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Record W4415644375 · doi:10.1111/cid.70099

Reduced Surgical Complications in Graft‐Masked <scp>3D</scp> Ti Mesh for Alveolar Augmentation: A Retrospective Comparative Study

2025· article· en· W4415644375 on OpenAlexvenueno aff
Hui Gao, D. Chen, Chao Wang, Lingling Zheng, Chunjuan Wang, Liya Ai, Antonio Apicella, Yubo Fan

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2025
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesChongqing Science and Technology CommissionNational Natural Science Foundation of ChinaBeijing Municipal Natural Science FoundationChongqing Municipal Health Commission
KeywordsDental alveolusSurgical meshRetrospective cohort studyRegeneration (biology)Oral Surgical ProceduresTitanium

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess and compare the effectiveness of different bone grafting techniques, including unmasked meshes and graft-masked meshes approaches, for augmenting alveolar bone defects using 3D-printed titanium mesh (3D-TM). MATERIALS AND METHODS: This retrospective study included 34 patients (69 teeth with alveolar bone defects) who underwent guided bone regeneration (GBR) using 3D-printed titanium mesh (3D-TM). Patients were assigned to two groups: the unmasked meshes group (n = 17, 34 treatment sites) and the graft-masked meshes group (n = 17, 35 treatment sites). Cone beam computed tomography (CBCT) data of pre- and post-operative 3D-TM implantation were digitally reconstructed, with a minimum 6-month follow-up period. Clinical outcomes included titanium mesh exposure rates, pseudo-periosteum rates, and osteogenic efficiency metrics such as bone volume, vertical bone height/width, and bone contour. Bone volume was analyzed using samples t-tests, vertical bone height/width was analyzed using a generalized estimating equations (GEE) model, and bone contour was analyzed using the Mann-Whitney U test. Categorical outcomes were evaluated via Fisher's exact probability test. RESULTS: Clinical complications analysis revealed distinct outcomes between the two groups. Titanium mesh exposure occurred in 7 cases overall, with no statistically significant difference between the unmasked meshes group (5/17, 29.4%) and the graft-masked meshes group (2/17, 11.8%) (Fisher's exact test, p = 0.398). In contrast, pseudo-periosteum demonstrated a significant discrepancy, observed in 14/17 cases (82.4%) in the unmasked meshes group compared to 4/17 cases (23.5%) in the graft-masked meshes group (Fisher's exact test, p = 0.002). Notably, no infections occurred in either group. Analysis of osteogenic efficacy revealed significant intergroup differences in bone volume ratio (Independent samples t-test, df = 32, p < 0.05), vertical bone height ratio, and width ratio (GEE, df = 1, p < 0.05), and bone contour accuracy at the minimum and 25% percentiles (Mann-Whitney U test, p < 0.05). No significant differences were observed at the 50%, 75% percentile, or maximum value. CONCLUSION: The graft-masked meshes technique in 3D-TM guided bone regeneration surgery is a reliable and effective method for augmenting alveolar bone defects. This method effectively reduces procedure-related complications, including titanium mesh exposure and pseudo-periosteum, thereby improving osteogenic efficacy.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.181
GPT teacher head0.532
Teacher spread0.352 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

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