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Record W4283075199 · doi:10.53350/pjmhs22165624

Subciliary and Subtarsal Incision in Management of Zygomatico-Orbital Fracture, A Study on Scar Assessment

2022· article· en· W4283075199 on OpenAlexaboutno aff
Rajesh Kumar, Syed Aijaz Ali Zaidi, Bhavesh Maheshwari, Khursheed Ahmed, Lajpat, Salman Shams

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVascularityOrbital FractureSurgery

Abstract

fetched live from OpenAlex

Objective: To evaluate outcome between the subciliary and subtarsal incision in management of zygomatico-orbital fracture in terms of postoperative scar assessment. Subject and Methods: A total 36 patients of either gender, age 21 to 40 years having isolated zygomatico-orbital fracture were selected by consecutive sampling (16 patients in Subciliary and 16 in Sub-tarsal group). Zygomatico-orbital fracture was confirmed by 3D CT scan and Occipitomental view of face. After surgery postoperative scar assessment (Pigmentation, Pliability, Vascularity and height) was performed using Vancouver scar scale. Results: Male participants accounted for 27 (84.4%) of the 32 zygomaticomaxillary complex fractured patients, followed by 5 female patients (15.6% ). With 17 (53.1%) patients, the age group 21-25 years was the most afflicted, followed by 26-30 years with 15 (46.9%) patients and a mean age of 25.59 ± 3.004 years. In all three postoperative weeks, the subtarsal group performed considerably better than the subciliary group in terms of postoperative scar evaluation. Conclusion: Scar formation was higher in subciliary group as compared to subtarsal group Keywords: Subtarsal, Subciliary, Zygomatico-orbital, Fracture,Scar, Assessment

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.020
GPT teacher head0.317
Teacher spread0.297 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

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