Literature DB >> 28233170

Radiographic diagnosis of proximal caries-influence of experience and gender of the dental staff.

Margrit-Ann Geibel1, S Carstens2, U Braisch3, A Rahman4, M Herz5, A Jablonski-Momeni6.   

Abstract

OBJECTIVES: The aim of this study was to examine the influence of experience and gender on the radiographic detection of proximal caries lesions and on therapeutic decisions.
MATERIALS AND METHODS: A survey of 220 examiners (students and employees at three universities and dentists in the field) was taken using a standardized written questionnaire concerning radiographic diagnosis and therapy planning. An expert opinion of four dentists was determined as radiographic reference. A mixed effect logistic regression model was used for statistical evaluation and the odds ratio and p values were calculated (α = 0.05).
RESULTS: Examiners with experience had an almost four times greater chance of a correct assessment, if proximal caries lesion was present or not, than examiners with low experience (OR 3.7 (95% CI 2.4-5.8)). No gender-specific differences were discovered (OR women vs. men 0.9 (95% CI 0.6-1.4)). There was a relationship between the severity of the burnout effect on the x-ray and false positive caries diagnosis. Overall, 43% of respondents would plan invasive treatment in the enamel on a patient at low risk of caries and 78% on a high-risk patient. The results showed that the more experienced practitioners would be more likely to postpone restorative therapy on proximal caries until the lesion reached a later stage.
CONCLUSIONS: The results of this study suggest that examiner's experience influences the radiographic diagnosis of proximal lesions. No gender-specific differences could be found. CLINICAL RELEVANCE: Examiner's professional experience is an important factor when radiography is included for detection and treatment planning of proximal lesions.

Entities:  

Keywords:  Dental caries; Diagnosis; Gender; Proximal caries; Radiography

Mesh:

Year:  2017        PMID: 28233170     DOI: 10.1007/s00784-017-2078-2

Source DB:  PubMed          Journal:  Clin Oral Investig        ISSN: 1432-6981            Impact factor:   3.573


  59 in total

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2.  Diagnosis of secondary caries and crevices adjacent to amalgam.

Authors:  I Espelid; A B Tveit
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3.  Detecting and treating occlusal caries lesions: a cost-effectiveness analysis.

Authors:  F Schwendicke; M Stolpe; H Meyer-Lueckel; S Paris
Journal:  J Dent Res       Date:  2014-12-10       Impact factor: 6.116

4.  Underestimation of the prevalence of approximal caries and inadequate restorations in a clinical epidemiological study.

Authors:  J H Poorterman; I H Aartman; H Kalsbeek
Journal:  Community Dent Oral Epidemiol       Date:  1999-10       Impact factor: 3.383

5.  Some factors influencing observer performance in radiographic caries diagnosis.

Authors:  H G Gröndahl
Journal:  Swed Dent J       Date:  1979

6.  Variation in radiographic interpretation and restorative treatment decisions on approximal caries among dentists in Norway.

Authors:  I Espelid; A Tveit; O Haugejorden; P J Riordan
Journal:  Community Dent Oral Epidemiol       Date:  1985-02       Impact factor: 3.383

7.  Influence of education level and experience on detection of approximal caries in digital dental radiographs. An in vitro study.

Authors:  Kristina Hellén-Halme; Gunnel Hänsel Petersson
Journal:  Swed Dent J       Date:  2010

8.  French dentists' restorative treatment decisions.

Authors:  Sophie Doméjean-Orliaguet; Stéphanie Tubert-Jeannin; Paul J Riordan; Ivar Espelid; Anne B Tveit
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9.  Restorative treatment thresholds for interproximal primary caries based on radiographic images: findings from the Dental Practice-Based Research Network.

Authors:  Valeria V Gordan; Cynthia W Garvan; Marc W Heft; Jeffrey L Fellows; Vibeke Qvist; D Brad Rindal; Gregg H Gilbert
Journal:  Gen Dent       Date:  2009 Nov-Dec

10.  Radiographic interpretation and treatment decisions among dental therapists and dentists in Western Australia.

Authors:  P J Riordan; I Espelid; A B Tveit
Journal:  Community Dent Oral Epidemiol       Date:  1991-10       Impact factor: 3.383

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  6 in total

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Review 2.  Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)-A Systematic Review.

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3.  A Performance Comparison between Automated Deep Learning and Dental Professionals in Classification of Dental Implant Systems from Dental Imaging: A Multi-Center Study.

Authors:  Jae-Hong Lee; Young-Taek Kim; Jong-Bin Lee; Seong-Nyum Jeong
Journal:  Diagnostics (Basel)       Date:  2020-11-07

4.  Evaluation of dental caries detection with quantitative light-induced fluorescence in comparison to different field of view devices.

Authors:  Song Hee Oh; Jin-Young Choi; Seong-Hun Kim
Journal:  Sci Rep       Date:  2022-04-12       Impact factor: 4.379

5.  Artificial intelligence in digital cariology: a new tool for the diagnosis of deep caries and pulpitis using convolutional neural networks.

Authors:  Liwen Zheng; Haolin Wang; Li Mei; Qiuman Chen; Yuxin Zhang; Hongmei Zhang
Journal:  Ann Transl Med       Date:  2021-05

6.  Diagnosis of interproximal caries lesions with deep convolutional neural network in digital bitewing radiographs.

Authors:  Yusuf Bayraktar; Enes Ayan
Journal:  Clin Oral Investig       Date:  2021-06-25       Impact factor: 3.606

  6 in total

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