Prevalence of Taurodontism in the United Arab Emirates: A Retrospective Study with a Global Comparison
Bibliographic record
Abstract
Objective: Taurodontism is a developmental dental anomaly that can significantly impact various dental treatment procedures. This study retrospectively investigated the prevalence of taurodontism in the United Arab Emirates (UAE) and compared it with global prevalence rates. Materials and Methods: A total of 1,355 panoramic radiographs were retrospectively examined to identify cases of taurodontism. An extensive review of the literature was performed across three databases to identify studies reporting the global prevalence of taurodontism. Statistical Analysis: The global prevalence data were compared with findings from the UAE using Fisher's exact test or chi-square test. Results: The prevalence of taurodontism in Sharjah (UAE) was 0.66%. It was observed three times more frequently in the mandible (73.3%) than in the maxilla (26.7%). The mandibular second molar (46.7%) was the most affected tooth. Hypotaurodontism (66.7%) was the most prevalent type identified in the study. The pooled prevalence of taurodontism in the UAE was 1.4%, which closely aligned with the average prevalence observed in Middle Eastern countries. Based on the retrieved literature, North America recorded the highest prevalence at 31.3%, whereas the Middle East had the lowest prevalence at 1.9%. Conclusion: Taurodontism is less prevalent in the UAE compared with other regions worldwide. Globally, the occurrence of taurodontism varies significantly, with the highest prevalence rates reported in Canada, China, and Brazil. These differences may be influenced by genetic and environmental factors, variations in diagnostic methodologies, sample sizes, and inconsistencies in the inclusion and exclusion criteria applied across studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".