Division of Periodontics, Section of Oral and Diagnostic Sciences, College of Dental Medicine, Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
J Dent Res. 2011 Jul;90(7):855-60. doi: 10.1177/0022034511407069. Epub 2011 Apr 29.
Many diabetic patients remain undiagnosed, and oral findings may offer an unrealized opportunity for the identification of affected individuals unaware of their condition. We recruited 601 individuals who presented for care at a dental clinic, were ≥40 years old, if non-Hispanic white, and ≥30 years old, if Hispanic or non-white, and had never been told they have pre-diabetes or diabetes. Those with at least one self-reported diabetes risk factor (N=535) received a periodontal examination and a point-of-care hemoglobin A1c (HbA1c) test. A fasting plasma glucose (FPG) test was used as the study outcome, signifying potential diabetes or pre-diabetes. Performance characteristics of simple models of dysglycemia (FPG≥100 mg/dL) identification were evaluated and optimal cut-offs identified. A model including only two dental variables had an estimated area under the receiver operating characteristic curve (AUC) of 0.65. The addition of a point-of-care HbA1c test improved the AUC to 0.79 (p<0.001). The presence of ≥26% deep pockets or ≥4 missing teeth correctly identified 73% of true cases; the addition of an HbA1c≥5.7% increased correct identification to 92%. Analysis of our data suggests that oral healthcare professionals have the opportunity to identify unrecognized diabetes and pre-diabetes in dental patients and refer them to a physician for further evaluation and care.
许多糖尿病患者未被诊断出来，而口腔检查结果可能为那些尚未意识到自身病情的患者提供了一个尚未被充分利用的识别机会。我们招募了 601 名在牙科诊所就诊的个体，这些个体年龄均≥40 岁（若非西班牙裔白人）或≥30 岁（若是西班牙裔或非白人），且从未被告知患有前驱糖尿病或糖尿病。其中有至少一个自我报告的糖尿病风险因素（N=535）的个体接受了牙周检查和即时血红蛋白 A1c（HbA1c）检测。空腹血糖（FPG）检测用作研究结果，代表潜在的糖尿病或前驱糖尿病。我们评估了简单的糖代谢异常（FPG≥100mg/dL）识别模型的性能特征，并确定了最佳截断值。仅包含两个牙科变量的模型的接受者操作特征曲线（ROC）下面积（AUC）估计值为 0.65。添加即时 HbA1c 检测可将 AUC 提高至 0.79（p<0.001）。≥26%的深牙周袋或≥4 颗缺失牙齿的存在可正确识别 73%的真实病例；添加 HbA1c≥5.7%可将正确识别率提高至 92%。对我们数据的分析表明，口腔保健专业人员有机会在牙科患者中识别出未被识别的糖尿病和前驱糖尿病，并将他们转介给医生进行进一步评估和治疗。
