Sex and gender differences in periodontal disease: a cross-sectional study in Switzerland
Bibliographic record
Abstract
BACKGROUNDS: The role of sex- and gender-related traits has often been downplayed in clinical studies and periodontal disease is no exception. Sex and gender represent distinct biological and sociocultural factors that may independently influence periodontal disease. These factors can affect the risk and progression of periodontal disease as well as response to treatment. This clinical observational study was designed to evaluate gender distribution and the impact of sex and gender on health of gingival tissue using bleeding on probing and probing depth (Periodontal Screening Index "PSI"). METHODS: Four hundred thirty patients were included in this study. Clinical parameters were retrieved from standard examination and a questionnaire was used to assess gender. Sex was characterized as indicated in the birth certificate, a short version of a Swiss-Canadian gender questionnaire was used for the assessment of gender. In addition, patients were asked about self-attribution of gender and the gender Score (GS) was constructed for each subject. RESULTS: 53.0% (228 patients) were females and 47.0% (202 patients) males. No statistically significant differences were observed regarding sex distribution between the categorization of PSI in two and three groups (p = 0.68 and p = 0.57 respectively). The mean gender score (GS) in the subjects with Gingivitis/Mild Periodontitis was 51.75 ± 41.77 while in the subjects with claimed Periodontitis was 51.74 ± 40.55 (One-way ANOVA F = 0.00 p = 0.98). There was no statistically significant association between GS and periodontitis. CONCLUSIONS: This study is one of the first to examine both sex and gender using a validated score in relation to periodontal disease. The outcomes of the cross-sectional study demonstrate that gender is not an indicator for the presence of periodontal disease in Swiss population, emphasizing the need to consider sex and gender as separate factors in clinical studies. Clinical screening protocols may not need to be adjusted based on gender-related traits.
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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 | 0.001 | 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".