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June 8, 2010Pain1,026 citations

Quantitative sensory testing in the German Research Network on Neuropathic Pain (DFNS): Somatosensory abnormalities in 1236 patients with different neuropathic pain syndromes

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CMClaudia S. MaierRBRalf BaronTTThomas R. Tölle

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Abstract

Neuropathic pain is accompanied by both positive and negative sensory signs. To explore the spectrum of sensory abnormalities, 1236 patients with a clinical diagnosis of neuropathic pain were assessed by quantitative sensory testing (QST) following the protocol of DFNS (German Research Network on Neuropathic Pain), using both thermal and mechanical nociceptive as well as non-nociceptive stimuli. Data distributions showed a systematic shift to hyperalgesia for nociceptive, and to hypoesthesia for non-nociceptive parameters. Across all parameters, 92% of the patients presented at least one abnormality. Thermosensory or mechanical hypoesthesia (up to 41%) was more frequent than hypoalgesia (up to 18% for mechanical stimuli). Mechanical hyperalgesias occurred more often (blunt pressure: 36%, pinprick: 29%) than thermal hyperalgesias (cold: 19%, heat: 24%), dynamic mechanical allodynia (20%), paradoxical heat sensations (18%) or enhanced wind-up (13%). Hyperesthesia was less than 5%. Every single sensory abnormality occurred in each neurological syndrome, but with different frequencies: thermal and mechanical hyperalgesias were most frequent in complex regional pain syndrome and peripheral nerve injury, allodynia in postherpetic neuralgia. In postherpetic neuralgia and in central pain, subgroups showed either mechanical hyperalgesia or mechanical hypoalgesia. The most frequent combinations of gain and loss were mixed thermal/mechanical loss without hyperalgesia (central pain and polyneuropathy), mixed loss with mechanical hyperalgesia in peripheral neuropathies, mechanical hyperalgesia without any loss in trigeminal neuralgia. Thus, somatosensory profiles with different combinations of loss and gain are shared across the major neuropathic pain syndromes. The characterization of underlying mechanisms will be needed to make a mechanism-based classification feasible.

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Cite This Study

Maier et al. (2010) studied this question.

synapsesocial.com/papers/69dbde28498b35d3e6a3d63ehttps://doi.org/10.1016/j.pain.2010.05.002
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