Can the FRAX tool be a useful aid for clinicians in referring women for periodontal care?
Bibliographic record
Abstract
OBJECTIVE: This study aims to compare periodontitis severity in postmenopausal women whose FRAX (World Health Organization Fracture Risk Assessment Tool) scores indicate a major risk for osteoporotic fracture (OPF) versus controls. METHODS: Participant charts from the Case/Cleveland Clinic Postmenopausal Wellness Collaboration 853-sample database were selected based on the following inclusion criteria: (1) aged between 51 and 80 years; (2) menopause for more than 1 year but less than 10 years; (3) nonsmoker; (4) hemoglobin A1c less than 7; and (5) no glucocorticoid, hormone, RANKL (receptor activator of nuclear factor-κB ligand) inhibitor, or bisphosphonate therapy within 5 years. FRAX score was calculated, and participants were organized into two groups: women with major OPF risk (FRAX scores >20%) and controls. Periodontal data were obtained from the charts. T test was used to assess differences in periodontal parameters between groups. RESULTS: Ninety participants had FRAX scores higher than 20% and were considered to have high OPF risk; 98 participants served as controls. Probing depth (mean [SD], 2.75 [0.66] vs 2.2 [0.57]), clinical attachment loss (3.15 [0.78] vs 2.73 [0.66]), alveolar bone height (0.58 [0.03] vs 0.60 [0.02]), and tooth loss (5.6 [1.96] vs 3.84 [1.94]) were significantly different between groups, whereas plaque score and bleeding on probing were not. CONCLUSIONS: Postmenopausal women whose FRAX scores suggest major OPF risk have significantly more severe periodontitis endpoints than controls even though oral hygiene scores do not significantly differ. These findings suggest to clinicians treating women after menopause that referral to a periodontist for disease screening may be appropriate for those women with high fracture risk based on FRAX scores.
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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 | 0.007 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".