Use of Dietary Supplements in Patients Seeking Treatment at a Periodontal Clinic
Bibliographic record
Abstract
Dietary supplement use may modify the risk of periodontal disease but effects on wound healing after periodontal procedures are less clear. This study characterized dietary supplement use by male and female patients (n = 376) attending a periodontal clinic-information that is essential for evidence-based intervention studies that may improve patient outcomes after periodontal procedures. Calcium, vitamin D, multivitamin and vitamin C were most commonly used. A greater (p ≤ 0.05) number of males took no supplements compared to females, and more (p ≤ 0.05) females than males took ≥ four supplements. Females took more (p ≤ 0.05) calcium, vitamin D, fish oil, green tea, magnesium, omega 3,6,9 and B vitamin complex. Younger patients (31-50 years) had the highest (p ≤ 0.05) frequency of no supplement use compared to older age groups. Patients over age 50 had a higher (p ≤ 0.05) frequency of using ≥ four supplements including calcium and vitamin D. Supplement use was lower (p ≤ 0.05) in smokers, particularly for calcium, fish oil, green tea and vitamin D. In conclusion, females, older individuals and non-smokers have higher supplement use. Future dietary intervention studies can focus on supplements with known biological activities-anti-inflammatory, antioxidant or osteogenic activity-that may enhance wound healing after reconstructive periodontal procedures.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".