Hypothyroidism in Rheumatoid Arthritis — To Screen or Not to Screen?
Bibliographic record
Abstract
The manifestations of rheumatoid arthritis (RA) extend beyond the symmetrical inflammation of the joints, as shown by accumulating evidence of increased risk for comorbid conditions such as cardiovascular disease (CVD), the leading cause of death in patients with RA1,2. Osteoporosis, another well established comorbidity in RA and low bone mineral density, has been suggested to be associated with cardiovascular mortality as well3,4. These studies demonstrate the importance of alertness for comorbid conditions in RA since it is well known that in patients with chronic diseases coexisting comorbidity is often overlooked5. Interestingly, in this issue of The Journal, McCoy and colleagues report about another comorbidity in patients with RA that seems to be an important amplifier of cardiovascular risk: hypothyroidism6. In the literature on associations between RA and hypothyroidism, which goes back to the 1960s7,8, one of the first studies reported thyroiditis in up to 12% of patients with RA9. Major limitations of these studies were cross-sectional or observational designs and lack of “adequate” control groups. To (partly) tackle these limitations and to elucidate whether … Address correspondence to Dr. Nurmohamed. E-mail: m.nurmohamed{at}reade.nl
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.017 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".