The Canadian Systemic Sclerosis Oral Health Study II: the relationship between oral and global health-related quality of life in systemic sclerosis
Bibliographic record
Abstract
OBJECTIVE: Both oral and global health-related quality of life (HRQoL) are markedly impaired in SSc. In this study we aimed to determine the degree of association between oral HRQoL and global HRQoL in SSc. METHODS: Subjects were recruited from the Canadian Scleroderma Research Group registry. Global HRQoL was measured using the Medical Outcomes Trust 36-item Short Form Health Survey (SF-36) and oral HRQoL with the Oral Health Impact Profile (OHIP). The Medsger Disease Severity Score was used to determine organ involvement. Multivariate regression models determined the independent association of the OHIP with the SF-36 after adjusting for confounders. RESULTS: This study included 156 SSc subjects. The majority (90%) were women, with a mean age of 56 years, mean disease duration 13.8 years (s.d. 8.5) and 29% of the subjects had dcSSc. Mean total OHIP score was 40.8 (s.d. 32.4). Mean SF-36 mental component summary (MCS) score was 49.7 (s.d. 11.1) and physical component summary (PCS) score was 37.0 (s.d. 10.7). In adjusted analyses, the total OHIP score was significantly associated with the SF-36 MCS and PCS, accounting for 9.7% and 5.6% of their respective variances. Measures of disease severity were not related to OHIP score. CONCLUSION: Oral HRQoL in SSc is independently associated with global HRQoL. Oral HRQoL, however, is not related to physician-assessed disease severity. This suggests that physicians may be disregarding issues related to oral health. HRQoL is an additional dimension of HRQoL not captured by generic instruments such as the SF-36.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".