RELIABILITY, APPLICABILITY AND EXPANSION OF ACCESS TO DIAGNOSIS THROUGH TELECONSULTATION IN STOMATOLOGY: a scoping review
Bibliographic record
Abstract
Teledentistry comprises several modalities of remote dental care, notably teleconsultation—defined as the exchange of clinical information among healthcare professionals—and telediagnosis, which involves issuing diagnostic reports. However, the impact of teleconsultation on the early diagnosis of oral lesions remains uncertain. This study aims to synthesize the available evidence and provide a comprehensive overview of the reliability, applicability, and potential to expand access to the diagnosis of oral lesions, including malignant and potentially malignant disorders, through teleconsultation in oral medicine. A systematic search was conducted in MEDLINE/PubMed, Cochrane Library, EMBASE, LILACS, and gray literature up to January 2025, with no language restrictions. Methodological quality and risk of bias were assessed using specific tools: Newcastle-Ottawa (cohort studies), JBI (cross-sectional studies), QUADAS-2 (diagnostic accuracy studies), and GRADE (certainty of evidence). A narrative synthesis was performed. A total of 25 observational studies (cross-sectional, cohort, and diagnostic accuracy) were included, involving 8,746 patients assessed via teleconsultation, although not all studies reported the exact number of participants. Among the evaluated cases, 612 were confirmed as malignant. Diagnostic agreement between general practitioners and specialists ranged from 60% to 100%, being higher in studies with standardized protocols, prior training, or those conducted by specialists. Remote diagnostic accuracy reached up to 97% compared to the gold standard. Overall satisfaction with the service was high (96.5%), and 75% of patients reported the procedure as comfortable. Some studies demonstrated that teleconsultation contributes to expanding access to diagnosis in oral medicine, as reflected in an increase in referrals. Despite promising findings, the high methodological heterogeneity (>85%) among studies precluded a robust meta-analysis and limited the generalizability of results.
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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 | 0.076 | 0.297 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| 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".