability of
individuals to suppress at least 29% of pain and this cutoff was applied in a
later study [ 43 ]. Secondly, the method proposed by Locke et al. [ 44 ] was adopted and further elaborated in the section on pain modulation profile (PMP)
classification.
The classification of participants into different categories of PMP was achieved
by applying the cut-off thresholds of WUR and CPM [ 45 ]. PMP refers to different
ways in which an individual’s body responds to and regulates pain signals [ 46 ].
In the context of WUR, the cut-off values were determined by adjusting the method
described by Vaegter and Graven-Nielsen [ 45 ]. This adjustment process involved
the inclusion of normative temporal summation data obtained from a cohort of 110
healthy women. Individual WUR values that exceeded the upper limit (95%
confidence interval) of the normative WUR data for the hand (WUR >2.57) were
identified as elevated. For the establishment of CPM cut-off criteria, a
methodology described by Locke et al . [ 44 ] was implemented. This
approach integrated temporal summation (TS) data collected across three
experimental cycles, alongside the CPM data. A significant CPM effect was
recognised when the percentage increase in TS from the baseline exceeded the
inherent measurement error. The calculation of the measurement error involved a
series of steps. Firstly, the intraclass correlation coefficient (ICC) model 3.3
for mean TS (both single and serial stimulation) within each group (5 groups)
from the three experimental cycles. Then, computed the standard error of
measurement (SEM) for each visit, using the formula: SEM = SD(TS) ×
square root of (1 − ICC), and the sum of the SEM with the mean TS for each
stimulation. Next, we converted this value into a percentage change relative to
the mean TS. Finally, we averaged these three TS + SEM relative change percentage
values. Any CPM value above the inherent measurement error indicated a normal or
greater effect. By applying those WUR and CPM effect cut-off values, we therefore
classified participants into four different PMP categorizations: PMP I: Double
pro-nociception (increased TSP/impaired CPM), PMP II: Inhibitory pro-nociception
(normal TSP/impaired CPM), PMP III: Facilitatory pro-nociception (increased
TSP/normal CPM) and PMP IV: Antinociception (normal TSP/normal CPM).
All manual data obtained was entered into a secure electronic database.
Categorical variables were analysed using the chi-square test. Continuous
outcomes were assessed for the normality, and reported as mean ± standard
deviation (SD) with 95% confidence interval. Mean differences among 5 groups
were compared using analysis of variance (ANOVA) if data was normally distributed
and Kruskal-Wallis H test for non-normally distributed data. The significance
level was set at p < 0.05. Additionally, the post hoc test
was conducted when the initial analysis demonstrated statistical significance.
Section 3
Of the 152 participants, 13 were excluded for specific reasons: 4 had taken
NSAIDs within 5 hours before the study, 4 had consumed alcohol within the
previous 12 hours, 3 had smoked cigarettes before the experiment, and 2 were
unable to tolerate the water temperature. Therefore, the final number of
participants included in the study was 139. The clinical characteristics of
participants are shown in Table 1 . Among them, 99 were female and 40 were male,
with a mean age of 42.13 years, SD 10.81. Participants had a mean BMI of 23.15,
SD 3.58. Most participants (96%) were right-handed. The CPM protocol was
performed predominantly between 13:00 and 17:00. The average temperature of the
cold water used in the test was 9.96 °C with an SD of 0.42 °C.
No significant differences were observed across the various characteristics of
the participants. When examining cases, the TMD + MG + FM group gave the highest
mean clinical pain score of 60 out of 100.
General characteristics of study participants.
TMD: TMD patients; TMD + MG: TMD patients with chronic migraine; MG: Chronic
migraine patients; TMD + MG + FM: TMD patients with comorbid migraine and
fibromyalgia.
SD: Standard Deviation; TMD: Temporomandibular disorders; MG:
migraine; FM: fibromyalgia; N/A: Not Applicable.
MDT and PPT values and differences were documented in Fig. 2 a,b. Within the
participant pool, individuals with migraine (MG) had the lowest mean threshold of
0.45 grammes on the face, while the TMD + MG + FM group had the lowest mean
threshold of 0.68 grammes on the hand. In contrast, the remaining groups
exhibited relatively similar mean MDT values for both facial and hand areas.
Significant differences of MDT were detected when accessing the painful region,
differentiating between the MG group from the healthy controls, the TMD, as well
as the TMD + MG groups. In terms of the PPT test, the MG group consistently
reported the lowest threshold on the face (1.35 kPa), whereas the control group
showcased the highest PPT (1.59 kPa). Nevertheless, distinctions were also
apparent in testing on the face between when comparing control group with the MG,
TMD + MG, and TMD + MG + FM groups. Interestingly, although the TMD + MG + FM
group registered the lowest PPT on the hand, no significant differences were
observed across all five groups.
The TMD + MG + FM group had the most elevated pain scores of 21 and 43 out of
100 in the single and serial tests, respectively. In contrast, the healthy
control group reported the lowest pain scores in both assessments, 15 and 32 out
of 100, respectively ( Table 2 ). No significant differences were
found between the participants when the TS test was examined with a single
stimulus. However, with serial stimulation, there were notable differences
between the groups. The mean WUR from the TS tests was presented in Table 2 and
Fig. 2 c, but the result showed no significant differences across the five study
groups.
Pain rating scores and outcomes during temporal summation and
conditioned pain modulation protocol.
*: Statistical difference ( p < 0.05); TMD: TMD patients; MG: Chronic
migraine patients; TMD + MG: TMD patients with chronic migraine; TMD + MG + FM:
TMD patients with comorbid migraine and fibromyalgia.
NRS: Numeric Rating Scale; SD: Standard Deviation; CPM: conditioned pain modulation; TMD: Temporomandibular
disorders; MG: migraine; FM: fibromyalgia.
The pain scores obtained from the CPM experiment were detailed in both Table 2
and Fig. 2 d. The control group reported the highest pain scores, and these scores
differed significantly from the other four groups for both single and serial
stimulation, 8 and 21 out of 100, respectively. In the context of within-group
analysis ( Table 2 ), the presence of pain inhibition (where the pain score during
CPM deviated from the baseline pain score in MTS) was evident in all groups for
both types of stimulation, except for TMD + MG + FM in both stimulations.
The CPM magnitude values for both the single and serial tests were presented in
Table 2 and Fig. 2 e. No noticeable distinction in CPM magnitude emerged for the
single stimuli. However, in the context of serial stimulation, the control group
showed the lowest CPM magnitude (−11), which was significantly different from the
MG, TMD + MG and TMD + MG + FM groups. Furthermore, apart from the healthy
participants, the TMD group demonstrated the second lowest CPM magnitude (−8)
during serial stimulation, followed by the MG (−5), TMD + MG (−4) and TMD + MG +
FM (−4) groups.
The pain score acquired from the MTS and the CPM were used to calculate the
percentage change in CPM effect. The CPM effect was reversed from CPM magnitude
which meant that higher CPM effect (more positive percentage) indicated higher
pain inhibition ability, while lower CPM percentage indicated lower pain
inhibition ability. The mean percentage change within each group was reported in
Table 2 and the significant differences among groups were shown in Fig. 2 f. In
the single stimulation, CPM effect in healthy individuals was higher and
different from other groups of patients. For the serial stimulation, all the pain
patients, except for TMD patients, exhibited lower CPM effect than controls and
the difference was also observed between TMD and TMD + MG groups. The frequency
of participants who had efficient CPM (the ability of individuals to inhibit at
least 29% of pain) were presented in Table 2 and Fig. 3 . It illustrated that the
largest proportion of participants with effective CPM responses were found among
the healthy samples, accounting for 70% and 60% for the single and serial
tests, respectively. In contrast, the lowest proportion of effective CPM
responders was observed in the TMD + MG + FM group, with rates of 36% and 21%
for the single and serial tests, respectively.
Comparison of (a) mechanical detection threshold (MDT), (b)
pressure pain threshold (PPT) among participants, (c) pain score during
mechanical temporal summation (TS), (d) pain score during conditioned pain
modulation (CPM), (e) conditioned pain modulation magnitude, (f) percentage of
CPM effect change. Controls (black), TMD Patients (orange), Migraine Patients
(green), TMD Patients with Comorbid Migraine (blue), TMD Patients with Comorbid
Migraine and Fibromyalgia (grey). SD: standard deviation; TMD: temporomandibular
disorder; MG: migraine; FM: fibromyalgia.
Percentage of participants with an effective conditioned pain
modulation (CPM) response, a minimum of 29% pain inhibition. TMD:
temporomandibular disorder; MG: migraine; FM: fibromyalgia.
The correlation analysis examined the relationship between the number of
comorbidities and the CPM effect. In this study, we have analysed by selecting
three groups: the TMD group had no comorbid pain, the TMD + MG group experienced
one comorbid pain, and the TMD + MG + FM group faced two comorbid pain
conditions. Using Pearson Correlation, we found a significantly negative
correlation between the number of comorbidities and the CPM effect during single
stimulation. The correlation coefficient ( r ) was −0.312 with p
< 0.001. A similar negative correlation was observed during serial stimulation,
where an r was −0.344 with p < 0.001, suggesting a meaningful
yet mildly negative trend.
The cutoff value of 2.57 for WUR and the corresponding value for CPM were
employed to classify participants into four pain modulation profiles. In the
context of CPM, the threshold values were derived from TS relative change from
the baseline for each stimulation. For single stimulation, CPM cut-off was
16.20% for the control group, 8.48% for the TMD group, 12.35% for the MG
group, 9.50% for the TMD + MG group, and 10.73% for the TMD + MG + FM group.
The serial stimulation had CPM cut-off points at 10.52% for the control group,
12.87% for the TMD group, 12.75% for the MG group, 14.43% for the TMD + MG
group, and 12.77% for the TMD + MG + FM group. Consequently, the distribution of
PMP classifications within each group was visually presented in Fig. 4 . When
analysing the distribution of PMP classification among the five groups, there was
a significant difference among them during serial stimulation (χ 2 =
28.85, p = 0.004), whereas such differences were not present in single
stimulation (χ 2 = 8.96, p = 0.760). Nevertheless, employing
the Bonferroni correction in the context of pairwise comparisons within each
category did not provide the capability to identify which specific categories
differ from each other.
Distribution of pain modulation profile (PMP) in single and
serial stimulations across groups: controls (a), TMD Patients (b), Migraine
Patients (c), TMD Patients with Comorbid Migraine (d), TMD Patients with Comorbid
Migraine and Fibromyalgia (e). TMD: temporomandibular disorder; MG: migraine; FM:
fibromyalgia; CPM: conditioned pain modulation; TSP: temporal summation of pain.
Section 4
This study investigated EPM in individuals with TMD, migraine, and fibromyalgia
in comparison to a control group of healthy individuals, as well as the
correlation between the CPM responses and the number of comorbidities. A total of
139 participants were predominantly female, right-handed, with an average age of
42.13 years and a mean BMI of 23.15. Although there were no significant
differences in the characteristics of the participants, there is evidence that
gender and age have an impact on EPM. Pain facilitation was more prominent in
females and those of advanced age [ 47 ]. EPM is less efficient among females [ 48 ]
and older individuals [ 49 ]. Efforts were made to adjust for age, but due to the
predominantly female composition of the patient population, adjusting for gender
was challenging. The study prioritized a larger, more diverse group of
participants while maintaining control over other factors, such as the timing of
the test and water temperature. Water temperature was closely monitored using a
digital thermometer. The simple design of the CPM setup suggests potential for
practical use in clinical settings with limited equipment, but the reliability of
the results should be considered when interpreting findings.
The MDT and PPT tests on the hand showed no significant differences between the
groups, but the face told a different story. Migraine patients were most
sensitive to mechanical stimuli in the masseter muscle compared with other
groups, except for TMD + MG + FM. Furthermore, the MG group consistently reported
the lowest PPT on the face, with differences evident when comparing the control
group. These findings contradict a prior study comparing headache with other pain
conditions (TMD, FM, lower back pain, and irritable bowel syndrome) and reported
the greatest degree of increased pain sensitivity in TMD and FM [ 50 ]. However,
the headache population under the aforementioned study extended beyond
migraineurs. Despite our discrepant findings, the rationale underlying the
greatest increased sensitivity to pain in migraine compared with other pain
conditions remains elusive [ 51 ], and we regrettably lacked a definitive
explanation for this phenomenon. However, as the number of pain comorbidities
increased, as in the TMD + MG and TMD + MG + FM groups, there was a discernible
pattern of lower MDT and PPT. This observation suggests that the combination of
these conditions may have a synergistic effect on pain sensitivity, a phenomenon
consistent with a previous study [ 50 ]. This may underscore the possible interplay
between multiple pain conditions and their collective effects on pain
sensitivity.
The results from the MTS revealed interesting patterns in different stimulation
scenarios. The test involved a single stimulus; there were no significant
differences observed among the participants. However, in serial stimulation,
notable differences emerged among groups. MTS was found to be higher in
individuals with pain conditions when compared with healthy participants, except
for migraine patients. These MTS results were consistent with some previous
studies involving TSP using pinprick stimuli in non-trigeminal areas among TMD
individuals compared with control subjects. Four studies reported an increase in
MTS over the hand [ 13 , 16 ], trapezius [ 16 ], and leg [ 52 ], while another study
found no increase in MTS over the trapezius and hand areas [ 53 ]. The presence of
migraine did not seem to significantly influence MTS responses in TMD patients.
However, when fibromyalgia was present, as seen in the TMD + MG + FM group, it
led to TS differences when compared with the TMD, TMD + MG and MG groups. This
phenomenon could be attributed to the manifestation of widespread bodily pain and
central sensitization associated with the presence of fibromyalgia. Additionally,
the mean WUR did not show significant differences across the five study groups.
This finding is consistent with the recent study that showed no WUR difference
among TMD patients, TMD patients with migraine, and patients with headaches
secondary to TMD [ 54 ]. However, another study yielded contrasting results [ 13 ].
This observation lends support to the idea that temporal summation might be an
inconsistent phenomenon or that the assessment methods used may not effectively
capture the phenomenon of central sensitization [ 55 ].
In the evaluation of the CPM experiment, the difference in the change from the
baseline in the CS pain score serves as an indicator of pain inhibition within
each group. Subsequently, the alteration in the CPM magnitude was converted into
a percentage CPM effect to enable a comparison of the effectiveness of EPM among
groups. The higher the CPM effect, the more efficient the EPM. In general,
individuals with chronic pain conditions, particularly those in the MG, TMD + MG
and TMD + MG + FM groups, displayed lower CPM responses to dynamic stimulation
than healthy participants. The TMD group exhibited less CPM effect only with the
single stimulation. This suggests that the ability to modulate pain in response
to single and repeated stimuli is less effective in MG and TMD patients with
comorbid pain compared with healthy participants. On the other hand, TMD-only
patients showed a lower CPM effect compared with pain-free subjects with only
single stimulation. When considering the threshold for efficient CPM, defined as
the ability to inhibit at least 29% of pain [ 42 ], healthy participants had the
highest proportion of efficient CPM responses. In contrast, the TMD + MG + FM
groups had the lowest proportion of effective CPM responses. Altogether, our
results showed that EPM was impaired in TMD patients with comorbid pain
conditions and the combination of pain conditions shows a trend to reduce the
efficacy of CPM.
To date, few reports have found an effect of CPM in relation to the combination
of pain conditions and multiple studies have provided results on the individual
pain condition in relation to EPM and CPM response. In the TMD population, the
evidence regarding impaired EPM is somewhat mixed. Three studies reported
impaired EPM, specifically in the trigeminal region but not in non-trigeminal
regions [ 13 , 18 , 56 ]. Conversely, another study presented contrasting results,
finding impaired EPM in both extra-segmental and intra-segmental areas in TMD
patients [ 57 ]. Additionally, in one study, no EPM effect was observed in any of
these sites [ 58 ]. Furthermore, when examining only the outside trigeminal area,
three studies were conducted. Among these, an impairment of EPM was found in TMD
patients when compared with a pain-free population in two studies [ 15 , 59 ], while
in one study, no such difference was found [ 10 ]. Most of these studies have
provided evidence supporting intact EPM in TMD patients in non-trigeminal areas.
In other words, CPM between TMD patients and healthy individuals was not
different. Our results in the TMD-only group align with these findings. However,
when concurrent pain conditions are present in the TMD population, it may impact
their ability to engage in EPM, resulting in reduced CPM compared with healthy
individuals, as demonstrated by our study results. The lack of significant CPM
differences among TMD patients is consistent with a previous study that examined
CPM in TMD patients with migraine and headache attributed to TMD but not in
controls [ 54 ]. Furthermore, the analysis using Pearson’s correlation revealed a
negative correlation between the number of comorbidities and the efficiency of
CPM, for both single and serial stimulations. This implies that as the number of
comorbid pain conditions increases, the ability of individuals to effectively
inhibit pain decreases. Therefore, the ability to modulate pain might be an
important factor to consider when managing TMD patients with co-existing pain
disorders.
The distribution of PMP showed a significant difference among the five groups
for serial stimulation but not for single stimulation. Interestingly, in both
serial and single stimulation, the percentage of participants with either
increased TSP or impaired EPM (PMP I, II, III) were higher than that in TMD-only
patients and control subjects. However, applying the Bonferroni correction for
pairwise comparisons within each category made it challenging to pinpoint
specific group differences. A limited number of studies have reported the use of
the PMP classification in chronic pain patients [ 13 , 45 ] and found that a small
percentage of patients had no impaired EPM and no difference in PMP
classification between TMD patients and pain-free subjects [ 13 ]. This scarcity of
usage may stem from its perceived lack of refinement in effectively
distinguishing pain patients based on their EPM abilities. However, this study
suggests that the PMP categorization approach may be valuable, especially in
dynamic stimulation paradigms that showed significant pain response differences
between chronic pain patients and healthy controls. This underscores the
promising applicability of the PMP classification and suggests further
opportunities for the development of predictive models of pain onset and
personalised pain treatment strategies based on the PMP classification [ 60 ].
In terms of the different effects of stimulus modality, previous literature did
not extensively explore differences in MTS and CPM outcomes between single
(static) stimuli and serial (dynamic) stimuli. Our findings suggested that the
cumulative effect of repeated painful stimuli, as seen in the serial test, might
have a more pronounced impact on pain modulation. The result was similar to a
study comparing different stimulus modalities for MTS and CPM, including heat and
pressure, as well as single and serial stimuli. This prior study suggested that
CPM was significantly more influenced by serial stimuli in MTS than by single
stimuli in MTS [ 61 ]. However, it is crucial to acknowledge that CPM responses as
well are highly dependent on the experimental design and can be influenced by
considerations of its reliability [ 41 ]. The use of distinct stimuli or even
variations in the intensity of the same stimulus can potentially impact the
results of CPM assessments [ 62 ].
The discovery of reduced efficacy of CPM in patients suffering from various pain
syndromes requires an explanation. This situation theoretically raises a dilemma
resembling a “chicken and egg” scenario [ 60 ]. It suggests that either the
patients originally had normal CPM efficiency, but their pain inhibition capacity
had been depleted due to the persistent chronic pain, rendering them incapable of
effectively reducing pain within the CPM protocol setting, or the patients
initially had a less efficient CPM. CPM plays an important role in both pain
research and clinical practice, enabling the assessment of a patient’s pain
modulation system, predicting treatment outcomes, and guiding tailored pain
management [ 60 ]. However, challenges, such as individual variability and lack of
standardised protocols, need to be addressed to maximise its clinical utility in
the treatment of chronic pain.
This study has several limitations to be acknowledged. Firstly, the CPM protocol
used lacks standardisation for specific conditions, so it was adapted for TMD
based on tailored evidence. Further research on CPM validation and variability is
needed. Secondly, precise control of water temperature was critical.
Unfortunately, due to limited access to equipment, we had to use an alternative
insulated cooling container with a digital thermometer. These adaptations were
tested and validated prior to the study. Thirdly, the population of TMD patients
with comorbid fibromyalgia and migraine was small due to low prevalence and time
constraints. Moreover, medications beyond NSAIDs, paracetamol, or psychiatric
treatments may not have been fully excluded. While these agents could potentially
influence pain modulation, their impact is likely less immediate compared with
short half-life analgesics, and was therefore not specifically controlled for in
the study design. Lastly, we did not include a TMD + FM group for comparison,
preferring the TMD + MG + FM group to assess the impact of comorbidities within
the study’s timeframe. Hence, increasing the sample size for the TMD + MG + FM
group and incorporating the TMD + FM group might have potentially modified the
results, rendering them more significant.
Section 5
The coexistence of comorbid pain conditions, such as migraine and fibromyalgia,
in TMD patients is correlated with a reduced capacity for endogenous pain
modulation. This suggests that TMD patients struggling with concurrent pain
disorders may require a more thorough assessment of their pain modulation
systems. Targeted treatment strategies that systematically address these
interrelated pain conditions might be crucial in improving pain management
overall. This highlights the importance of a comprehensive treatment approach for
individuals with multiple pain-related comorbidities.
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