A Multi-National Questionnaire-Based Analysis of Dental Students’ Knowledge of the Management of Deep Caries and the Exposed Pulp
Bibliographic record
Abstract
INTRODUCTION AND AIMS: To evaluate knowledge regarding the management of deep carious lesions and exposed pulps among undergraduate and postgraduate endodontic students from ten dental institutions across ten countries, and the impact of operator (material, antibiotic prescription) and patient-related (age, symptoms) factors on their treatment protocols. METHODS: An online questionnaire was distributed to evaluate student knowledge of the management of deep caries and exposed pulp related to four clinical scenarios. Simple descriptive statistics were used to describe the data and McNemar tests were employed to identify significant differences between the scenarios. The P-value was set at 5%. RESULTS: A total of 435 undergraduates and 139 postgraduates from ten dental schools participated in this survey. The final survey included 401 responses from undergraduates and 127 from postgraduates for statistical analysis. When symptoms were present, the majority of undergraduate and postgraduate students preferred non-selective (complete) caries removal over selective (partial) caries removal in young patients. The majority of postgraduates preferred partial pulpotomy in younger patients and pulpectomy and root canal treatment (RCT) in older patients. The majority of undergraduates preferred pulpectomy and RCT in both young/old patients when symptoms were present. The majority of undergraduates and postgraduates opted for mineral trioxide aggregate and Biodentine, respectively, when treating the exposed pulp. Systemic antibiotics were not recommended by both undergraduates and postgraduates, regardless of the patient's age and symptoms. CONCLUSION: Among the scenarios surveyed, the majority of undergraduates and postgraduates preferred: a) pulpectomy and RCT for older patients in the presence or absence of symptoms; b) hydraulic calcium silicate cements as pulp capping material; and c) did not recommend systemic antibiotics. CLINICAL RELEVANCE: The majority of students choose non-selective (complete) caries removal in all cases and if the pulp is exposed, the use of hydraulic calcium silicate cements iwas the preferred material. Systemic antibiotics are considered unnecessary, irrespective of the patient's age and symptoms.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".