Review of clinical utility of pain classification part 2

Part 2: Evaluating mechanism-based classification algorithms for neuropathic pain in people with non-specific arm pain: How’d they do?

Translating knowledge of pain mechanisms into clinical practice is challenging. In our study [6] we examined three recently published classifications for assessing pain [1, 2, 7] (see previous post on BiM for details) to test their applicability to a condition different to that originally investigated.

We recruited people with non-specific arm pain (NSAP) – an ideal condition for applying pain classification algorithms because its pathophysiology is both vague and varied. For example, there is evidence of neural tissue mechanosensitivity [8, 9] and impaired sensory detection[8], causing suspicion of neuropathic pain. Muscle tissue changes have been highlighted [10], suggestive of localized nociceptive mechanisms, and we previously reported evidence of pressure and thermal hyperalgesia (locally and remotely) suggestive of more widespread nociceptive sensitization (peripheral and central) [9]. Thus different pain types could exist in this group. So, could using these algorithms enlighten us to a dominant pain classification in NSAP? To evaluate this we had two examiners apply these three algorithms to people with NSAP.

Of the three classification algorithms, two are physiotherapy based (‘Schafer algorithm’ and ‘Smart classification’) and the third is an algorithm endorsed by the IASP neuropathic pain special interest group (NeuPSIG algorithm). The latter was simple to use and examiners typically agreed that participants did not have ‘definite’ or ‘probable’ neuropathic pain. This may seem surprising given the frequent reporting of neural tissue sensitization and sensory deficit in NSAP. However, to us it made sense as the diagnosis of NSAP excludes those with a specific disorder including neuropathy.

And then it got interesting… when using the ‘Schafer algorithm’, examiner agreement was high (kappa=0.78), probably because each decision is dichotomous. Most people were classified as having ‘peripheral nerve sensitization’ with few cases of ‘neuropathic sensitization’ or ‘denervation’. Similarly, using the ‘Smart classification’ system, ‘peripheral neuropathic pain’ was the dominant pain classification. However, examiners disagreed more frequently (kappa =0.40), with more people classified as ‘mixed’. This was likely due to the lack of guidelines around how to interpret and weight clinical features in each classification. While open to bias, this does reflect clinical practice where mixed pain types are common. We aimed to identify a ‘dominant pain type’ in NSAP, but recognize that mixed pain types occur.

What else does this study tell us about NSAP? Although the majority of people were classified clinically as not having neuropathic pain using the NeuPSIG algorithm, the pre-dominant classification using the other two algorithms was ‘peripheral nerve sensitisation’ and ‘peripheral neuropathic pain’. This was largely due to the presence of neural tissue mechanosensitivity on clinical testing.

Very few people were classified with central/neuropathic sensitization. These results don’t support the degree of sensitization to thermal and pressure stimuli (both locally and remotely) that we previously identified using quantitative sensory testing in this same group versus healthy controls and cervical radiculopathy [9, 11]. The mis-match between our previous results (suggestive of widespread sensitization) and the present classification results (suggestive of peripheral neuropathic pain/sensitization) may be explained by potential over-estimation of the presence of pain sensitization in our previous work using group mean comparisons of quantitative sensory testing between healthy people and people with NSAP). However, an alternate explanation may be that clinical assessment frameworks are not yet sensitive enough. For example, one might challenge the practice of establishing the presence of neuropathic sensitization based on the LANSS questionnaire alone [2]. Certainly, the move seems to be towards interpreting neuropathic or pain sensitization using a more comprehensive assessment approach [12].

With the lack of gold-standard means of assessment, frameworks that assist clinical reasoning are very attractive. Ultimately, frameworks serve as a guide and should be integrated into clinical practice but we need to recognize the limitations of the algorithms evaluated. There is no substitute for sound clinical reasoning and reviewing the clinical presentation as treatment progresses. Whether pain classification helps to stratify care and whether this leads to better patient outcomes, while intuitive, needs much more research. Time will tell.

About Niamh Moloney

Niamh MoloneyNiamh Moloney is a musculoskeletal physiotherapist who, following her PhD at University College Dublin, moved to Australia and is currently a lecturer in Physiotherapy at Macquarie University. Her research relates to sensory profiling and assessment of pain sensitization in clinical practice. Outside of work, she is committed to regular ‘de-sensitising of her nervous system’ through yoga, rowing and exploring Sydney’s great bush walks.

References

  1. Haanpää, M., et al., NeuPSIG guidelines on neuropathic pain assessment. Pain, 2011. 152(1): p. 14-27.
  2. Schafer, A., T. Hall, and K. Briffa, Classification of low back- related leg pain- A proposed patho-mechanism based approach. Manual Therapy, 2009. 14(2): p. 222-230.
  3. Smart, K.M., et al., Mechanisms-based classifications of musculoskeletal pain: part 1 of 3: symptoms and signs of central sensitisation in patients with low back (+/- leg) pain. Man Ther, 2012. 17(4): p. 336-44.
  4. Smart, K.M., et al., Mechanisms-based classifications of musculoskeletal pain: Part 2 of 3: Symptoms and signs of peripheral neuropathic pain in patients with low back (±leg) pain. Manual Therapy, 2012. 17(4): p. 345-351.
  5. Smart, K.M., et al., Mechanisms-based classifications of musculoskeletal pain: part 3 of 3: symptoms and signs of nociceptive pain in patients with low back (+/- leg) pain. Man Ther, 2012. 17(4): p. 352-7.
  6. Moloney, N., et al., The clinical utility of pain classifictation in non-specific arm pain. Manual Therapy, 2015. 20(1): p. 157-65.
  7. Smart, K.M., et al., The discriminative validity of “nociceptive”, “peripheral neuropathic” and “central sensitisation” as mechanisms-based classifications of musculoskeletal pain. Clinical Journal of Pain, 2012. 28(9): p. 655-663.
  8. Greening, J., B. Lynn, and R. Leary, Sensory and autonomic function in the hands of patients with non-specific arm pain (NSAP) and asymptomatic office workers. Pain, 2003. 104: p. 275-281.
  9. Moloney, N.A., T.M. Hall, and C.M. Doody, Sensory hyperalgesia is characteristic of non-specific arm pain. Clinical Journal of Pain, 2013. 29: p. 948-956.
  10. Calder, K.M., D.W. Stashuk, and L. McLean, Motor unit potential morphology differences in individuals with non-specific arm pain and lateral epicondylitis. Journal of NeuroEngineering and Rehabilitation, 2008. 5(34).
  11. Moloney, N., T. Hall, and C. Doody, Divergent sensory phenotypes in nonspecific arm pain: comparisons with cervical radiculopathy. Archives of physical and medical rehabilitation, 2015. 96(2): p. 269-275.
  12. Nijs, J., et al., Applying modern pain neuroscience in clinical practice: Criteria for the classification of central sensitization pain Pain Physician, 2014. 17(5): p. 447-457.