Changes In Human Mandibular Condylar Angulation In Patients With Degenerative Joint Disease (DJD)
Bibliographic record
Abstract
Objective: The aim of this retrospective study was to validate the relationship between an increased horizontal condylar angulation (HCA), decreased intercondylar angulation (ICA), and reduced height of mandibular condyles on cone-beam computed tomography (CBCT) scans of patients in Manitoba. The focus of the study was to assess the clinical and radiographic appearance of the mandibular condylar angulation and height changes. Method: Seventy-six mid-field CBCT scans (152 mandibular condyles) from the University of Manitoba Dental clinic in Winnipeg, Manitoba, will be analyzed. The anatomic changes of each condyle will be analyzed. The measurements will be recorded using Invivo 7 software (Anatomage Inc., USA). Results: Patients with DJD showed a statistically significant increase in HCA, with a medially inclined condylar rotation, compared to non-DJD condyles (27.18° vs. 22.3°, P < 0.05). ICA was statistically significantly decreased in those with DJD compared to those without (127.6° vs. 135.4°, P < 0.05). Condylar length was also decreased in those with a unilateral presentation of DJD (16.62 vs. 21.01, P <0.05). Conclusion: DJD associated with the mandibular condyles is associated with measurable morphological changes on CBCT scans, including an increased HCA, and decreased ICA and condylar height. Our findings suggest that the use of CBCT imaging can help identify osseous changes in those who have DJD in symptomatic TMJs.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".