Inflammatory and Noninflammatory Disease Activity in Rheumatoid Arthritis: The Effect of Pain on Personalized Medicine
Bibliographic record
Abstract
Disease activity in rheumatoid arthritis (RA) is often described in terms of inflammation, although noninflammatory mechanisms are also integral to the disease. Pain is the most important symptom for many people with RA,1 and is therefore a key component of clinically relevant measures of RA disease activity. As an example, the Disease Activity Score in 28 joints (DAS28) incorporates a visual analog scale for general health (VAS-GH) and tender joint counts (TJCs), which are largely dependent on pain. Inflammation contributes to RA pain, but so also do noninflammatory mechanisms. In this edition of The Journal of Rheumatology , Wohlfahrt et al2 use DAS28 to define disease activity, explicitly incorporating both inflammation and noninflammatory pain into their concept of active disease. Noninflammatory pain mechanisms are multiple and complex, and pain can be experienced in different ways by different people and at different times. Pain may be constant or intermittent, localized or widespread, and may be described by a variety of words, such as throbbing, burning, gnawing, or shooting. Pain is often reduced during measurement to a single number, for example, in answer to the global question, “How severe has your pain been over the past week?”3 However, the various pain characteristics are mediated by different mechanisms within peripheral and central nervous systems. Quantitative sensory testing (QST) can be used to explore aspects of hypersensitivity that contribute to the experience of pain. QST has used multiple modalities with standardized stimuli to explore different pain mechanisms. Pain hypersensitivity may indicate either increased facilitation or decreased inhibition of nociceptive transmission. Pressure pain thresholds (PPTs) measure the lowest pressure experienced as pain when a standardized pressure is applied, for example, to a joint or muscle. PPTs are reduced if there is sensitization of peripheral nociceptive neurons (eg, due to inflammation), but they … Address correspondence to Prof. D.A. Walsh, Academic Rheumatology, University of Nottingham Clinical Sciences Building, City Hospital, Nottingham NG5 1PB, UK. Email: david.walsh{at}nottingham.ac.uk.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".