Assessing the Relationship Between COVID-19 and Dental Decay Risk in Youth: A Retrospective Analysis
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted public health globally, with particular attention on the effects on children, adolescents, and young adults. This study aimed to investigate the potential relationship between COVID-19 and caries risk in this age group. METHODS: A retrospective chart review was conducted on 120 patients between the ages of six and 25 years who received dental treatment at a university-affiliated dental clinic between January 2020 and December 2021. Demographic and medical data were collected, and dental examinations were performed to record the number of decayed, missing, and filled teeth (DMFT) and decayed, missing, and filled surfaces (DMFS). Data were analyzed using descriptive statistics, chi-square test or Fisher's exact test, student's t-test or Mann-Whitney U test, and multivariate regression analysis. RESULTS: Of the 120 patients, 40 were COVID-19-positive, and 32 of those patients were at high caries risk. Of the 80 patients who were COVID-19 negative, 48 were at high caries risk. There was a statistically significant association between COVID-19 exposure and caries risk. Participants who tested positive for COVID-19 had 1.8 times higher odds of dental caries than those who tested negative. However, no significant association was found between caries risk and age, gender, or previous dental history. CONCLUSION: The findings suggest that COVID-19 may be a risk factor for caries in children, adolescents, and young adults. Dental professionals should consider COVID-19 exposure as a potential risk factor when assessing caries risk in this age group. Further research is needed to better understand the mechanism underlying this association.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".