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Record W4403474679 · doi:10.1111/cid.13373

Soft tissue response to titanium healing abutments treated by Er: <scp>YAG</scp> laser or plasma spray: A randomized controlled feasibility clinical study with <scp>SEM</scp> and histological analysis

2024· article· en· W4403474679 on OpenAlexvenueno aff
Dalia Yossri, Nevine H. Kheir El Din, Nermeen Afifi, Doaa Adel‐Khattab

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2024
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsOsseointegrationSoft tissueImplantDentistryAbutmentMedicineTitaniumMaterials scienceBiomedical engineeringSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: Soft tissue seal around implants ensures stable osseointegration and a long-term survival of dental implants. Different surface modification and decontamination for implant abutments were endorsed in order to improve peri-implant soft tissue healing, such as laser, plasma spray, acid etching, and steaming. The aim of this study was to evaluate the response of peri-implant soft tissue to titanium abutments treated with Erbium-doped: Yttrium-Aluminum-Garnet (Er:YAG) laser versus plasma spray. METHODS: Twenty-four patients who required implant placement in the maxillary arch participated in this study. Patients were divided into three groups, abutments treated with Er:YAG laser versus cold plasma spray and untreated abutments. Fourteen days following the implant abutment insertion, soft tissue peri-implant biopsies were taken for histological, histochemical, and immunohistochemical evaluation. Scanning electron microscopy was done for the abutments; plaque index (PI) and gingival index (GI) were assessed 14 days and 3 months following final restoration. RESULTS: Regarding the histological results, the least mean inflammatory cell count was in the plasma group (174.09 ± 40.67), followed by the laser group (654.27 ± 85.95) and the control group (852.00 ± 117.98), with statistically significant differences between them. The mean area fraction of collagen fibers showed the highest value in the plasma group (9.73 ± 1.91), followed by the laser group (3.25 ± 0.49), while the lowest value was found in the control group (1.17 ± 0.51). The immunohistochemical expression of E-cadherin was significantly higher and uniformly distributed in the plasma group (42.4 ± 11.2%) followed by the laser group (15.4 ± 4.07%) and the control group (6.8 ± 1.7%). SEM analysis of healing abutments showed fibroblast-like cells, which were more developed with dense fibers in the plasma group; laser group fibers showed fewer and more delicate fibers than the plasma group, while no fibers were detected in the control group. CONCLUSION: Within the limitations of this feasibility study, the present data concluded that plasma spray and Erbium: YAG laser can be used for abutment surface treatment to achieve better peri-implant soft tissue healing. Clinically and histologically, plasma spray showed a better effect on the peri-implant soft tissues by reducing the inflammatory reaction, promoting collagen fiber formation, higher fibroblast-like cell attachment, and upregulating E-cadherin expression than Erbium: YAG laser and control groups.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.090
GPT teacher head0.475
Teacher spread0.385 · 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 designRandomized trial
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

Citations5
Published2024
Admission routes1
Has abstractyes

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