Literature DB >> 23253824

Tooth loss, pocket depth, and HbA1c information collected in a dental care setting may improve the identification of undiagnosed diabetes.

Bruce A Dye1, Robert J Genco.   

Abstract

SUBJECTS: A total of 506 adults participated in this study. The study population was recruited from a pool of new patients presenting to the Columbia University College of Dental Medicine over a 12-month period (April 2009 to March 2010). New patients were screened to determine potential eligibility for participation based on 2 criteria: age and knowledge of their diabetes status. Non-Hispanic white adults were required to be 40 years old or older and Hispanic or non-white adults were required to be 30 years or older. Additionally, all potential participants had to respond that a health care provider had never told them that they had diabetes or prediabetes. This screening yielded 601 individuals. From this group, 535 were selected based on having 1 of 4 self-reported risk factors (hypertension, high cholesterol, overweight, or a family history of diabetes). These 535 adults continued with a periodontal examination and an HbA1c test. Five hundred six participants returned for a follow-up visit to collect blood for a fasting plasma glucose (FPG) test. KEY RISK/STUDY FACTOR: HbA1c test, and dentate and periodontal status. MAIN OUTCOME MEASURE: FPG level. MAIN
RESULTS: Among the 535 individuals participating in the study, 161 were determined potentially to be prediabetic (FPG was 100-125 mg/dL) and 21 potentially to be diabetic (FPG ≥ 126 mg/dL). Receiver operating characteristics (ROCs) via logistic regression was used to assess model performance and calculate key findings. The area under the curve of a multivariate regression model that included oral health status indicators and all 4 self-reported risk factors had a predicted value of 0.68 (confidence interval [CI]: 0.63, 0.73) for abnormal FPG (≥100 mg/dL). A model with just the percentage of periodontal pockets ≥5 mm and the number of missing teeth had a predicted value of 0.65 (CI: 0.60, 0.70). When the test results from HbA1C were added to the simpler model, the predictive value improved to 0.79 (CI: 0.75, 0.83). The authors also determined that the presence of 4 or more missing teeth or having pocket depth of 5 mm or more involving more than 25% of the sites identified 73% of the true cases (ie, abnormal FPG).
CONCLUSIONS: Dental care professionals have the potential to identify patients at risk for diabetes and refer them to a physician for follow-up evaluation.
Copyright © 2012. Published by Mosby, Inc. All rights reserved.

Entities:  

Year:  2012        PMID: 23253824     DOI: 10.1016/S1532-3382(12)70003-9

Source DB:  PubMed          Journal:  J Evid Based Dent Pract        ISSN: 1532-3382            Impact factor:   5.267


  3 in total

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Authors:  Kaustubh Sansare; Mamta Raghav; Abhiram Kasbe; Freny Karjodkar; Neeraj Sharma; Ambika Gupta; Harneet Singh; Asha Iyengar; Seema Patil; Sanarpalayam C Selvamuthukumar; Chandrasekaran Krithika; Michael Glick; Barbara L Greenberg
Journal:  Int Dent J       Date:  2015-07-14       Impact factor: 2.607

2.  A framework for physician-dentist collaboration in diabetes and periodontitis.

Authors:  Satheesh Elangovan; Ruth Hertzman-Miller; Nadeem Karimbux; Donald Giddon
Journal:  Clin Diabetes       Date:  2014-10

3.  Dentists' attitudes towards chairside medical conditions screening in a dental setting in Saudi Arabia: an exploratory cross-sectional Study.

Authors:  Saba Kassim; Badr Othman; Sakher AlQahtani; Alemad Mustafa Kawthar; Sterling M McPherson; Barbara L Greenberg
Journal:  BMC Oral Health       Date:  2019-08-06       Impact factor: 2.757

  3 in total

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