Inflammation in complex regional pain syndrome
Bibliographic record
Abstract
OBJECTIVES: We conducted a systematic review of the literature with meta-analysis to determine whether complex regional pain syndrome (CRPS) is associated with a specific inflammatory profile and whether this is dependent on the duration of the condition. METHODS: Comprehensive searches of the literature using MEDLINE, Embase, Scopus, Web of Science, and reference lists from published reviews identified articles that measured inflammatory factors in CRPS. Two independent investigators screened titles and abstracts, and performed data extraction and risk of bias assessments. Studies were subgrouped by medium (blood, blister fluid, and CSF) and duration (acute and chronic CRPS). Where possible, meta-analyses of inflammatory factor concentrations were performed and pooled effect sizes were calculated using random-effects models. RESULTS: Twenty-two studies were included in the systematic review and 15 in the meta-analysis. In acute CRPS, the concentrations of interleukin (IL)-8 and soluble tumor necrosis factor receptors I (sTNF-RI) and II (sTNF-RII) were significantly increased in blood. In chronic CRPS, significant increases were found in 1) TNFα, bradykinin, sIL-1RI, IL-1Ra, IL-2, sIL-2Ra, IL-4, IL-7, interferon-γ, monocyte chemoattractant protein-1 (MCP-1), and sRAGE (soluble receptor for advanced glycation end products) in blood; 2) IL-1Ra, MCP-1, MIP-1β, and IL-6 in blister fluid; and 3) IL-1β and IL-6 in CSF. Chronic CRPS was also associated with significantly decreased 1) substance P, sE-selectin, sL-selectin, sP-selectin, and sGP130 in blood; and 2) soluble intercellular adhesion molecule-1 (sICAM-1) in CSF. Most studies failed to meet 3 or more of our quality criteria. CONCLUSION: CRPS is associated with the presence of a proinflammatory state in the blood, blister fluid, and CSF. Different inflammatory profiles were found for acute and chronic cases.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".