Flares in Patients with Rheumatoid Arthritis after Total Hip and Total Knee Arthroplasty: Rates, Characteristics, and Risk Factors
Bibliographic record
Abstract
OBJECTIVE: Rates of total knee arthroplasty (TKA) and total hip arthroplasty (THA) remain high for patients with rheumatoid arthritis (RA), who are at risk of flaring after surgery. We aimed to describe rates, characteristics, and risk factors of RA flare within 6 weeks of THA and TKA. METHODS: Patients with RA were recruited prior to elective THA and TKA surgery and prospectively followed. Clinicians evaluated RA clinical characteristics 0-2 weeks before and 6 weeks after surgery. Patients answered questions regarding disease activity including self-reported joint counts and flare status weekly for 6 weeks. Per standard of care, biologics were stopped before surgery, while glucocorticoids and methotrexate (MTX) were typically continued. Multivariable logistic regression was used to identify baseline characteristics associated with postsurgical RA flares. RESULTS: Of 120 patients, the mean age was 62 years and the median RA duration 14.8 years. Ninety-eight (82%) met 2010/1987 American College of Rheumatology/European League Against Rheumatism criteria, 53 (44%) underwent THA (and the rest TKA), and 61 (51%) were taking biologics. By 6 weeks, 75 (63%) had flared. At baseline, flarers had significantly higher disease activity (as measured by the 28-joint Disease Activity Score), erythrocyte sedimentation rate, C-reactive protein, and pain. Numerically more flarers used biologics, but stopping biologics did not predict flares, and continuing MTX was not protective. A higher baseline disease activity predicted flaring by 6 weeks (OR 2.12, p = 0.02). CONCLUSION: Flares are frequent in patients with RA undergoing arthroplasty. Higher baseline disease activity significantly increases the risk. Although more patients stopping biologics flared, this did not independently predict flaring. The effect of early postsurgery flares requires further study.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".