Traits associated with central pain augmentation in the Knee Pain In the Community (KPIC) cohort

Akin-Akinyosoye, Kehinde; Frowd, Nadia; Marshall, Laura; Stocks, Joanne; Fernandes, Gwen; Valdes, Ana M.; McWilliams, Daniel F.; Zhang, Weiya; Doherty, Michael; Ferguson, Eamonn; Walsh, David A.

doi:10.1097/j.pain.0000000000001183

Cited by 37 publications

(62 citation statements)

References 77 publications

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“…In a previous study, we demonstrated that 8 self-report items, each measuring one of these characteristics, contribute to a single latent 'Central Mechanisms' trait 7 . This Central Mechanisms trait was associated with pressure pain detection thresholds (PPTs) at a distal site in individuals with knee pain, an index of central sensitization 7 .…”

Section: Introductionmentioning

confidence: 93%

“…The Central Mechanisms trait score was derived from 8 items ( Supplementary Table 1) representative of the individual component self-report traits measuring anxiety, catastrophizing, cognitive impact, depression, fatigue, neuropathic-like pain, pain distribution and sleep 7 . Reverse worded items were coded so that higher scores represented greater pain or distress.…”

Section: Central Mechanisms Trait Scorementioning

confidence: 99%

“…Self-report traits of anxiety 7,8 , depression 7,8 , catastrophizing 7,9 , neuropathic-like pain 7,10 , fatigue 7,11 , sleep disturbance 7,9 , pain distribution 7 , and cognitive impact 7 each is associated with pain intensity and clinical and experimental markers for central pain mechanisms in individuals reporting knee pain. In a previous study, we demonstrated that 8 self-report items, each measuring one of these characteristics, contribute to a single latent 'Central Mechanisms' trait 7 . This Central Mechanisms trait was associated with pressure pain detection thresholds (PPTs) at a distal site in individuals with knee pain, an index of central sensitization 7 .…”

Section: Introductionmentioning

confidence: 99%

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Baseline self-report ‘central mechanisms’ trait predicts persistent knee pain in the Knee Pain in the Community (KPIC) cohort

Akin-Akinyosoye

Sarmanova

Fernandes

et al. 2020

Osteoarthritis and Cartilage

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Objectives: We investigated whether baseline scores for a self-report trait linked to central mechanisms predict 1 year pain outcomes in the Knee Pain in the Community cohort. METHOD: 1471 participants reported knee pain at baseline and responded to a 1-year follow-up questionnaire, of whom 204 underwent pressure pain detection thresholds (PPTs) and radiographic assessment at baseline. Logistic and linear regression models estimated the relative risks (RRs) and associations (b) between self-report traits, PPTs and pain outcomes. Discriminative performance for each predictor was compared using receiver-operator characteristics (ROC) curves. Results: Baseline Central Mechanisms trait scores predicted pain persistence (Relative Risk, RR ¼ 2.10, P ¼ 0.001) and persistent pain severity (b ¼ 0.47, P < 0.001), even after adjustment for age, sex, BMI, radiographic scores and symptom duration. Baseline joint-line PPTs also associated with pain persistence (RR range ¼ 0.65 to 0.68, P < 0.02), but only in univariate models. Lower baseline medial joint-line PPT was associated with persistent pain severity (b ¼ À0.29, P ¼ 0.013) in a fully adjusted model. The Central Mechanisms trait model showed good discrimination of pain persistence cases from resolved pain cases (Area Under the Curve, AUC ¼ 0.70). The discrimination power of other predictors (PPTs (AUC range ¼ 0.51 to 0.59), radiographic OA (AUC ¼ 0.62), age, sex and BMI (AUC range ¼ 0.51 to 0.64), improved significantly (P < 0.05) when the central mechanisms trait was included in each logistic regression model (AUC range ¼ 0.69 to 0.74). Conclusion: A simple summary self-report Central Mechanisms trait score may indicate a contribution of central mechanisms to poor knee pain prognosis.

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Section: Introductionmentioning

confidence: 93%

Section: Central Mechanisms Trait Scorementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Baseline self-report ‘central mechanisms’ trait predicts persistent knee pain in the Knee Pain in the Community (KPIC) cohort

Akin-Akinyosoye

Sarmanova

Fernandes

et al. 2020

Osteoarthritis and Cartilage

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“…[12][13][14] Recently, researchers have utilized self-report to investigate clinical features of centralized pain, including spatial distribution of pain and cognitive, emotional, and physical symptoms. 15,16 Although self-report is an indirect tool to assess central sensitization, it remains the gold standard in pain assessment. 8 Indeed, comprehensive assessment of pain, which includes assessment of bodily distribution of pain, is needed to accurately classify both acute and chronic pain.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the psychometric properties of the Widespread Pain Index and the Symptom Severity Scale in youth with painful conditions

Dudeney

Law

Meyyappan

et al. 2019

Canadian Journal of Pain

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Background: Assessing features of centralized pain may prove to be clinically meaningful in pediatric populations. However, we are currently limited by the lack of validated pediatric measures. Aim: We examined the psychometric properties of the Widespread Pain Index (WPI) and Symptom Severity (SS) scale to assess features of centralized pain in youth with painful conditions from three clinical samples: (1) musculoskeletal surgery, (2) headache, and (3) chronic pain. Methods: Participants were 240 youth aged 10 to 18 years (M age = 14.8, SD = 1.9) who completed the WPI and SS scale. Subsets of participants also completed additional measures of pain region, pain intensity, quality of life, pain interference, and physical function. Results: Increased features of centralized pain by age were seen for the WPI (r = 0.27, P < 0.01) and SS scale (r = 0.29, P < 0.01). Expected differences in sex were seen for the WPI (sex: t 132 = −3.62, P < 0.01) but not the SS scale (sex: t 223 = −1.73, P = 0.09). Reliability for the SS scale was adequate (α = 0.70). Construct validity was demonstrated through relationships between the WPI and pain regions (r = 0.57, P < 0.01) and between the SS scale and quality of life (r = −0.59, P < 0.01) and pain interference (r = 0.56, P < 0.01). Criterion validity was demonstrated by differences on the WPI between the surgery sample and the headache and chronic pain samples (F 2,237 = 17.55, P < 0.001). Comprehension of the SS scale items was problematic for some youth. Conclusions: The WPI showed adequate psychometric properties in youth; however, the SS scale may need to be modified. Our findings support the need to develop psychometrically sound instruments for comprehensive assessment of pain in pediatric samples.

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“…This position seems intuitive, yet we regularly encounter situations in which our pain threshold seems to have moved or indeed vanished completely. In the scientific literature, pain threshold is conceptualised as a fixed point (or very narrow range) in the stimulus-response relationship, [1][2][3] and the position of this point (or narrow range) on the stimulus-response curve can be shifted by biological, psychological and social factors (see 4 for an accessible review).…”

Section: Introductionmentioning

confidence: 99%

Rethinking pain threshold as a zone of uncertainty

Madden

Kamerman

Catley

et al. 2019

Preprint

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Background. The pain threshold is traditionally conceptualised as a boundary that lies between painful and non-painful events, suggesting a reasonably stable relationship between stimulus and response. In two previous experiments, participants received laser stimuli of various intensities and rated each stimulus on the Sensation and Pain Rating Scale (SPARS), which includes ranges for rating painful and non-painful events and clearly defines the presumed boundary between them. In the second experiment, participants also provided ratings on the conventional 0-100 Numerical Rating Scale for pain (NRS) and a new rating scale for non-painful events. Those data showed the SPARS to have a curvilinear stimulus-response relationship, reflecting that several different intensities may be rated as painful and non-painful in different trials. This suggests that participants were uncertain about painfulness over a range of intensities and calls into question the idea of a boundary between non-painful and painful events. The current study aimed to determine the number of different stimulus intensities across which each participant provided 'painful' and 'non-painful' reports in different trials. Methods. We undertook novel exploratory analyses on data from the aforementioned two experiments (n = 19, 11 female, 18-31 years old; n = 7, 5 female, 21-30 years old). We used the binomial test to formally determine the width of this 'zone of uncertainty' about painfulness, using ratings on the SPARS and the comparator scales, and data visualisation to assess whether trial-totrial change in stimulus intensity influences ratings. Results. We found that the width of the zone of uncertainty varied notably between individuals and that the zone was non-continuous for most participants. Plots of group-level data concealed the inter-individual variability apparent in the individual plots, but still showed a wide zone of uncertainty on both the SPARS and the NRS, but a narrow zone on the scale for non-painful events. There was no evidence that trial-to-trial change in stimulus intensity influenced ratings. Conclusions. The variability revealed by this study has important design implications for experiments that include initial calibration of repeatedly delivered stimuli. The variability also stands to inflate the size of sample that is required for adequate statistical powering of experiments, and provides rationale for the use of statistical approaches that account for individual variability in studies of pain. Finally, the high variability implies that, if experimental stimuli are to be used in clinical phenotyping, many trials may be required to obtain results that represent a single patient's actual response profile.

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Traits associated with central pain augmentation in the Knee Pain In the Community (KPIC) cohort

Abstract: Supplemental Digital Content is Available in the Text.Self-report items measuring 8 pain-related traits represent a unifying construct. This construct, and items, are significant correlates of quantitative sensory testing indices for centrally augmented knee pain.

Cited by 37 publications

References 77 publications

Baseline self-report ‘central mechanisms’ trait predicts persistent knee pain in the Knee Pain in the Community (KPIC) cohort

Baseline self-report ‘central mechanisms’ trait predicts persistent knee pain in the Knee Pain in the Community (KPIC) cohort

Evaluating the psychometric properties of the Widespread Pain Index and the Symptom Severity Scale in youth with painful conditions

Rethinking pain threshold as a zone of uncertainty

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