Sensory data-driven classification of complex regional pain syndrome: a multicentre cohort study
Authors' conclusion
A novel bottom-up approach can stratify CRPS based on sensory phenotypes, adding to a mechanistic understanding through a comparative analysis of human pain surrogate models.
Study context
- Population
- Patients with complex regional pain syndrome (type I: n=520; type II: n=84) undergoing Quantitative Sensory Testing (DFNS protocol)training 380, validation 224
- Participants
- 604 patients
- Exposure
- Thermal hypersensitivity vs Sensory loss vs Allodynia/hyperalgesia
- Thermal hypersensitivityn = 382
- Sensory lossn = 200
- Allodynia/hyperalgesian = 22
- Outcome
- Sensory phenotypes identified by cluster analysis of 13 QST parameters
Methodological detailshypothesis-free cluster analysis, training and validation sets
- Hypothesis-free cluster analysis
- Training and validation sets
Main finding
As reported in the abstract
Sensory phenotypes
Three sensory phenotypes identified in the training set, confirmed in the validation set
3
Pronounced hypersensitivity towards cold and heat pain
n=382
Loss of thermal and mechanical sensation
n=200
Strong allodynia and mechanical hyperalgesia (small, but consistent)
n=22
Observational data: associations, not effects.
Original publication
Sensory data-driven classification of complex regional pain syndrome: a multicentre cohort study. Br J Anaesth. Published 1 August 2026. doi:10.
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