A Prospective Study of Periodontal Disease and Risk of Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To test for an association between periodontal disease (PD) and incident rheumatoid arthritis (RA) in a large prospective cohort. METHODS: We conducted a prospective analysis of history of periodontal surgery, tooth loss, and risk of RA among 81,132 women in the Nurses' Health Study prospective cohort. Periodontal surgery and tooth loss were used as proxies for history of PD. There were 292 incident RA cases diagnosed from 1992 to 2004. Information on periodontal surgery and tooth loss in the past 2 years was collected by questionnaire in 1992. Cox proportional hazards models were used to assess relationships between periodontal surgery, tooth loss, and risk of RA adjusting for age, smoking, number of natural teeth, body mass index, parity, breastfeeding, postmenopausal status, postmenopausal hormone use, father's occupation, and alcohol intake. RESULTS: Compared with those who reported no history of periodontal surgery or tooth loss, women with periodontal surgery or tooth loss did not have a significantly elevated risk of RA in multivariable-adjusted models (RR 1.24, 95% CI 0.83, 1.83; and RR 1.18, 95% CI 0.47, 2.95, respectively). In analyses stratified by ever and never-smokers, ever-smokers with periodontal surgery had an increased risk that was also nonsignificant. Those with severe PD (both history of periodontal surgery and tooth loss) did not have a significant increased risk. CONCLUSION: In this large cohort of American women, there was no evidence of an increased risk of later-onset RA among those with a history of periodontal surgery and/or tooth loss.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".