Peak alpha frequency is related to the degree of widespread pain, but not pain intensity or duration, among people with urologic chronic pelvic pain syndrome

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Widespread pain, reflecting central sensitization, is associated with lower peak alpha frequency when compared with localized pain in people with chronic pelvic pain syndrome.

Abstract

Introduction:

Effective prevention and management strategies for chronic pain remain elusive. This has prompted investigations into biomarkers to better understand the mechanisms underlying pain development and persistence. One promising marker is low peak alpha frequency (PAF), an electroencephalography (EEG) measure that has been associated with increased sensitivity during acute experimental pain. However, findings regarding the relationship between PAF and chronic pain are variable, potentially due to disparate levels of central sensitization among chronic pain populations. This is evidenced by the variable extent of widespread pain, a phenotypic marker for central sensitization, observed across individuals with chronic pain.

Objective:

To explore the impact of widespread pain on PAF among people with chronic pain.

Method:

Thirty-eight individuals with urologic chronic pelvic pain syndrome were categorized as having widespread (n = 24) or localized (n = 14) pain based upon self-reported body maps. Electroencephalography data were collected under resting conditions, and PAF was determined using spectral analysis.

Results:

Participants with widespread pain had a significantly lower global average PAF than those with localized pain, after controlling for age and sex. This relationship persisted even when accounting for pain intensity and duration. Peak alpha frequency differences were observed across all EEG electrodes, particularly in the sensorimotor and occipital regions.

Conclusion:

Preliminary findings suggest that PAF may represent a potential biomarker for central sensitization in chronic pain, highlighting the importance of considering pain distribution in chronic pain research. Future studies with larger samples should investigate the neural mechanisms underlying these observations and the clinical utility of PAF in diverse chronic pain populations.

1. Introduction

Chronic pain affects approximately 1.5 billion people globally and is a leading cause of productivity loss, disability, and declines in quality of life.⁴³ The total cost of chronic pain conditions exceeds $USD 600 billion annually in the United States alone.¹⁰ Unfortunately, despite considerable investment over the past 2 decades, effective preventative and treatment strategies for chronic pain remain elusive. Accumulating research has therefore sought markers to better understand the mechanisms underlying chronic pain and guide the development of novel therapeutic approaches.

One promising marker of interest in pain research is peak alpha frequency (PAF). This electroencephalography (EEG) measure represents the dominant frequency within the alpha band (7–13 Hz) of brain wave activity and has been investigated in a variety of cognitive and sensory processes.³² Peak alpha frequency has received particular attention given its relative ease of collection, trait-like characteristics,²¹ and excellent test–retest reliability over extended periods.³⁹ Notably, lower pain-free PAF has been associated with increased pain sensitivity in healthy individuals during acute experimental pain paradigms.^16,17 This has led to the hypothesis that reductions in PAF could be a viable biomarker for increased susceptibility to chronic pain development. However, recent literature demonstrates that the relationship between PAF and chronic pain is more variable, with reductions,^11,46 increases,¹⁴ and no differences^13,41,50 in PAF being observed between people with chronic pain and healthy controls. The role of PAF in chronic pain is therefore yet to be completely elucidated.

Previous explorations of PAF have often consolidated findings across several diagnoses to form a single “chronic pain” group that is compared with healthy controls.⁵⁴ This approach may obscure important differences in pain mechanisms between conditions. Heterogenous patient cohorts likely present with varying degrees of central sensitization, a process where the central nervous system becomes hyperresponsive to stimuli. This is evidenced by the variable extent of widespread pain, a common clinical marker for central sensitization, observed across individuals within and across chronic pain diagnoses.^7,30 Conditions characterised by widespread pain, such as fibromyalgia, are associated with more diffuse maladaptive central changes when compared with localized pain conditions, such as low back pain, which have readily identifiable peripheral contributions.^20,33 Indeed, gray matter volume across multiple cortical areas has been shown to be increased among individuals with widespread pain.²⁹ This is supported by work in animal models suggesting that cortical activity differs between localized and widespread pain.¹² Previous findings regarding PAF may therefore have been confounded by the inclusion of participants with disparate levels of widespread pain.

Thus, the aim of this study was to explore the impact of widespread pain on PAF among individuals with chronic pain. Specifically, we investigated a cohort of men and women with urologic chronic pelvic pain syndrome. We hypothesised that individuals with more widespread pain, a clinical reflection of central sensitization, would demonstrate reductions in PAF when compared with those with localized pain, irrespective of pain intensity or duration.

2. Methods

2.1. Participants

No previous studies have investigated the effects of widespread pain on PAF in people with urologic chronic pelvic pain syndrome (UCPPS). An exploratory sample was therefore derived from 2 study populations at the University of Southern California (USC): from a previously completed observational study of UCPPS in men⁵³ and from pretreatment baseline data in an ongoing clinical trial of UCPPS in women. Participants were recruited through community advertisements and by directly contacting physical therapists and urologists for referrals throughout the Los Angeles, California, metropolitan area.

Inclusion/exclusion criteria for both studies were based on the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network and earlier studies of UCPPS.^31,53 Participants were eligible for analysis in this study if they were at least 18 years old and had a diagnosis of UCPPS. Women were eligible if they had symptoms present most of the time for the past 3 months; men were eligible if they had symptoms present most of the time in any 3 of the past 6 months. Exclusion criteria for women consisted of the following: symptomatic urethral stricture, ongoing neurological conditions affecting the bladder or bowel, active autoimmune or infectious disorders, history of cystitis caused by tuberculosis or radiation or chemotherapies, history of nondermatologic cancer, current major psychiatric disorders, or severe cardiac, pulmonary, renal, or hepatic disease. Exclusion criteria for men consisted of the following: positive urine culture and active treatment for bacterial prostatitis; severe, debilitating, or urgent medical condition (other than chronic pelvic pain); active urethral or ureteral calculi; urethral diverticulum; history of pelvic radiation therapy; tuberculous cystitis; bladder cancer; carcinoma in situ; prostate or urethral cancer; or unilateral testicular pain without other pelvic symptoms.

The final data set comprised all eligible women (n = 19) and a group of men who were matched in terms of age and degree of widespread pain (n = 19), resulting in a total sample of 38 participants with UCPPS. Men and women were matched according to age and degree of widespread pain with propensity score matching to minimize the effect of sex between the localized and widespread pain groups. Propensity score matching fits a logistic regression model to estimate the likelihood of being in one group (eg, male or female) based on observed covariates, such as age or degree of widespread pain. This probability, or propensity score, is then used to match participants from different groups with similar likelihoods of being in either group. This is intended to minimize selection bias and control for necessary confounding variables.^2,25

2.2. Experimental protocol

All participants were provided with written and verbal descriptions of the experiment, and written informed consent was obtained before testing. All procedures were approved by the USC Institutional Review Board and performed in accordance with the Declaration of Helsinki.

All data were obtained from a single experimental session, during which demographic data (age, sex, and time since pain onset), pain intensity, and levels of anxiety and depression (Hospital Anxiety and Depression Scale⁵) were collected. To assess the spatial distribution of pain among the included participants, each individual then completed a self-reported body map of pain. After these baseline assessments were conducted, participants underwent electroencephalography (EEG) recordings under resting conditions.

2.3. Assessments

2.3.1. Pain intensity

Pain intensity was assessed using a previously validated 11-point numerical rating scale, where 0 = no pain and 10 = the worst pain imaginable.¹ Participants were asked to report their current pain intensity and perceived average pain intensity over the preceding week.¹

2.3.2. Pain distribution (widespread vs localized)

To examine pain distribution (widespread vs localized), women participating in the ongoing study of interstitial cystitis completed a body map embedded within the Chronic Overlapping Pain Conditions Screener (COPC-S).⁴² The COPC-S body map comprises 23 regions over which participants report the presence or absence of pain at the time of assessment. Men in the study of chronic prostatitis had completed the body map included within the Brief Pain Inventory (BPI),⁹ which comprises 45 regions. To ensure a harmonized and consistent assessment of pain distribution across the included participants, the BPI body maps were transposed onto the COPC-S body map. The means by which BPI regions were converted to COPC-S regions is illustrated in Supplementary Files 1 and 2 (http://links.lww.com/PR9/A288). As concluded in previous research, individuals reporting >2 regions of pain were categorised as having “widespread” pain whereas those with ≤2 regions of pain were considered to have “localized” pain.^7,29,35,51

2.3.3. Electroencephalography

2.3.3.1. Electroencephalography data acquisition

Continuous EEG data were collected using a 64-channel, ANT Neuro gel-based electrode cap with sintered Ag/AgCl electrodes. The online reference was placed at the right mastoid. Electroencephalographic signals were acquired with eego sports acquisition software (v1.2.1) from an Ant Neuro eego Sports amplifier (Product Number ee-202) at a sampling rate of 2048 Hz. Impedances for all electrodes were kept below 15 kΩ.

There is evidence to suggest that the alpha rhythm may vary based upon the body position (supine or semirecumbent), but little is known regarding the effects of the position on PAF.⁴⁵ To mitigate any potential effects, all participants were tested with an identical setup—resting in supine and told to keep their head as still as possible, relax, and not go to sleep. In the study of individuals with interstitial cystitis, participants provided one continuous, 10-minute collection of eyes-closed EEG. Participants in the study of chronic prostatitis followed automated, alternating voice commands to open or close their eyes. The continuous recording was annotated at the beginning of each eyes-open/eyes-closed epoch: In total, there were 10 minutes of continuous EEG data with non-overlapping, 1-minute epochs marked for 5 eyes-open and 5 eyes-closed periods. To mimic the data structure of the interstitial cystitis study, the eyes-open segments from the chronic prostatitis study data were removed (including 1 second before and after the state transition) and the eyes-closed segments concatenated into a single, 5-minute continuous recording. Identical EEG preprocessing pipelines were then used across all participants.

2.3.3.2. Electroencephalography preprocessing

Electroencephalography preprocessing parameters were selected based on a comprehensive review of PAF analyses in pain studies.³² Offline data processing was executed using custom scripts in EEGLAB (v2024.0) and MATLAB (2024a). Preprocessing was conducted across all 64 EEG channels for each participant. The signal was first bandpass filtered from 1 to 100 Hz, and a notch filter applied from 58 to 62 Hz to reduce electrical noise.³²

To ensure the quality and integrity of the EEG data, we used the Multiple Artifact Rejection Algorithm (MARA), a robust and automated method for identifying and removing artifacts from EEG recordings.^48,49 Multiple Artifact Rejection Algorithm first leverages Independent Component Analysis using the extended Infomax algorithm to decompose the EEG signal into spatially fixed, temporally independent components. This decomposition allows for the isolation of artifacts such as eye movements, muscle activity, and other noise sources from the brain's electrical activity.

After Independent Component Analysis decomposition, the MARA was applied to the independent components to automatically classify them as either artifacts or neural activity. Multiple Artifact Rejection Algorithm uses a machine learning approach to assess the likelihood that a component represents an artifact based upon spatial topography, frequency characteristics, kurtosis, and the correlation of components with typical eye movement patterns.^48,49 Components classified by MARA (using default settings) as artifacts were subsequently removed. After artifact removal, each channel's signal was re-referenced to the common average of all channels for each participant. A summary of the preprocessing pipeline is presented in Figure 1.

Figure 1.

Electroencephalography preprocessing pipeline. ICA, independent component analysis; MARA, multiple artifact rejection algorithm.

2.3.3.3. Peak alpha frequency determination

Peak frequency in the alpha band (7–13 Hz) was determined in EEGLAB using the eegstats (v.12) plugin, implementing a 2-second Hamming window with 1-second overlap.^40,47 The weighted sum of the alpha spectrum was divided by the total power, resulting in the “center” of the spectral power, or the “center of gravity (COG)”. This approach has been shown to be the most stable measure of PAF determination.^6,28 The COG was calculated individually for each of the 64 channels for each participant. These values were further averaged for a single, “global average” PAF value for each participant.³²

2.4. Statistical analyses and data visualization

Statistical analyses were undertaken using Statistical Package for the Social Sciences software (version 23 IBM Corp, Armonk, NY) and bespoke MATLAB scripts.

To evaluate the effect of widespread pain on PAF, a linear regression was conducted with global average PAF as the outcome variable and pain distribution (localized vs widespread) as the predictor of interest, while controlling for age and sex. Pain intensity (current and average over preceding week) and pain duration were also added to this foundational model to examine the influence of these outcomes on PAF. To address any potential spatial differences not captured in the global average, the same foundational model was run at each electrode and corrected for multiple comparisons using a Benjamini–Hochberg false discovery rate correction.⁴

A principal component analysis (PCA) was also performed on the topographic PAF at each electrode for every participant. The objective was to determine whether PAF was low-dimensional and, if so, to assess whether the grand-average PAF served as an effective low-dimensional representation of the data. The percentage of total variance explained by each principal component was examined to evaluate the independence of topographic PAF across all electrodes. A Kendall rank correlation was used to determine whether the principal component score aligned with the global average PAF.

2.5. Patient and public involvement

Patients were not involved in the design, reporting, or dissemination of the research. Participants were recruited through community advertisements and by directly contacting physical therapists and urologists for referrals throughout the Los Angeles, California, metropolitan area. Participants were provided with a lay summary of the study's findings and a link to the published manuscript upon request.

3. Results

3.1. Participant characteristics

Participant characteristics are summarised in Table 1. Pain duration was not available for 3 women and one male (participant data entry errors). There were no other missing data. After categorising participants into “widespread” (n = 24) or “localized” pain (n = 14) groups based upon their COPC-S body maps, there were no significant between-group differences in demographic variables, pain intensity, depression, or anxiety.

Table 1.

Participant characteristics.

	Widespread pain group Mean (SD)	Localised pain group Mean (SD)	P
Sample size (n)	24	14	—
Sex (male, female)	12, 12	7, 7	—
Age (y)	43 (13)	45 (15)	0.64
Ethnicity   Hispanic or Latino   Not Hispanic or Latino	29% 71%	21% 79%	—
Race   North American Indian/Native American   Asian/Asian American   Black/African American   Native Hawaiian/Pacific Islander   White/Caucasian   Other	0% 0% 8% 0% 79% 13%	0% 0% 7% 0% 79% 14%	— — — — — —
Average pain intensity over preceding week/10	3.9 (1.7)	4.0 (2.3)	0.85
Current pain intensity/10	3.5 (2.4)	3.0 (2.7)	0.56
Time since pain onset (y)	7.7 (10.7)	6.0 (8.0)	0.61
HADS-A	14 (5)	13 (6)	0.84
HADS-D	12 (5)	12 (6)	0.88

HADS-A and -D, Hospital Anxiety and Depression Scale (Anxiety) and (Depression) Score, respectively.

As shown in Figure 2, participants in the localized pain group had pain that was primarily limited to the pelvic region. Participants in the widespread pain group also had the pelvic region as a primary pain source, but had a more diffuse representation of pain that extended to (and beyond) the abdomen and lower limbs.

Figure 2.

Comparison of pain distribution (widespread and localized). Colour bar = percentage of participants within group reporting pain at that region. The numbers within each region are the raw numbers of participants reporting pain in that region (regions with no number had no participants reporting pain at that region).

3.2. Differences in peak alpha frequency between widespread and localized pain

Participants with widespread pain had a lower global average PAF than those with localized pain. Specifically, the global average (SD) PAF was 9.58 (0.71) for the widespread pain group and 10.25 (0.83) Hz for the localized pain group. After controlling for age and sex, there was a significant difference between widespread and localized pain as a predictor of the global average PAF (P = 0.02). Using localized pain as the reference category, widespread pain was associated with a β value of −0.66 Hz, indicating that, holding all other variables constant, patients with widespread pain had approximately 0.66 Hz lower global average PAF values than those with localized pain. Figure 3 presents the estimated marginal means for the global average PAF across the entire sample (2A) and EEG frequency spectra from 2 representative participants (2B), facilitating visualization of the shift in PAF between the widespread and local pain groups across EEG channels.

Figure 3.

Comparison of PAF and frequency spectra. (A) Estimated marginal means for the global average PAF across the entire sample. *P < 0.05. (B) Spectra across multiple channels for representative participants from the widespread (blue) and localized (red) pain groups. The group average for the global average PAF is marked with a dotted line to assist with visualizing the shift between groups. Note the consistency of PAF across multiple channels for each participant. Error bars = 95% confidence intervals.

As shown in Table 2, age and sex did not have a significant relationship with the global average PAF. The inclusion of pain intensity over preceding week (P = 0.25) or duration (P = 0.30) in the model did not influence the overall findings, indicating that these factors did not significantly affect the relationship observed between global average PAF and pain distribution (Table 2). Inclusion of current pain intensity rather than average pain intensity over the preceding week in the model had no bearing on the overall findings.

Table 2.

Regression table.

Model	β value	Std. Error	t	Sig
1   (Constant)   Age   Sex   Widespread vs local pain	9.613 −0.007 −0.229 −0.658	0.740 0.010 0.264 0.269	12.999 −0.644 −0.867 −2.447	0.000 0.524 0.393 0.020*
2   (Constant)   Age   Sex   Widespread vs local pain   Pain intensity/10	9.300 −0.008 −0.175 −0.594 0.095	0.781 0.010 0.266 0.273 0.080	11.914 −0.744 −0.660 −2.177 1.186	0.000 0.463 0.515 0.038* 0.245
3   (Constant)   Age   Sex   Widespread vs local pain   Time since pain onset (y)	9.304 0.001 −0.113 −0.629 −0.018	0.794 0.012 0.285 0.270 0.017	11.718 0.047 −0.398 −2.331 −1.056	<0.001 0.963 0.694 0.027* 0.300

^*P < 0.05.

There were also significant differences between the widespread and localized pain groups in PAF at every electrode. Individuals with widespread pain had lower PAF values than those with localized pain across the entire scalp (FDR corrected, all electrodes P < 0.035). The range of β values across the electrodes, with localized pain as the reference category, was −0.80 to −0.60. As shown in Figure 4, the areas of maximal difference between the 2 groups were generally across the sensorimotor and occipital regions.

Figure 4.

Comparison of EEG scalp topography between groups. Colour bar = β values for widespread pain vs localized pain as a predictor of PAF values, controlling for age and sex. Widespread pain has significantly lower PAF values at every electrode (all corrected P < 0.035).

3.3. Explanatory power of the global average peak alpha frequency

The PCA revealed that >96% of the variance for the PAF values across electrodes was explained by a single component. This component aligned well with the global average PAF, as confirmed by the Kendall rank correlation coefficient of 0.99 (P < 0.001). This demonstrates that the global average PAF is an excellent individual reflection of PAF variability.

4. Discussion

This was the first study to explore the influence of widespread pain on PAF among individuals with urologic chronic pelvic pain syndrome. In support of our hypothesis, participants with widespread pain demonstrated reductions in the global average PAF when compared with those with localized pain, irrespective of pain intensity or duration. Significant differences between groups were observed across all EEG electrodes and were most pronounced over the sensorimotor and occipital regions. The findings of this study provide novel insights into the neural correlates underlying central sensitization, potentially holding significance for the development of tailored therapeutic strategies among people with chronic pain.

Recent studies have highlighted variability in PAF among chronic pain populations. A systematic review of resting state EEG literature found that, when compared with healthy control participants, one study (8%) reported increased PAF among people with chronic pain, 4 studies (33%) reported decreased PAF, and 7 (58%) found no differences.⁵⁴ This variability is consistent with an earlier review of EEG outcomes among individuals with chronic pain.³⁸ Given that PAF determination is robust against common differences in EEG processing pipelines,^8,32 such discrepancies are unlikely due to methodological considerations. Our findings suggest that previously reported variability in PAF may be attributable to disparate levels of central sensitization within chronic pain cohorts, reflected as differences in pain distribution.

Accumulating research supports neurophysiological differences between local and widespread pain. For example, patients with fibromyalgia (the prototypical widespread, centralized pain disorder) demonstrate reduced connectivity between the nucleus accumbens and the left ventral pallidum, left putamen, and left thalamus when compared with individuals with more localized (lower back) pain.³⁶ Among patients with UCPPS, Kutch et al.²⁹ demonstrated increases in gray matter volume between localized and widespread pain groups within several sensorimotor areas, including the mid-cingulate cortex, inferior parietal lobules, primary somatosensory cortex, and primary motor cortex. This analysis also revealed increased connectivity between the salience network and sensorimotor regions in people with widespread pain. Such neurobiological differences underscore the importance of considering widespread pain in studies investigating the neural correlates of chronic pain. Furthermore, widespread pain has been associated with greater reductions in physical and mental function compared with local pain (irrespective of pain intensity),²⁹ potentially reflecting broadly distributed maladaptive changes to the central nervous system. The differences in PAF observed in this study could therefore reflect these differences in central nervous system involvement and organization.

We found no relationship between PAF and pain intensity in people with chronic pain. This finding is supported by a previous study of people after spinal cord injury, where EEG peak frequency did not correlate with pain intensity but was significantly slower among patients experiencing neuropathic pain when compared with those with no pain.⁵² These data corroborate work in experimental pain models¹⁵ and clinical populations⁴¹ suggesting that PAF may reflect states associated with increased sensitization, rather than the overt intensity of persistent pain. In addition, we observed no effect of pain duration on PAF. This contrasts previous work in patients with chronic pancreatitis showing that greater reductions in PAF are observed among individuals with a longer pain duration.¹¹ Reasons for this discrepancy remain unclear, but may be attributable to diagnosis-specific differences in PAF or the prior lack of consideration of differences in pain distribution. Nevertheless, our findings support a growing body of research suggesting that widespread pain may hold more utility as a clinical phenotypic marker of central sensitization compared with pain intensity or duration.²⁹

Consistent with previous research,³² our PCA of EEG data showed that a single component could explain more than 96% of the variance in PAF across the scalp. We also found a strong correlation between this principal component and the global average PAF. Earlier work has demonstrated that peak frequencies in the alpha band exhibit high interindividual variation compared with intraindividual variation, giving them strong discriminating ability when classifying individuals based on EEG data.²³ Taken together, these findings highlight the utility of the global average PAF as a standardized metric in chronic pain research.

The finding that PAF differed between groups across all channels suggests the involvement of a central generator, with the thalamus being a commonly proposed candidate because of its extensive cortical connections and role in generating the alpha rhythm.^3,26 It has been suggested that reductions in PAF result from thalamocortical dysrhythmia, where high-threshold bursting in thalamocortical neurons slows due to diminished modulatory feedback from the cortex.²⁷ In this study, PAF differences were most pronounced over the sensorimotor and occipital regions, aligning with the thalamocortical pathways involved in pain processing. This observation supports the potential contribution of thalamocortical disruptions in widespread pain. However, recent findings from human intracranial recordings challenge the notion of the thalamus as the primary alpha rhythm pacemaker.²⁴ Multiple studies have also demonstrated independent associations between fluctuations in alpha and changes in blood oxygenation at both thalamic and cortical (eg, occipital, superior temporal, inferior frontal, and cingulate cortex) sites.^18,19 Further research using comprehensive neuroimaging techniques, such as magnetic resonance imaging, is required to disentangle the neural mechanisms underlying the observed differences in PAF between widespread and local pain.

Reliable biomarkers are crucial for developing personalised therapeutic approaches and for early identification of individuals at risk for chronic pain. The capacity of the global average PAF to discriminate between individuals with widespread and localized pain, when combined with its stability over time,³⁹ heritability,⁴⁴ and relative ease of collection, makes it a promising outcome measure during investigations of central sensitization. The observed relationship between PAF and widespread pain suggests that PAF could guide interventions targeting this phenomenon. Preliminary work suggests that PAF may be modifiable through interventions such as noninvasive brain stimulation³⁴ and epidural spinal cord stimulation.³⁷ Whether modulation of PAF successfully alters pain distribution represents an important avenue for future research.

Despite a rigorous approach toward data collection and analysis, this study is not without limitations. Although widespread pain serves as a common clinical marker for central sensitization, it is not a direct assessment of the underlying neural mechanisms. Furthermore, the cross-sectional nature of this study precludes evaluation of causal effects. Whether reductions of PAF are a trait-like driver or a consequence of widespread pain is therefore yet to be determined. Future longitudinal studies exploring healthy individuals at risk of chronic pain development are required to further understand the neurophysiological drivers of central sensitization and widespread pain.

In addition, there remains contention regarding the optimal cut-off for the number of painful sites constituting “local” vs “widespread” pain. For this study, we adopted a cut-off of 2 sites as per previous research,^7,29,35,51 given the potential for individuals to experience remote or unrelated concurrent pain experiences on assessment. Only 5 participants experienced pain at a single location in this study, precluding analyses involving a cut-off of one painful site. Future research with larger samples should be conducted to explore whether varying the number of sites representing “local” or “widespread” pain influences the findings of this study.

Although the equal representation of men and women in our study improves internal validity, it does not reflect the global prevalence of chronic pain conditions, where women predominate.²² Future research should aim to include larger, more representative samples to validate our findings. This is particularly important given the large effects observed in this study, where between-group differences were comparable with those reported between patients and controls in previous work.⁵⁴ Larger data sets would assist in determining whether the observed effects are generalizable or were attributable in part to our relatively small sample. Comparisons with control data would also be beneficial in identifying whether individuals with local vs widespread pain demonstrate consistent or divergent changes in PAF relative to pain-free individuals.

5. Conclusion

This study provides preliminary evidence showing that widespread pain, a clinical reflection of central sensitization, is associated with reductions in PAF when compared with localized pain, irrespective of pain intensity or duration. These findings underscore the importance of considering the degree of widespread pain in chronic pain research and suggest that PAF could serve as a valuable biomarker for assessing central sensitization and guiding therapeutic interventions. Future studies should investigate the neural underpinnings of these observations and explore the clinical utility of PAF in diverse chronic pain populations.

Disclosures

The authors have no conflict of interest to declare.

Appendix A. Supplemental digital content

Supplemental digital content associated with this article can be found online at http://links.lww.com/PR9/A288.