Evidence map›Paper›PMID 39590244›Full record

ArticleBiomimetics (Basel, Switzerland)2024

Histomorphometric Analysis of Osseointegrated Intraosseous Dental Implants Using Undecalcified Specimens: A Scoping Review.

Stefan Peev, Ralitsa Yotsova, Ivaylo Parushev

Abstract readScoping Review
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Stefan PeevDepartment of Periodontology and Dental Implantology, Faculty of Dental Medicine, Medical University of Varna, 9002 Varna, Bulgaria.ORCID 0000-0003-4846-013X
Ralitsa YotsovaDepartment of Oral Surgery, Faculty of Dental Medicine, Medical University of Varna, 9002 Varna, Bulgaria.ORCID 0000-0001-7491-5607
Ivaylo ParushevDepartment of Clinical Medical Sciences, Faculty of Dental Medicine, Medical University of Varna, 9002 Varna, Bulgaria.ORCID 0000-0002-9660-3353

Funding

the European Union-NextGenerationEU BG-RRP-2.004-0009
6 · The paper itself

Abstract

Bone histology and histomorphometry are reliable diagnostic tools for the assessment of the bone-implant interface, material safety and biocompatibility, and tissue response. They allow for the qualitative and quantitative analysis of undecalcified bone specimens. This scoping review aims to identify the most common staining techniques, study models for in vivo experiments, and histomorphometric parameters used for quantitative bone evaluation of osseointegrated dental implants in the last decade. The Web of Science, PubMed, and Scopus databases were searched on 1 July 2024 for relevant articles in English, published in the last ten years, and the data were exported to an MS Excel spreadsheet. A total of 115 studies met the eligibility criteria and were included in the present review. The results indicate that the most common study models are dogs, rabbits, and pigs. Some of the most frequently used methods for the assessment of the bone-implant interface are the Toluidine blue, Stevenel's blue with Van Gieson, and Levai-Laczko stainings. The results from this study demonstrate that the most commonly used histomorphometric parameters in implant dentistry are the bone-to-implant contact (BIC), bone area fraction occupancy (BAFO), bone area (BA), and bone density (BD). This review presents the recent trends in histomorphometric analysis of dental implants and identifies some research gaps that necessitate further research.

Indexed as

dental implanthistologyhistomorphometrynon-decalcifiedosseointegrationundecalcified

Identifiers

PMID39590244
PMCPMC11592138

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.