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Record W2947839608 · doi:10.1097/moo.0000000000000556

Current approaches to cleft lip revision

2019· review· en· W2947839608 on OpenAlexaff
Damir B. Matic

Bibliographic record

VenueCurrent Opinion in Otolaryngology & Head & Neck Surgery · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsVictoria HospitalLondon Health Sciences CentreSt Joseph's Health Care
Fundersnot available
KeywordsMedicinePsychosocialSurgeryLocal anesthesiaDentistry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Cleft lip repair requires multidisciplinary follow-up throughout a child's life and often requires lip revision surgery in adolescence to restore function and symmetry of the lip. There is significant variability in the approaches taken for lip repair and therefore a review of current techniques and subsequent guidance to secondary cleft lip repair is warranted. RECENT FINDINGS: New methods of secondary reconstruction can be divided into superficial or muscle related. Recent suggestions for superficial reconstruction include botulinum toxin injection, silicone gel sheeting, local flap reconstruction, fat grafting, and CO2 laser ablation. Suggestions for muscular reconstruction include pedicled prolabial flaps, modified Abbe flap, and orbicularis oris eversion. SUMMARY: Secondary cleft lip deformities can be classified as superficial or muscle related. Superficial problems require relatively minor treatments such as laser, local scar revisions, small local flaps, mucosal excision, or fat grafting. Muscle deformities generally require total lip revision and rerepair as a first step to achieving longstanding improvements in lip esthetics and function. Cleft lip revision should only be considered in concert with the patient, be based on the patient's concerns and desires, and offered at the appropriate timeline to improve social integration and/or psychosocial wellbeing.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.282
GPT teacher head0.412
Teacher spread0.130 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Otolaryngology & Head & Neck SurgerySame topicCleft Lip and Palate ResearchFrench-language works237,207