Evidence map›Paper›PMID 42038185›Full record

ArticleGalen medical journal2025

Laboratory Investigation of the Effect of Three Decontamination Methods on Surface Alterations of Dental Implants :.

Shohreh Khalilzadeh, Soroush Etesami

Abstract read
In one paragraph

Article in Galen medical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Shohreh KhalilzadehDepartment of Prosthodontics, School of Dentistry, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Soroush EtesamiDepartment of Prosthodontics, School of Dentistry, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The present study aimed to evaluate the effectiveness of three decontamination methods on the surface alterations of dental implants and the removal of bacterial plaque from their surfaces. Materials and Methods: In this experimental in vitro study, 24 titanium cylinders with sandblasted, large-grit, acid-etched (SLA) surfaces were contaminated with Staphylococcus aureus to simulate biofilm formation. Samples were randomly assigned to four groups (n=6): titanium curette, diode laser, titanium brush, and saline flush control. Surface roughness (Ra and Rz) was measured using scanning electron microscopy (SEM) before and after cleaning. Colony-forming units (CFUs) were quantified post-treatment to assess bacterial removal. Statistical analyses included Kruskal-Wallis tests, Mann-Whitney pairwise comparisons, and one-way ANOVA with post hoc LSD tests (α=0.05). Results: Surface roughness differed significantly among groups after cleaning (Ra, P=.002; Rz, P=.002). Titanium curette and titanium brush produced smoother surfaces than diode laser and control, with the curette achieving the greatest reduction in roughness. CFU analysis revealed significant differences among groups (F=3.26, P=.043). Contrary to expectations, the saline flush control showed the lowest CFU counts, whereas titanium curette and titanium brush exhibited higher bacterial counts than control (P.05), and diode laser did not differ significantly from control (P=.151). Conclusion: The titanium curette and titanium brush caused the samples' most significant surface roughness changes. However, the effectiveness of these methods for bacterial plaque removal was lower than that of the control group and the Diode laser group.

Indexed as

Dental ImplantsImplant Surface RoughnessScanning Electron Microscope

Identifiers

PMID42038185
PMCPMC12894812

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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.