Evidence map›Paper›PMID 40181387›Full record

ArticleBMC oral health2025

Evaluating the relationship between periodontal bone loss in maxillary posterior teeth and Schneiderian membrane thickness.

Cemre Ekşi, Başak Şeker

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Cemre EkşiDepartment of Periodontology, Faculty of Dentistry, Eskişehir Osmangazi University, Eskisehir, 26040, Turkey. dtcemredag@gmail.com.
Başak ŞekerDepartment of Periodontology, Faculty of Dentistry, Antalya Bilim University, Antalya, 07190, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo understand the potential impact of periodontal disease on maxillary sinus health, this study aimed to evaluate the relationship between periodontal bone loss and maxillary sinus membrane thickness using cone beam computed tomography (CBCT).

methodsNine hundred thirty-nine maxillary posterior segment images from 527 subjects were retrospectively scanned via CBCT. A total of 826 premolar, 701 first molar and 817 s molar teeth were examined. The maxillary sinuses in each segment were divided into anterior, median and posterior regions according to the tooth roots they were associated with, and their membrane thicknesses were measured and categorized. The effects of age and gender on membrane thickness were evaluated. T tests and one-way ANOVA were used to analyze differences between groups, followed by post hoc Tukey tests for multiple comparisons. Additionally, correlation analyses were performed to investigate the relationships between the categorized membrane thicknesses and periodontal bone loss.

resultsA significant positive correlation was found between maxillary sinus membrane thickness and periodontal bone loss in all three regions (p < 0.05). Periodontal bone loss was greater in regions with class IV membrane thickness (p < 0.001). Sinus membrane thickness and periodontal bone loss were greater in men and older people (p < 0.001).

conclusionsThis study found a relationship between maxillary sinus membrane thickness and bone loss due to periodontal disease in the maxillary posterior region. Considering the relationship between periodontal disease and sinus infections, it can be concluded that progressive and untreated periodontal disease may be associated with infections in close anatomical structures such as the maxillary sinus. These results may contribute to the development of clinical decisions and treatment plans in implantology practices.

Indexed as

Alveolar Bone LossMaxillary SinusNasal MucosaAdolescentAdultAgedCone-Beam Computed TomographyFemaleHumansMaleMaxillaMiddle AgedMolarRetrospective StudiesYoung AdultCBCTMaxillary sinusPeriodontal bone lossSchneiderian membraneSinus membrane thickness

Identifiers

PMID40181387
PMCPMC11967070

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LicenceCC BY-NC-ND
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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.