Evidence map›Paper›PMID 41053716›Full record

ArticleBMC oral health2025

High degree of dental neglect characterizes adult patients hospitalized with severe odontogenic infections: a retrospective cross-sectional study.

Sofie Holmboe Dahl, Rasmus Søndenbroe, Simon Storgård Jensen, Esben Boeskov Øzhayat, Merete Markvart

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

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sofie Holmboe DahlSection of Clinical Oral Microbiology, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-6649-0976
Rasmus SøndenbroeSection for Oral Biology and Immunopathology, Department of Odontology, University of Copenhagen, Copenhagen, Denmark. rasmus.soendenbroe@sund.ku.dk.ORCID http://orcid.org/0009-0003-6533-4941
Simon Storgård JensenSection for Oral Biology and Immunopathology, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-3519-4103
Esben Boeskov ØzhayatSection of Oral Health, Society and Technology, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.ORCID http://orcid.org/0000-0001-8656-0292
Merete MarkvartSection of Clinical Oral Microbiology, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-9524-9233

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDental neglect is associated with deteriorated oral health, which can lead to the development of severe odontogenic infections (SOI) eventually requiring hospitalization. The clinical impact of risk factors for dental neglect remains unknown. This study aims to identify signs of dental neglect in patients hospitalized with odontogenic infections with the overall goal of early detection and prevention.

methodsThis study is a retrospective cross-sectional analysis of 384 patients previously hospitalized with a SOI. Patients completing the Dental Neglect Scale (DNS) were included. The patients were divided into two groups based on high and low DNS scores, and were compared in terms of clinical, paraclinical, radiographic, and sociodemographic variables using unadjusted and adjusted estimates (chi-square test of independence, independent sample t-test, and binary logistic regression models).

resultsA total of 163 patients completed the DNS (response rate 51.7%), of whom 78 patients (47.8%) had a high DNS score. A high DNS score was significantly related to male sex (p ≤ 0.001), to the indication for having teeth extracted during hospitalization (p = 0.007), and having two or more decayed teeth or teeth with apical periodontitis, with an odds ratio of 3.2 (p = 0.025) and 2.9 (p = 0.019), respectively. The score of Decayed, Missing, and Filled Teeth (DMFT) (p = 0.982) and attendance of dental care prior to hospitalization (p = 0.107) was not correlated with the DNS score.

conclusionsApproximately half of all patients hospitalized with SOI have a high degree of dental neglect. From a clinical perspective, the study addresses the potential of using the clinical threshold or the DNS in the early identification of patients at risk of SOI. However, further research on the topic is necessary to define the target of preventing patients at risk of SOI within the healthcare system. Exploring dental neglect in a non-selected study population might elucidate the validity and clinical usability of the threshold.

Indexed as

Focal Infection, DentalHospitalizationAdultAgedCross-Sectional StudiesDental CariesFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsAbscessOral healthPeriapical periodontitisSelf-Neglect

Identifiers

PMID41053716
PMCPMC12502255

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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.