Defining Flare in Osteoarthritis of the Hip and Knee: A Systematic Literature Review — OMERACT Virtual Special Interest Group
Bibliographic record
Abstract
OBJECTIVE: in OA, the objective was to identify the key variables, or symptoms, that worsen, and to clarify how these variables are described in the literature by patients and clinicians. METHODS: A systematic review of the literature was conducted in Medline and PsychINFO. In brief, the search terms used were "osteoarthritis," "knee," "hip," and "flare." Specific characteristics of included studies were identified, including the type of study design, type of flare assessed, how the flare developed, and what definition of flare was used, including whether the definition was based on qualitative or quantitative analysis. RESULTS: Pain was the major factor in the definition of flare within these studies. Four components of flare were identified: pain, other factors, composite criteria, and global assessment. While the majority of studies reported flare as an increase in pain using standardized outcome measures, only 1 study reported the antecedents and consequences of a pain flare using qualitative methods. CONCLUSION: The use of flare as an outcome or inclusion criterion in rheumatology trials is a common occurrence; however, this review highlights the wide variation in the definitions of OA flare currently in use and the emphasis on the measurement of pain. This variation in definition does not allow for direct comparison between trials and limits interpretation of evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".