The Canadian systemic sclerosis oral health study: orofacial manifestations and oral health-related quality of life in systemic sclerosis compared with the general population
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare oral abnormalities and oral health-related quality of life (HRQoL) of patients with SSc with the general population. METHODS: SSc patients and healthy controls were enrolled in a multisite cross-sectional study. A standardized oral examination was performed. Oral HRQoL was measured with the Oral Health Impact Profile (OHIP). Multivariate regression analyses were performed to identify associations between SSc, oral abnormalities and oral HRQoL. RESULTS: We assessed 163 SSc patients and 231 controls. SSc patients had more decayed teeth (SSc 0.88, controls 0.59, P = 0.0465) and periodontal disease [number of teeth with pocket depth (PD) >3 mm or clinical attachment level (CAL) ≥5.5 mm; SSc 5.23, controls 2.94, P < 0.0001]. SSc patients produced less saliva (SSc 147.52 mg/min, controls 163.19 mg/min, P = 0.0259) and their interincisal distance was smaller (SSc 37.68 mm, controls 44.30 mm, P < 0.0001). SSc patients had significantly reduced oral HRQoL compared with controls (mean OHIP score: SSc 41.58, controls 26.67, P < 0.0001). Multivariate regression analyses confirmed that SSc was a significant independent predictor of missing teeth, periodontal disease, interincisal distance, saliva production and OHIP scores. CONCLUSION: Subjects with SSc have impaired oral health and oral HRQoL compared with the general population. These data can be used to develop targeted interventions to improve oral health and HRQoL in SSc.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".