Dental Education in the Interior of a Brazilian State: Profile of Patients and Procedures Performed in a Teaching Clinic
Bibliographic record
Abstract
Objective: This study aimed to identify the profile of adult patients treated at the Integrated Clinic of the UFVJM Dentistry course in Diamantina-MG between 2010 and 2019. Methods: A retrospective analysis was conducted using patient records from individuals who had completed treatment and were discharged. Only fully completed and legible records were included, while those that were incomplete, illegible, or related to ongoing treatments were excluded. Data collected encompassed gender, age, place of origin, race, comorbidities (such as diabetes and hypertension), treatment duration, start and end year of treatment, smoking habits, alcohol consumption, and the types of procedures performed, categorized into various treatment groups. Results: Out of 469 records analyzed, 414 met the inclusion criteria. The majority of patients were female (63.5%), predominantly of mixed race (46.3%), with an average age of 34.1 years, and most resided in Diamantina (84.7%). The highest number of treatment initiations occurred in 2018 (41.6%), which also had the most discharges (38.4%). The average treatment duration was 66.3 days. Radiography was the most frequently performed procedure (22.3%), while endodontic treatment was the least common (2%). A positive correlation was identified between age and the creation of removable prostheses. Conclusion: The predominant profile of patients treated at the clinic consists of young, mixed-race women, primarily residents of Diamantina, who tend not to smoke but frequently consume alcohol. These findings provide insights into the demographic and treatment needs of the population served by the clinic, informing potential improvements in patient care and educational approaches in the dentistry program.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".