Evidence map›Paper›PMID 40756921›Full record

ReviewJournal of maxillofacial and oral surgery2025

Surface Characteristics and Their Influence on Osseointegration: A Scientometric Analysis with a Focus on Dental Implants.

Mayank Mathur, Peeyush Phogat, Mukesh Jewariya, Meher Wan

Abstract readReview
In one paragraph

Review in Journal of maxillofacial and oral surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Mayank MathurAcademy of Scientific & Innovative Research, Ghaziabad, Uttar Pradesh India.
Peeyush PhogatCSIR-National Institute of Science Communication and Policy Research, New Delhi, New Delhi India.
Mukesh JewariyaCouncil of Scientific and Industrial Research-National Physical Laboratory, New Delhi, New Delhi India.
Meher WanCSIR-National Institute of Science Communication and Policy Research, New Delhi, New Delhi India.ORCID 0000-0003-2954-9972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Surface roughness is a critical factor in implant technology, influencing osseointegration and biocompatibility. A thorough understanding of the research landscape is essential to track advancements, key contributors, and highlight emerging trends. Objective: To perform a scientometric analysis of research on surface roughness in implants, identifying trends, highly contributing institutions, collaboration networks, and emerging research areas. Methods: Data was collected from the Web of Science Core Collection using a structured search strategy focused on surface roughness and implant-related terms. Bibliometric techniques, including citation analysis, keyword co-occurrence mapping, and collaboration network visualization, were employed to analyze the dataset. Results: The analysis identified leading institutions, and highly cited publications in the field. Keyword trends indicated growing interest in 3D printing, novel biomaterials, and advanced surface modification techniques. Collaboration networks highlighted interdisciplinary engagement. Conclusion: While significant advancements have been made in understanding surface roughness in implant technology, future research should focus on long-term effects and standardized roughness parameters. Emerging technologies, such as additive manufacturing and bioengineered surfaces, present promising avenues for further innovation.

Indexed as

Biomedical implantsDental implantsScientometric analysisSurface roughnessSurface topography

Identifiers

PMID40756921
PMCPMC12316664

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.