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A Meta-analysis of complications of orbital blowout fracture by surgical approaches

2019· article· en· W4405800423 on OpenAlexaboutno aff
Jinhai Yu, Hongfei Liao, Hao Luo, Meng-Lin Shi, Qihua Xu

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsnot available
Fundersnot available
KeywordsOrbital FractureFracture (geology)MedicineGeologySurgeryOrthodonticsPaleontology

Abstract

fetched live from OpenAlex

AIM:To investigate the effect of conjunctival approach and skin approach on postoperative complications in orbital blowout fracture through Meta-analysis. METHODS: Search literatures in PubMed, Web of Science, Cochrane library, OVID, Chinese biomedical literature database, Weipu, Wanfang and CNKI database from the establishment of the database to May 30, 2018. The main contents included randomized controlled trials and cohort studies about comparing the postoperative complications of orbital blowout fracture through the transconjunctival approach and subciliary approach. Meta-analysis of the incidence of complications was performed using Review Manager 5.3 statistical software. RESULTS: A total of 7 cohort studies were included. The Newcastle Ottawa Scale(NOS)score showed that the quality of the included literature was above 6 points. Meta-analysis showed no significant difference in odds ratio(OR)between the transconjunctival approach group and subciliary approach group \〖<i>OR</i>=0.74, 95% <i>CI </i>(0.44-1.24),<i> P=</i>0.25\〗. Sensitivity analysis showed that the results of the Meta-analysis were stable and reliable. Funnel plot analysis showed that there might be publication bias in the included literature. CONCLUSION: The effect of skin approach and conjunctival approach on the incidence of postoperative complications of orbital blowout fractures is not significant. The two approaches have their own advantages and disadvantages. It is necessary to combine the clinical practical considerations to select the most suitable surgical approach.

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 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 score0.177
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.000

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 head0.472
GPT teacher head0.542
Teacher spread0.070 · 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.

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

Citations1
Published2019
Admission routes1
Has abstractyes

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