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Record W2995555483 · doi:10.14740/jcs387

Maxillofacial Fractures: A Three-Year Survey

2019· article· en· W2995555483 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Current Surgery · 2019
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)Oral and maxillofacial surgeryMaxillaRadiological weaponInjury preventionRetrospective cohort studyPoison controlRoad trafficDentistrySurgeryEmergency medicine

Abstract

fetched live from OpenAlex

Background: Maxillofacial fractures constitute a substantial proportion of trauma globally. The main causes worldwide are road traffic accidents (RTAs), falls, assaults, sports, firearm injuries and industrial trauma. The highest incidence is commonly seen in the young age group with majority being male. The most common site in maxillofacial injuries is the mandible followed by the zygomatic complex, maxilla, and alveolar process. Maxillofacial trauma also poses a significant socioeconomic burden on affected individuals. Hence appropriate treatment and prevention of these morbidities and possible mortality is necessary. This study is therefore aimed at analyzing the prevalence, pattern of presentation of maxillofacial injuries at Lagos State University Teaching Hospital (LASUTH) in Western Nigeria. Methods: A retrospective review of 182 patients diagnosed and treated for maxillofacial injuries at the Oral and Maxillofacial Department of the LASUTH was conducted. Data were obtained from clinical notes and records of radiological findings noting patient ’s age, gender, etiologic factors (RTA, assault, sport, and fall), anatomic site of injury and different definitive treatment modalities. The data were analyzed by SPSS version 20 using various descriptive statistical tools. Mean and standard deviation were calculated for quantitative variable like age while frequency and percentage were calculated for qualitative variables like gender and site of fracture. Results: Majority of patients were male (72.0%) with a male to female ratio of 1:0.4. Most patients were between 31 and 40 (34.1%) years of age. RTA accounting for 73.1% of the injuries was the most common cause for maxillofacial injury followed by assault (19.2%). Majority of injuries due to RTA were of motorcycles accidents (33.6%). The most common sites of fracture out of 226 sites were in the mandible (62.8%, P = 0.003). Among the mandibular fracture sites, 28.2% affected the body of the mandible. Majority (31.9%) of the studied patients presented within 24 h (<= 1 day). Out of the 182 patients, 68.1% were treated by close reduction. Conclusions: RTA represented the major etiological factor of maxillofacial injuries. The mandible remains the most affected bone of the facial skeleton. Closed reduction is the most common approach used for treatment. J Curr Surg. 2019;9(4):51-56 doi: https://doi.org/10.14740/jcs387

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.328
Teacher spread0.270 · 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