Central sensitization in CRPS patients with widespread pain: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: Widespread pain hypersensitivity and enhanced temporal summation of pain (TSP) are commonly reported in patients with complex regional pain syndrome (CRPS) and discussed as proxies for central sensitization. This study aimed to directly relate such signs of neuronal hyperexcitability to the pain phenotype of CRPS patients. METHODS: Twenty-one CRPS patients and 20 healthy controls (HC) were recruited. The pain phenotype including spatial pain extent (assessed in % body surface) and intensity were assessed and related to widespread pain hypersensitivity, TSP, and psychological factors. Quantitative sensory testing (QST) was performed in the affected, the contralateral and a remote (control) area. RESULTS: CRPS patients showed decreased pressure pain thresholds in all tested areas (affected: t(34) = 4.98, P < .001, contralateral: t(35) = 3.19, P = .005, control: t(31) = 2.65, P = .012). Additionally, patients showed increased TSP in the affected area (F(3,111) = 4.57, P = .009) compared to HC. TSP was even more enhanced in patients with a high compared to a low spatial pain extent (F(3,51) = 5.67, P = .008), suggesting pronounced spinal sensitization in patients with extended pain patterns. Furthermore, the spatial pain extent positively correlated with the Bath Body Perception Disturbance Scale (ρ = 0.491; P = .048). CONCLUSIONS: Overall, we provide evidence that the pain phenotype in CRPS, that is, spatial pain extent, might be related to sensitization mechanism within the central nociceptive system. This study points towards central neuronal excitability as a potential therapeutic target in patients with more widespread CRPS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".