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Record W4412809431 · doi:10.2196/77210

Unilateral Lefort I advancement Versus Dentoalveolar Transport Distraction in patients with large Alveolar Clefts: Protocol for a Prospective Observational Study. (Preprint)

2025· article· en· W4412809431 on OpenAlexvenueno aff
Kundan Shibjee Jha, Nitin Bhola

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyPreprintDentistryMedicineDistractionDistraction osteogenesisProtocol (science)OrthodonticsPsychologyComputer scienceAlternative medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background Cleft lip and palate is a complex congenital defect that can present functional and esthetic challenges, particularly in patients with large alveolar clefts for which surgical management is indicated. In contrast to traditional treatment techniques such as autologous bone grafting, newer techniques include unilateral Le Fort I osteotomy advancement and dentoalveolar transport distraction osteogenesis and have been shown to be useful in the treatment of maxillary hypoplasia and large alveolar clefts. These techniques may help improve both esthetic and function in patients with substantial tissue deficiencies as well as in patients with scarring. Objective This study aims to compare the outcomes of unilateral Le Fort I advancement and dentoalveolar transport distraction in the management of large alveolar clefts, specifically focusing on the closure of alveolar gaps, maxillary arch form, stability of the advanced or distracted segment, and wound healing. Methods This prospective observational study is being conducted at the Department of Oral and Maxillofacial Surgery, Siddharth Gupta Memorial Cancer Hospital, in collaboration with the Sharad Pawar Dental College in Maharashtra, India. Patients aged 9 to 25 years with unilateral alveolar clefts measuring 1 cm or greater will be included. Patients with smaller clefts, bilateral clefts, or those who are unsuitable for surgery will be excluded. The study will evaluate 14 patients, divided into 2 groups: group A will undergo dentoalveolar transport distraction, whereas group B will undergo unilateral Le Fort I advancement. We will assess the closure of the alveolar gap, arch form, stability of the advanced or distracted segment, and soft tissue healing. Through cone beam computed tomography and maxillary occlusal view, radiographic parameters of closure of the alveolar gap and arch form will be evaluated. The outcome measures will be statistically analyzed on RStudio software, with appropriate tests applied to each outcome measure. P <.05 will be considered significant. Results As of June 2025, institutional ethical clearance has been obtained and patient recruitment is ongoing. Recruitment began in April 2023, with 12 patients enrolled as of June 2025. Data collection is expected to be completed by December 2025, and results will be published in mid-2026. Conclusions This study aims to provide evidence-based guidance for the management of large alveolar clefts by comparing 2 graftless surgical techniques: unilateral Le Fort I advancement and dentoalveolar transport distraction. The findings are expected to help clinicians select the most suitable surgical approach based on individual case requirements, cleft morphology, and long-term outcome expectations. Ultimately, the study will contribute to optimizing cleft care strategies with reduced donor site morbidity and improved postoperative stability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0260.003

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 head0.149
GPT teacher head0.529
Teacher spread0.381 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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".

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Citations0
Published2025
Admission routes1
Has abstractno

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