Oral health status of long-term care residents-a vulnerable population.
Bibliographic record
Abstract
OBJECTIVE: To conduct an observational, cross-sectional survey of the oral health status of adults ≥ 45 years of age in rural and urban long-term care (LTC) facilities in Nova Scotia, Canada. METHODS: Residents capable of informed consent were recruited by LTC staff in a stratified random sample of LTC facilities. Calibrated personnel administered standard clinical and quality-of-life instruments. RESULTS: Of the 335 adults (74% female) surveyed (mean age 80.8 ± 11.6 years), only 25% reported having regular dental care. Although 76% described their oral health as good or excellent, 41% were edentulous, 41% had some mucosal abnormality, 36% reported xerostomia and 25% had perceived or self-reported untreated dental conditions. Most mandibular dentures were nonretentive (59%) and almost half were unstable (49%). Among the dentate, 51% had untreated coronal caries, 44% had untreated root caries and 67% had attachment loss of ≥ 4 mm at ≥ 1 site. Predictors of coronal decay were a debris score ≥ 2 (adjusted odds ratio [adj OR] = 2.12; p = 0.045) or a history of smoking (adj OR = 1.02 per year of smoking; p = 0.024). Predictors of root caries were participants' perceiving a need for dental treatment (adj OR = 2.56; p = 0.015) or a history of smoking (adj OR = 1.02 per year of smoking; p = 0.026). CONCLUSIONS: This epidemiologic study of the oral health of LTC residents revealed a high prevalence of untreated oral disease and low use of oral care services, highlighting the need for better access to oral care for this population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".