Early Dental Caries and Their Associated International Classifications of Disease Morbidity: A 16-Year Population Study
Bibliographic record
Abstract
Objective: The study objective was to examine the relationship between dental caries diagnosed before the age of four and ICD diseases over a 16-year period. Methods: The sample of approximately 33,531 (48% female) individuals having a total of 2,864,790 physician diagnoses over 16 years comprised a the cohort two groups, one with (2.7% of the sample) and one without dental caries (dependent variable) that were under the age of four years in the first two years of the sample data. Categories of dental caries and associated gingivitis and periodontal disease were based on the International Classification of Disease (ICD Version 9) diagnostic codes 521-523. The sample was described. Odds ratios comparing those with and without dental caries and the main ICD classes were calculated. Additionally, the ratio of each ICD diagnosis frequency comparing the cohort groups were calculated and represented the diagnoses assigned over the first 15 physician visits. Results: Males had proportionally more dental caries diagnosed. Diagnoses were made predominantly by general practitioners. Within the dental caries cohort group, associated ICD diagnoses were over-represented in both odds ratios and within individual ICD diagnoses on the first diagnosis and over the first 15 diagnoses in time. Conclusion: Dental caries diagnosed in very young children before the age of four are associated with multi-morbidity over subsequent years. Sex differences and patterns of associated morbidity may contribute to a better understanding of early life vulnerability to dental caries and their sequelae.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".