Dental imaging of trabecular bone structure for systemic disorder screening: A systematic review
Bibliographic record
Abstract
The purpose of this systematic review was to evaluate the potential use of dental imaging assessment of trabecular bone structure in the maxillomandibular complex as an adjuvant screening tool to identify systemic disorders. Five electronic databases and grey literature were searched. Studies were included if they investigated subjects with altered trabecular bone determined by dental radiographs. The QUADAS-2 assessed the risk of bias (RoB) among the studies, while the GRADE determined the strength of evidence. A total of 14 studies that included 1,466 individuals were considered eligible for the qualitative analysis. All studies presented an overall low RoB and low concern regarding applicability. Systemic disorders such as osteoporosis, osteogenesis imperfecta, diabetes, and primary hyperparathyroidism, with their respective control groups, were analyzed among the included studies. Osteoporosis was the condition presenting the most significant results, and 72% of the studies detected changes in the maxillomandibular trabecular bone structure. Studies exploring diabetic edentulous patients found less dense trabecular bone pattern (p < 0.05). In summary, periapical and panoramic radiographs, computed tomography, and cone beam computed tomography imaging could be considered useful for the assessment of the mandibular trabecular bone structure of patients affected by osteoporosis and patients with diabetes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".