MétaCan
Menu
Back to cohort
Record W4403691607 · doi:10.55730/1300-0144.5887

Open surgical approach to fractures of the mandibular condyle: surgical technique and associated complications

2024· article· en· W4403691607 on OpenAlexaboutno aff
Cenk Demirdöver, Alper Geyik

Bibliographic record

VenueTURKISH JOURNAL OF MEDICAL SCIENCES · 2024
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCondyleSurgery

Abstract

fetched live from OpenAlex

Background/aim: This study evaluates anatomical reduction and rigid internal fixation of mandibular condyle fractures using the preauricular retroparotid approach. It also discusses advantages, deficiencies, and associated complications of the technique. Materials and methods: This retrospective study reviewed the medical records of a total of 52 mandibular condyle fractures from 42 patients who were treated with open surgery using the preauricular retroparotid approach between January 2019 and January 2024. Preoperative and postoperative assessments included measurements of mouth opening (maximum interincisal distance), vertical mandibular movement, and facial paralysis. Moreover, the Vancouver Scar Scale (VSS) was used to evaluate scar quality at the surgical site. Descriptive statistics were used to summarize patient demographics, preoperative findings, and postoperative outcomes. Results: Anterior open bite was the most common finding, detected in 83% of the patients before surgery. The mean mouth opening of the patients increased significantly from 29 ± 4.94 mm to 37.76 ± 2.12 mm. Vertical mandibular movement exceeding 4 cm was a finding in more than half (52.3%) of the patients. The mean VSS score, indicating scar quality, was 1.64 ± 0.70, suggesting overall good cosmetic outcomes. Plate breakage in two patients was noted as a complication during follow-up. Conclusion: Several surgical techniques have been described for mandibular condyle fractures, each with its own benefits and limitations.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.384
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTURKISH JOURNAL OF MEDICAL SCIENCESSame topicFacial Trauma and Fracture ManagementFrench-language works237,207