Orofacial Complications of the Connective Tissue Disease Systemic Sclerosis
Bibliographic record
Abstract
Scleroderma (systemic sclerosis, SSc) is an autoimmune fibrosing connective tissue disease of unknown etiology. SSc patients show increased levels of autoantibodies, profibrotic cytokines, and extracellular matrix remodeling enzymes that collectively cause activated (myo)fibroblasts, the effector cell type of fibrosis. Despite these impacts, no disease-modifying therapy exists; individual symptoms are treated on a patient-to-patient basis. SSc research has been principally focused on symptoms observed in the lung and skin. However, SSc patients display significant oral complications that arise due to fibrosis of the not only skin, causing microstomia, but also the gastrointestinal tract, causing acid reflux, and the oral cavity itself, causing xerostomia and gingival recession. Due to these complications, SSc patients have impaired quality of life, including periodontitis, tooth loss, reduced tongue mobility, and malnutrition. Indeed, due to their characteristic oral presentation, SSc patients are often initially diagnosed by dentists. Despite their clinical importance, the oral complications of SSc are severely understudied; high-quality publications on this topic are scant. However, SSc patients with periodontal complications possess increased levels of matrix metalloproteinase-9 and chemokines, such as interleukin-6 and chemokine (C-X-C motif) ligand-4. Although many unsuccessful clinical trials, mainly exploring the antifibrotic effects of anti-inflammatory agents, have been conducted in SSc, none have used oral symptoms, which may be more amenable to anti-inflammatory drugs, as clinical end points. This review summarizes the current state of knowledge regarding oral complications in SSc with the goal of inspiring future research in this extremely important and underinvestigated area.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".