Evidence map›Paper›PMID 39619719›Full record

ArticleThe Saudi dental journal2024

Digital photometric analysis as a non-invasive method to determine gingival phenotype: A comparative study.

Seham Altaweel, Maha Sehli, Mirna Khogeer, Rahmah Ayyash, Saleh Al Zahrani, Thamer Al-Ghalib, Mohamed Abdelrasoul

Abstract read
In one paragraph

Article in The Saudi dental journal, 2024. 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

7 authors.

Seham AltaweelGeneral Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
Maha SehliGeneral Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
Mirna KhogeerGeneral Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
Rahmah AyyashGeneral Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
Saleh Al ZahraniDental Clinics, General Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
Thamer Al-GhalibProsthodontics Division, Dental Clinical Sciences Department, General Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
Mohamed AbdelrasoulPeriodontics Division, Dental Clinical Sciences Department, General Dentistry Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Identification of periodontal phenotype is critical in clinical practice. Thick and thin tissues respond differently to inflammation, and trauma. It significantly influences the outcomes of restorative treatment, regenerative therapy, and success of implants and periodontal surgery. Periodontal phenotype can be assessed via invasive or non-invasive methods. This study aimed to establish the reliability of non-invasive methods in determining gingival phenotypes in comparison with validated methods. Methods: This preapproved cross-sectional observational study was conducted at Batterjee Medical College in Saudi Arabia. The participants were conveniently sampled based on the inclusion criteria. The clinical study utilized Colorvue® biotype probes to evaluate gingival tissue phenotype in the region of interest, intraoral digital scanner (IOS) (iTero® scanner), and digital photography. Densitometric acquisition of photographs and intraoral scans was performed using Adobe Photoshop to quantify three-dimensional color measurements expressed in Delta E values (ΔE). Furthermore, patient-reported experience measures (PREMs) were used to evaluate anxiety and pain perception. Values of p < 0.05 were considered statistically significant. Results: The analysis of color difference values (ΔE) revealed significant variations in color perception across methods for the thin, medium and very thick groups, indicating perceptible color differences (p < 0.001). The assessment of anxiety levels indicated a statistically significant decrease in stress levels in favor of the IOS method for the medium phenotype. Furthermore, perceived pain was significantly lower with the IOS method than with the probing method for all phenotypes. Conclusion: Densitometric analysis of standardized clinical photographs and intraoral scans of the marginal gingiva offers a promising, non-invasive, less stressful, and virtually non-painful method of periodontal phenotype evaluation with reliable numerical outputs. Furthermore, these data may be used to feed AI systems, where machines can learn to recognize color differences and possibly deduce phenotype assessments.

Indexed as

Digital dentistryGingival phenotypeIntraoral scannerNon-invasivePatient-reported experience measuresPeriodontal

Identifiers

PMID39619719
PMCPMC11605722

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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.