Detection of xerostomia, Sicca, and Sjogren’s syndromes in a national sample of adults
Bibliographic record
Abstract
OBJECTIVES: To assess the prevalence and determinants of xerostomia among adults and identify how many of the ones experiencing xerostomia have Sicca and Sjogren's syndromes. MATERIALS AND METHODS: This cross-sectional study included 1405 35-74-year-old Lithuanians (51.7% response rate) from the five largest Lithuanian cities and 10 peri-urban and rural areas that were randomly selected from each of the 10 Lithuanian counties. Xerostomia was determined by the self-reported experience of dry mouth as "often" or "always". A dentist diagnosed Sicca syndrome by unstimulated whole sialometry and the Schirmer's test, and all cases were referred to a rheumatologist to confirm Sjogren's syndrome. Self-reported questionnaires collected data about the determinants. RESULTS: The prevalence of xerostomia was 8.0% (n = 112), Sicca syndrome was diagnosed for 8 participants (0.60%), and Sjogren's syndrome for 2 participants (0.14%), with this being the first time it was diagnosed. Experiencing xerostomia was associated with older age (OR 1.7, 95% CI 1.1-2.6), urban residence (OR 3.3, 95% CI 1.6-5.0), presence of systemic diseases (OR 2.5, 95% CI 1.4-3.3), and the use of alcohol (OR 0.6, 95% CI 0.4-0.9). The higher proportion of participants with Sicca syndrome involved females, of older age, having systemic diseases, and using medications. CONCLUSIONS: The prevalence of xerostomia was 8.0% and the determinants of xerostomia were older age, urban residence, systemic diseases, and absence of using alcohol. In total, 0.6% of participants had Sicca syndrome, which was more prevalent among females, older subjects, those with systematic diseases, and those using medications. Sjogren's syndrome was diagnosed in 0.14% of participants. Clinical relevance Dental clinicians need to be trained to identify potential Sjogren's syndrome cases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".