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口腔检查与未诊断的高血糖症的鉴定。

Dental findings and identification of undiagnosed hyperglycemia.

机构信息

Division of Periodontics, College of Dental Medicine.

出版信息

J Dent Res. 2013 Oct;92(10):888-92. doi: 10.1177/0022034513502791. Epub 2013 Aug 26.

DOI:10.1177/0022034513502791
PMID:23979781
Abstract

A change in the American Diabetes Association guidelines added hemoglobin A1c (HbA1c) to the assays for diabetes diagnosis, but evidence suggests that glucose vs. HbA1c criteria may identify different segments of the affected population. We previously demonstrated that oral findings offer an opportunity for the detection of undiagnosed abnormal fasting plasma glucose (FPG) among dental patients who present with diabetes risk factors. In this new cross-sectional study, we sought to extend these observations. The first goal, using data from 591 new participants, was to assess our previously identified hyperglycemia detection models when HbA1c is used for case definition. The second goal, using data from our total cohort of 1,097 participants, was to evaluate the models' performance regardless of whether an FPG or an HbA1c is used for diagnosis. The presence of ≥ 26% teeth with deep pockets or ≥ 4 missing teeth correctly identified 72% of pre-diabetes or diabetes cases in the HbA1c sample and 75% in the total population. The addition of a point-of-care HbA1c ≥ 5.7% increased correct identification to 87% and 90%, respectively. These results demonstrate the validity of our prediction models regardless of the test used for diabetes or pre-diabetes diagnosis in the clinical setting and underscore the contribution dentists can make.

摘要

美国糖尿病协会指南的一项变更将糖化血红蛋白(HbA1c)纳入了糖尿病诊断检测,但是有证据表明,血糖与 HbA1c 标准可能会识别出受影响人群的不同部分。我们之前的研究表明,口腔检查为发现有糖尿病风险因素的牙科患者中未确诊的异常空腹血糖(FPG)提供了机会。在这项新的横断面研究中,我们试图扩展这些观察结果。第一个目标是使用 591 名新参与者的数据,评估我们之前确定的当 HbA1c 用于病例定义时的高血糖检测模型。第二个目标是使用我们总共 1097 名参与者的数据,无论使用 FPG 还是 HbA1c 进行诊断,评估模型的性能。≥26%的牙齿有深牙周袋或≥4 颗缺失牙齿的存在正确识别了 HbA1c 样本中 72%的糖尿病前期或糖尿病病例,以及总人群中的 75%。添加即时 HbA1c≥5.7%可将正确识别率分别提高到 87%和 90%。这些结果表明,无论在临床环境中使用哪种检测方法来诊断糖尿病或糖尿病前期,我们的预测模型都是有效的,并强调了牙医的贡献。

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