Non-invasive investigation in patients with inflammatory joint disease
Bibliographic record
Abstract
Gut inflammation can occur in 30%-60% of patients with spondyloarthropathies. However, the presence of such gut inflammation is underestimated, only 27% of patients with histological evidence of gut inflammation have intestinal symptoms, but subclinical gut inflammation is documented in two-thirds of patients with inflammatory joint disease. There are common genetic and immunological mechanisms behind concomitant inflammation in the joints and intestinal tract. A number of blood tests, e.g. erythrocyte sedimentation rate, orosomucoid, C-reactive protein, and white cell and platelet counts, are probably the most commonly used laboratory markers of inflammatory disease, however, these tests are difficult to interpret in arthropathies associated with gut inflammation, since any increases in their blood levels might be attributable to either the joint disease or to gut inflammation. Consequently, it would be useful to have a marker capable of separately identifying gut inflammation. Fecal proteins, which are indirect markers of neutrophil migration in the gut wall, and intestinal permeability, seem to be ideal for monitoring intestinal inflammation: they are easy to measure non-invasively and are specific for intestinal disease in the absence of gastrointestinal infections. Alongside the traditional markers for characterizing intestinal inflammation, there are also antibodies, in all probability generated by the immune response to microbial antigens and auto-antigens, which have proved useful in establishing the diagnosis and assessing the severity of the condition, as well as the prognosis and the risk of complications. In short, non-invasive investigations on the gut in patients with rheumatic disease may be useful in clinical practice for a preliminary assessment of patients with suspected intestinal disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".