Two-versus three-screw osteosynthesis of the mandibular condylar head: A finite element analysis
Bibliographic record
Abstract
Titanium screws are commonly used for osteosynthesis of mandibular condylar head fractures. Evidence suggests that the insertion of three screws may result in better fracture stability. Two screws only, on the other hand, could reduce adverse effects, mainly bone resorption. This study aimed to investigate the biomechanical differences in mandibular condylar head osteosynthesis with two versus three titanium screws using finite element analysis. A finite element model of the mandible with a right type P condylar head fracture fixed with two or three titanium screws was analyzed in ANSYS Mechanical. The geometry of the model assembly was constructed in ANSYS Spaceclaim. Biomechanical load boundary conditions were obtained from a validated musculoskeletal model in AnyBody Modeling System™. The preprocessing of the finite element model and mapping of the obtained boundary conditions was done in docq VIT. Fracture displacement, fragment deformation, von Mises stress distribution, and reaction forces within the screws were evaluated in ANSYS for three different loading scenarios. Finite element analysis showed similar results when comparing osteosynthesis with two versus three titanium screws for all three loading scenarios. Contralateral molar loading resulted in the highest stress on both the fracture and the screws with the maximum von Mises stress being found at the condylar neck. Stress concentration within the screws was found in the fracture gap and was higher in the lateral fragment. In all scenarios, maximum von Mises stress values were smaller when forces were distributed among three screws. However, stability was also adequate when two screws were used. Mandibular condylar head osteosynthesis with two titanium screws appears to provide sufficient fracture stability. Further clinical studies are needed to clarify the implications of these results.
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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".