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Record W4404863302 · doi:10.62347/oglu3531

Factors affecting aesthetic results in patients undergoing craniofacial reconstruction following maxillofacial trauma

2024· article· en· W4404863302 on OpenAlex
Zhisheng Li

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueAmerican Journal of Translational Research · 2024
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCraniofacialMedicineDentistryOrthodonticsGeneral surgeryPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate the factors influencing the cosmetic outcomes and prognosis of patients undergoing maxillofacial trauma reconstruction. METHODS: A retrospective analysis was conducted on the clinical data of 335 patients who underwent maxillofacial trauma surgery criteria at Yunfu People's Hospital from March 2016 to June 2023. The Face-Q facial cosmetic rating scale was utilized to evaluate outcomes, with scores above 60 deemed the good prognosis group (n=234) and scores below 60 as the poor prognosis group (n=101). Two groups were compared in terms of demographic data, type of trauma, clinical presentation, intraoperative indicators, postoperative serum parameters and nutritional levels, Hamilton Anxiety Scale (HAS), Pittsburgh Sleep Quality Index (PSQI) sleep quality scores. Postoperative recovery and the incidence of complications were documented. Correlation analysis was performed, and Logistic regression analysis was used to determine influencing factors. RESULTS: Patients in the good prognosis group were significantly younger than those in the poor prognosis group (38.15 ± 10.32 vs. 46.69 ± 12.15, P < 0.001). Postoperative protein intake (65.81% vs. 33.66%, P < 0.001) and levels of anxiety (5.57 ± 1.52 vs. 6.61 ± 1.47, P < 0.001) were also better in the good prognosis group. There were significant differences in scar formation (5.57 ± 1.52 vs. 6.61 ± 1.47, P < 0.001), postoperative complications (2.56% vs. 8.91%, P=0.022) and scar hypertrophy (1.28% vs. 6.93%, P=0.015) between the two groups. Logistic regression analysis revealed that age (OR=1.07, 95% CI: 1.039-1.109), protein intake adequacy (OR=0.297, 95% CI: 0.141-0.625), HAS scores (OR=1.295, 95% CI: 1.011-1.658), infection (OR=11.579, 95% CI: 2.656-52.274), and Vancouver Scar Scale (VSS) score (OR=15.672, 95% CI: 7.379-33.285) were significantly associated with aesthetic outcomes. The ROC analysis showed that their combined prediction had an AUC of 0.920, indicating good predictive value. CONCLUSIONS: Younger age, adequate protein intake, lower anxiety scores, better scar assessment, and lower infection rates were associated with better prognosis. These findings emphasize the importance of addressing these factors to optimize outcome in craniofacial trauma reconstruction.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.382
Teacher spread0.318 · 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